October 2024 arXiv papers — page 62

El-kaïoum M. Moutuou, Habib Benali

The brain's synaptic network, characterized by parallel connections and feedback loops, drives interaction pathways between neurons through a large system with infinitely many degrees of freedom. This system is best modeled by the graph C*-algebra of the underlying directed graph, the Toeplitz-Cuntz-Krieger (TCK) algebra, which captures the diversity of path

Dibyendu Das, Alfredo Fontanini, Joshua F. Kogan, Haibin Ling

Fully optimized automation of behavioral training protocols for lab animals like rodents has long been a coveted goal for researchers. It is an otherwise labor-intensive and time-consuming process that demands close interaction between the animal and the researcher. In this work, we used a data-driven approach to optimize the way rodents are trained in labs.

A. Çaksu Güler

Rough set theory is one of the most widely used and significant approaches for handling incomplete information. It divides the universe in the beginning and uses equivalency relations to produce blocks. Numerous generalized rough set models have been put out and investigated in an effort to increase flexibility and extend the range of possible uses. We intro

Juan Dávila, Manuel del Pino, Monica Musso, Shrish Parmeshwar

This paper addresses the long-time dynamics of solutions to the 2D incompressible Euler equations. We construct solutions with continuous vorticity $\omega_{\varepsilon}(x,t)$ concentrated around points $\xi_{j}(t)$ that converge to a sum of Dirac delta masses as $\varepsilon\to0$. These solutions are associated with the Kirchhoff-Routh point-vortex system,

Harald Schmid, Yang Peng, Gil Refael, Felix von Oppen

We study a stroboscopic quantum Ising model with Fibonacci dynamics. Focusing on boundary spin correlation functions in long but finite chains, our simulations as well as analytical arguments reveal a self-similar phase diagram exhibiting regions with Majorana zero modes (MZM) as well as Majorana golden-ratio modes (MGM). We identify the self-similarity tran

Margaret Kroll, Kelsey Kraus

The emergence of powerful LLMs has led to a paradigm shift in abstractive summarization of spoken documents. The properties that make LLMs so valuable for this task -- creativity, ability to produce fluent speech, and ability to abstract information from large corpora -- also present new challenges to evaluating their content. Quick, cost-effective automatic

Saeed Hajmohammadi, MohammadSadegh KhajueeZadeh, Farid Tootoonchian, Sajjad Mohammadi

Rotary transformers are commonly used in wound rotor resolvers to transfer excitation signals to the rotating winding without mechanical contact. In many analyses, the rotary transformer is modeled as an ideal transformer, where the voltage transfer ratio is assumed to be equal to the turns ratio. However, in miniature rotary transformers used in compact res

Karl Chahine, Hyeji Kim

In steganography, selecting an optimal cover image, referred to as cover selection, is pivotal for effective message concealment. Traditional methods have typically employed exhaustive searches to identify images that conform to specific perceptual or complexity metrics. However, the relationship between these metrics and the actual message hiding efficacy o

Sudarshan Srinivasan, Maria Mahbub, Amir Sadovnik

This position paper proposes a novel approach to advancing NLP security by leveraging Large Language Models (LLMs) as engines for generating diverse adversarial attacks. Building upon recent work demonstrating LLMs' effectiveness in creating word-level adversarial examples, we argue for expanding this concept to encompass a broader range of attack types, inc

Aline Favero, Heliudson Bernardo

Two formulations of superfluidity are reviewed: Landau's phenomenological two-fluid model and a relativistic effective field theory description. We demonstrate how the two-fluid formalism can be recovered from the nonrelativistic limit of the relativistic effective theory at finite temperatures. We show how self-gravitating, nonrelativistic superfluids are o

Luciano M. Abreu, Kanchan P. Khemchandani, Alberto Martínez Torres, Fernando S. Navarra

In this work we discuss how femtoscopic analysis can shed light on the nature of the two lightest axial charmed mesons, denominated as $D_1(2430)$ and $D_1(2420)$, whose masses are similar but widths are different. Their properties are reasonably described taking into account meson-meson coupled channel dynamics and a bare quark-model pole constituting the l

Pierre Goutagny, Aymeric Fromherz, Raphaël Monat

Many legal computations, including the amount of tax owed by a citizen, whether they are eligible to social benefits, or the wages due to civil state servants, are specified by computational laws. Their application, however, is performed by expert computer programs intended to faithfully transcribe the law into computer code. Bugs in these programs can lead

Cormac Breen, George Montagnon, Peter Taylor, Elizabeth Winstanley

We present a new mode-sum prescription for the efficient computation of renormalized expectation values for a massive, charged, quantum scalar field propagating on a curved space-time background. Our method is applicable to any static, spherically-symmetric, four-dimensional space-time with a time-independent, background electrostatic potential and can be us

Samuele Poppi, Zheng-Xin Yong, Yifei He, Bobbie Chern

Recent advancements in Large Language Models (LLMs) have sparked widespread concerns about their safety. Recent work demonstrates that safety alignment of LLMs can be easily removed by fine-tuning with a few adversarially chosen instruction-following examples, i.e., fine-tuning attacks. We take a further step to understand fine-tuning attacks in multilingual

Chia-Hsuan Lee, Hao Cheng, Mari Ostendorf

Large language models (LLMs) have demonstrated self-improvement capabilities via feedback and refinement, but current small language models (SLMs) have had limited success in this area. Existing correction approaches often rely on distilling knowledge from LLMs, which imposes significant computation demands. In this work, we introduce CORRECTIONLM, a novel c

Nasrin Azimi, Danial Mohammad Rezaei

Grading and quality control of Piarom dates, a premium and high-value variety cultivated predominantly in Iran, present significant challenges due to the complexity and variability of defects, as well as the absence of specialized automated systems tailored to this fruit. Traditional manual inspection methods are labor intensive, time consuming, and prone to

Mikhail Khrenov, Moon Tan, Lauren Fitzwater, Michelle Hobdari

Metal additive manufacturing (AM) opens the possibility for spatial control of as-fabricated microstructure and properties. However, since the solid state diffusional transformations that drive microstructure outcomes are governed by nonlinear ODEs in terms of temperature, which is itself governed by PDEs over the entire part domain, solving for the system i

Subhadip Bisal, Arindam Chatterjee, Debottam Das, Syed Adil Pasha

A Wino-like neutralino dark matter (DM) in the form of the lightest supersymmetric particle (LSP) has been considered one of the popular paradigms that can naturally accommodate {\it new physics} at a relatively higher scale, typically beyond the reach of the LHC. The constraint on the DM relic density typically implies a lightest neutralino mass $\simeq 2$

Subhadip Bisal, Arindam Chatterjee, Debottam Das, Syed Adil Pasha

The lightest neutralino ($\tilde{\chi}_1^0$) is a promising dark matter (DM) candidate in the R-parity conserving minimal supersymmetric standard model (MSSM). In this work, we focus on dominantly Higgsino-like and Wino-like $\tilde{\chi}_1^0$ DM, with small admixtures of gauginos and Higgsinos, respectively. In particular, we explore large one-loop correcti

Mark L. Lewis, Shannon M. Tefft

Let $D: \mathbb{Z}_m^n \to \mathbb{Z}_m^n$ be defined so \[D(x_1, x_2, ..., x_n)=(x_1+x_2 \; \text{mod} \; m, x_2+x_3 \; \text{mod} \; m, ..., x_n+x_1 \; \text{mod} \; m).\] $D$ is known as the Ducci function and for $\mathbf{u} \in \mathbb{Z}_m^n$, $\{D^{\alpha}(\mathbf{u})\}_{\alpha=0}^{\infty}$ is the Ducci sequence of $\mathbf{u}$. Every Ducci sequence e

Farshad Jafari, Farzad Didehvar, Amin Gheibi

The present paper investigated automatic melody construction for Persian lyrics as an input. It was assumed that there is a phonological correlation between the lyric syllables and the melody in a song. A seq2seq neural network was developed to investigate this assumption, trained on parallel syllable and note sequences in Persian songs to suggest a pleasant

Rohit Bokade, Xiaoning Jin

Multi-Agent Reinforcement Learning (MARL) presents a promising approach for addressing the complexity of Traffic Signal Control (TSC) in urban environments. However, existing platforms for MARL-based TSC research face challenges such as slow simulation speeds and convoluted, difficult-to-maintain codebases. To address these limitations, we introduce PyTSC, a

Rodolfo R. Soldati, Durga B. R. Dasari, Jörg Wrachtrup, Eric Lutz

Refrigeration limits are of fundamental and practical importance. We here show that quantum systems can be cooled below existing incoherent cooling bounds by employing coherent virtual qubits, even if the amount of coherence is incompletely known. Virtual subsystems, that do not necessarily correspond to a natural eigensubspace of a system, are a key concept

Jiantao Wu, Sara Atito, Zhenhua Feng, Shentong Mo

The training methods in AI do involve semantically distinct pairs of samples. However, their role typically is to enhance the between class separability. The actual notion of similarity is normally learned from semantically identical pairs. This paper presents SimLAP: a simple framework for learning visual representation from arbitrary pairs. SimLAP explores

Marco Turchetta, Manuel Linares, Karri Koljonen, Jorge Casares

We report here the results obtained from a systematic optical photometric survey aimed at finding new compact binary millisecond pulsars (also known as "spiders"): the COmpact BInary PULsar SEarch (COBIPULSE). We acquired multi-band optical images over one year around $33$ unidentified Fermi-LAT sources, selected as pulsar candidates based on their curved Ge

Basabendu Barman, Subhaditya Bhattacharya, Sahabub Jahedi, Dipankar Pradhan

Dark matter (DM) genesis via Ultraviolet (UV) freeze-in embeds the seed of reheating temperature and dynamics in its relic density. Thus, discovery of such a DM candidate can possibly open the window for post-inflationary dynamics. However, there are several challenges in this exercise, as freezing-in DM possesses feeble interaction with the visible sector a

Annamária Friedl-Szász, Elena Popovici-Popescu, Nicoleta Voicu, Christian Pfeifer

We locally classify all possible cosmological homogeneous and isotropic Landsberg-type Finsler structures, in 4-dimensions. Among them, we identify viable non-stationary Finsler spacetimes, i.e. those geometries leading to a physical causal structure and a dynamical universe. Noting that any non-stationary Landsberg metric must be actually non-Berwaldian (i.

Andi Gu, Yihui Quek, Susanne Yelin, Jens Eisert

Quantum chaos is a quantum many-body phenomenon that is associated with a number of intricate properties, such as level repulsion in energy spectra or distinct scalings of out-of-time ordered correlation functions. In this work, we introduce a novel class of "pseudochaotic" quantum Hamiltonians that fundamentally challenges the conventional understanding of

Peter C. B. Smith, Jorge A. Sanchez, Michael R. Line, Emily Rauscher

A primary goal of exoplanet science is to measure the atmospheric composition of gas giants in order to infer their formation and migration histories. Common diagnostics for planet formation are the atmospheric metallicity ([M/H]) and the carbon-to-oxygen (C/O) ratio as measured through transit or emission spectroscopy. The C/O ratio in particular can be use

Luca Barsellotti, Roberto Bigazzi, Marcella Cornia, Lorenzo Baraldi

In the last years, the research interest in visual navigation towards objects in indoor environments has grown significantly. This growth can be attributed to the recent availability of large navigation datasets in photo-realistic simulated environments, like Gibson and Matterport3D. However, the navigation tasks supported by these datasets are often restric

Elyas Obbad, Iddah Mlauzi, Brando Miranda, Rylan Schaeffer

Data selection is crucial for optimizing language model (LM) performance on specific tasks, yet most existing methods fail to effectively consider the target task distribution. Current approaches either ignore task-specific requirements entirely or rely on approximations that fail to capture the nuanced patterns needed for tasks like Autoformalization or cod

M. S. Silcock, E. Curtis-Lake, D. J. B. Smith, I. E. B. Wallace

The presence of Active Galactic Nuclei (AGN) in low mass (Mstar $\lesssim$ $10^{9}$ Msun) galaxies at high redshift has been established, and it is important to characterise these objects and the impact of their feedback on the host galaxies. In this paper we apply the Spectral Energy Distribution (SED) fitting code BEAGLE-AGN to SMACS S06355, a z $\sim$ 7.6

Raphael Bousso, Elisa Tabor

The Quantum Focusing Conjecture (QFC) lies at the foundation of holography and semiclassical gravity. The QFC implies the Bousso bound and the Quantum Null Energy Condition (QNEC). The QFC also ensures the consistency of the quantum extremal surface prescription and bulk reconstruction in AdS/CFT. However, the central object in the QFC -- the expansion of li

Ottavia Truttero, Joe Zuntz, Alkistis Pourtsidou, Naomi Robertson

Accurately modelling matter power spectrum effects at small scales, such as baryonic feedback, is essential to avoid significant bias in the estimation of cosmological parameters with cosmic shear. However, Stage IV surveys like LSST will be so precise that significant information can still be extracted from large scales alone. In this work, we simulate LSST

Zhibo Yu, W. N. Brandt, Fan Zou, Ziyuan Zhu

Dust-obscured galaxies (DOGs) are enshrouded by dust, and many are believed to host accreting supermassive black holes (SMBHs), which makes them unique objects for probing the coevolution of galaxies and SMBHs. We select and characterize DOGs in the $13\,deg^2$ XMM-Spitzer Extragalactic Representative Volume Survey (XMM-SERVS), leveraging the superb multiwav

Evan Linck, Robert D. Mathieu, David W. Latham

NGC 2506 is a rich, intermediate-age (2.0 Gyr), metal-poor ([Fe/H] $\sim$ -0.2) open cluster. This work presents the results of 12,157 spectroscopic radial-velocity measurements of 2,442 stars in the NGC 2506 field over 41 years, made as part of the WIYN Open Cluster Study. Radial-velocity measurements are complete for the population of proper-motion member

Akhil Sivakumar

We construct black hole saddles dual to real-time/Schwinger-Keldysh (SK) path integrals with arbitrary splits of the thermal density matrix generalizing the holographic SK prescription in \cite{Glorioso:2018mmw}. Using a scalar probe on the AdS Schwarzschild black brane as an example, we demonstrate how KMS properties of the boundary correlators naturally de

Maria Jose Colmenares, Edwin Bergin, Colette Salyk, Klaus M. Pontopiddan

It has been proposed, and confirmed by multiple observations, that disks around low mass stars display a molecule-rich emission and carbon-rich disk chemistry as compared to their hotter, more massive solar counterparts. In this work, we present JWST Disk Infrared Spectral Chemistry Survey (JDISCS) MIRI-MRS observations of the solar-mass star DoAr 33, a low-

Marcin Badziak, Maxim Laletin

We compute the QCD axion contribution to the energy density of dark radiation, parameterized by $\Delta N_{\rm eff}$, by solving Boltzmann equations for the momentum distribution functions including the effects of quantum statistics for all particles involved in the axion production processes. This approach gives precise prediction for $\Delta N_{\rm eff}$ i

Stefano Ebagezio, Daniel Seifried, Stefanie Walch, Thomas G. Bisbas

We analyse synthetic maps of the [CII] 158 $\mu$m line and FIR continuum of simulated molecular clouds (MCs) within the SILCC-Zoom project to study the origin of the [CII] deficit, i.e., the drop in the [CII]/FIR intensity ratio. All simulations include stellar radiative feedback and account for further ionisation of C$^+$ into C$^{2+}$ inside HII regions. F

S. Britzen, A. B. Kovačević, M. Zajaček, L. Č. Popović

The BL Lac Object PKS 1717+177 has been identified as potential neutrino-emitting AGN in the point source stacking analysis of IceCube data. We explore peculiarities in the morphology and kinematics of the jet and examine multi-wavelength light curves for distinctive effects which might allow to pinpoint a likely neutrino generation mechanism. We re-modeled

Stefan Pelletier, Björn Benneke, Yayaati Chachan, Luc Bazinet

One of the outstanding goals of the planetary science community is to measure the present-day atmospheric composition of planets and link this back to formation. As giant planets are formed by accreting gas, ices, and rocks, constraining the relative amounts of these components is critical to understand their formation and evolution. For most known planets,

Himansh Rathore, Yumi Choi, Knut A. G. Olsen, Gurtina Besla

We present new measurements of the two-dimensional (2-D) geometry of the LMC's stellar bar with precise astrometric observations of red clump stars in Gaia DR3. We develop a novel solution to tackle crowding induced incompleteness in Gaia datasets with the Gaia BP-RP color excess. Utilizing the color excess information, we derive a 2-D completeness map of th

Ryan J. MacDonald

Spectroscopic observations of exoplanet atmospheres can reveal the chemical composition, temperature, cloud properties, and (potentially) the habitability of these distant worlds. The inference of such properties is generally enabled by Bayesian atmospheric retrieval algorithms. However, until recently, many retrieval codes have not been publicly available.

Samuel Rusterucci, Nicolas F. Martin, Else Starkenburg, Rodrigo Ibata

We provide an updated inference of the proper motion of M31 using the Gaia DR3 proper motions of bright stars from the disc of M31. By refining the motion of the quasar reference frame, and statistically accounting for the variations in the inferred proper motions obtained across different regions of M31, we demonstrate that these inconsistencies most likely

Irene Ferranti, Mikel Falxa, Alberto Sesana, Aurelien Chalumeau

Pulsar Timing Array (PTA) collaborations gather high-precision timing measurements of pulsars with the aim of detecting gravitational wave (GW) signals. A major challenge lies in the identification and characterization of the different sources of noise that may hamper their sensitivity to GWs. The presence of time-correlated noise that resembles the target s

Guang Hao Low, Yuan Su

Quantum algorithms for linear systems produce the solution state $A^{-1}|b\rangle$ by querying two oracles: $O_A$ that block encodes the coefficient matrix and $O_b$ that prepares the initial state. We present a quantum linear system algorithm making $\mathbf{\Theta}\left(1/\sqrt{p}\right)$ queries to $O_b$, which is optimal in the success probability, and $

Juliane Haug, Fabian Wunder

Angular integrals arise in a wide range of perturbative quantum field theory calculations. In this work we investigate angular integrals with three denominators in $d=4-2\varepsilon$ dimensions. We derive integration-by-parts relations for this class of integrals, leading to explicit recursion relations and a reduction to a small set of master integrals. Usi

Moritz Kade

We propose a double-scaling limit of $\beta$-deformed ABJM theory in three-dimensional $\mathcal{N} = 2$ superspace, and a non-local deformation thereof. Due to the regular appearance of the theory's Feynman supergraphs, we refer to this superconformal and integrable theory as the superfishnet theory. We use techniques inspired by the integrability of bi-sca

Stefan Divic, Valentin Crépel, Tomohiro Soejima, Xue-Yang Song

We argue that the combination of strong repulsive interactions and high magnetic fields can generate electron pairing and superconductivity. Inspired by the large lattice constants of moir\'e materials, which make large flux per unit cell accessible at laboratory fields, we study the triangular lattice Hofstadter-Hubbard model at one-quarter flux quantum per

Indranil Dey, Sridip Pal, Jiaxin Qiao

We prove the conjecture proposed by Hartman, Keller and Stoica [HKS14]: the grand-canonical free energy of a unitary 2D CFT with a sparse spectrum below the scaling dimension $\frac{c}{12}+\epsilon$ and below the twist $\frac{c}{12}$ is universal in the large $c$ limit for all $\beta_L\beta_R \neq 4\pi^2$. The technique of the proof allows us to derive a one

Shota Komatsu, Adrien Martina, João Penedones, Antoine Vuignier

We construct backreacted geometries dual to the supersymmetric mass deformation of the IKKT matrix model. They are Euclidean type IIB supergravity solutions given in terms of an electrostatic potential, having $SO(7)\times SO(3)$ isometry and 16 supersymmetries. Quantizing the fluxes, we find that the supergravity solutions are in one-to-one correspondence w

Pieter Bomans, Lorenzo Tranchedone

Spindle and disc solutions have received significant attention in recent literature. However, it is not entirely clear what these supergravity solutions represent in the dual SCFT. In this work we elucidate this issue by considering a different global completion of the spindle solution, focusing on a single conical defect. We argue that these solutions can b

R. Buscicchio, J. Torrado, C. Caprini, G. Nardini

Stellar-mass black-hole binaries are the most numerous gravitational-wave sources observed to date. Their properties make them suitable for observation both by ground- and space-based detectors. Starting from synthetic catalogues constructed based on observational constraints from ground-based detectors, we explore the detection rates and the characteristic

Amir Siraj, Christopher F. Chyba, Scott Tremaine

The plausibility of an unseen planet in the outer solar system, and the expected orbit and mass of such a planet, have long been a topic of inquiry and debate. We calculate the long-term orbital stability of distant TNOs, which allows us to expand the sample of objects that would carry dynamical information about a hypothetical unseen planet in the solar sys

G. Piotto, T. Zingales, L. Borsato, J. A. Egger

We present new observations from CHEOPS and TESS to clarify the architecture of the planetary system hosted by the old Galactic thick disk star TOI-561. Our global analysis, which also includes previously published photometric and radial velocity data, incontrovertibly proves that TOI-561 is hosting at least four transiting planets with periods of 0.44 days

Aditya Parikh, Ryosuke Sato, Tracy R. Slatyer

Long-range attractive interactions between dark matter particles can significantly enhance their annihilation, particularly at low velocities. This ``Sommerfeld enhancement'' is typically computed by evaluating the deformation of the two-particle wavefunction due to the long-range potential, while ignoring the physics associated with the annihilation, and th

Jake Xuereb, A. de Oliveira Junior, Fabien Clivaz, Pharnam Bakhshinezhad

Whilst the complexity of acquiring knowledge of a quantum state has been extensively studied in the fields of quantum tomography and quantum learning, a physical understanding of its operational role and cost in quantum thermodynamics is lacking. Knowledge is central to thermodynamics, as exemplified by Maxwell's demon thought experiment, where a demonic age

Sven Möller, Brandon C. Rayhaun

When can two strongly rational vertex operator algebras or 1+1d rational conformal field theories (RCFTs) be related by topological manipulations? For vertex operator algebras, the term "topological manipulations" refers to operations like passing to a conformal extension or restricting to a conformal subalgebra; for RCFTs, topological manipulations include

Mauro Sereno, Sophie Maurogordato, Alberto Cappi, Rafael Barrena

The Cluster HEritage project with XMM-Newton - Mass Assembly and Thermodynamics at the Endpoint of structure formation (CHEX-MATE) is a programme to study a minimally biased sample of 118 galaxy clusters detected by Planck through the Sunyaev-Zeldovich effect. Accurate and precise mass measurements are required to exploit CHEX-MATE as an astrophysical labora

Junwei Ma, Valentin Thomas, Rasa Hosseinzadeh, Alex Labach

Tabular data is one of the most ubiquitous sources of information worldwide, spanning a wide variety of domains. This inherent heterogeneity has slowed the development of Tabular Foundation Models (TFMs) capable of fast generalization to unseen datasets. In-Context Learning (ICL) has recently emerged as a promising solution for TFMs, enabling dynamic adaptat

Hengwei Bian, Lingdong Kong, Haozhe Xie, Liang Pan

Urban scene generation has been developing rapidly recently. However, existing methods primarily focus on generating static and single-frame scenes, overlooking the inherently dynamic nature of real-world driving environments. In this work, we introduce DynamicCity, a novel 4D occupancy generation framework capable of generating large-scale, high-quality dyn

Yang-Che Sun, Cheng Yu Yeo, Ernie Chu, Jun-Cheng Chen

In this work, we propose using a unified representation, termed Factorized Features, for low-level vision tasks, where we test on Single Image Super-Resolution (SISR) and \textbf{Image Compression}. Motivated by the shared principles between these tasks, they require recovering and preserving fine image details, whether by enhancing resolution for SISR or re

Renhao Wang, Kevin Frans, Pieter Abbeel, Sergey Levine

Sample-efficient online reinforcement learning often uses replay buffers to store experience for reuse when updating the value function. However, uniform replay is inefficient, since certain classes of transitions can be more relevant to learning. While prioritization of more useful samples is helpful, this strategy can also lead to overfitting, as useful sa

David Díaz-Guerra, Conrado Albertus, Prasanta Char, M. Ángeles Pérez-García

Astrophysical compact objects are usually studied using a perfect fluid model. However, in astrophysical processes out-of-equilibrium, dissipative effects become important to describe the dynamics of the system. In this work, we obtain gauge-invariant non-spherical perturbations of a self-gravitating non-perfect fluid in spherical spacetime. We use the Gerla

Laura Posch, João Alves, Nuria Mirét-Roig, Sebastian Ratzenböck

We explore the kinematics and star formation history of the Scorpius Centaurus (Sco-Cen) OB association following the initial identification of sequential, linearly aligned chains of clusters. Building upon our characterization of the Corona Australis (CrA) chain, we now analyze two additional major cluster chains that exhibit similar characteristics: the Lo

Qitai Wang, Lue Fan, Yuqi Wang, Yuntao Chen

Existing reconstruction-based novel view synthesis methods for driving scenes focus on synthesizing camera views along the recorded trajectory of the ego vehicle. Their image rendering performance will severely degrade on viewpoints falling out of the recorded trajectory, where camera rays are untrained. We propose FreeVS, a novel fully generative approach t

M. I. Rodríguez, U. Lisenfeld, S. Duarte Puertas, D. Espada

Cosmic voids, distinguished by their low-density environment, provide a unique opportunity to explore the interplay between the cosmic environment and the processes of galaxy formation and evolution. Data on the molecular gas has been scarce so far. In this paper, we continue previous research done in the CO-CAVITY pilot project to study the molecular gas co

Peter Shaw, James Cohan, Jacob Eisenstein, Kenton Lee

We propose a new programming language called ALTA and a compiler that can map ALTA programs to Transformer weights. ALTA is inspired by RASP, a language proposed by Weiss et al. (2021), and Tracr (Lindner et al., 2023), a compiler from RASP programs to Transformer weights. ALTA complements and extends this prior work, offering the ability to express loops an

Max Wilcoxson, Qiyang Li, Kevin Frans, Sergey Levine

Unsupervised pretraining has been transformative in many supervised domains. However, applying such ideas to reinforcement learning (RL) presents a unique challenge in that fine-tuning does not involve mimicking task-specific data, but rather exploring and locating the solution through iterative self-improvement. In this work, we study how unlabeled offline

Xue Zheng, Tian Xie, Xuwei Tan, Aylin Yener

Performative prediction is a framework that captures distribution shifts that occur during the training of machine learning models due to their deployment. As the trained model is used, data generation causes the model to evolve, leading to deviations from the original data distribution. The impact of such model-induced distribution shifts in federated learn

Xien Chen, Rit Gangopadhyay, Michael Chu, Patrick Rim

We propose UnCLe, the first standardized benchmark for Unsupervised Continual Learning of a multimodal 3D reconstruction task: Depth completion aims to infer a dense depth map from a pair of synchronized RGB image and sparse depth map. We benchmark depth completion models under the practical scenario of unsupervised learning over continuous streams of data.

Robert D Kavanagh, Harish K Vedantham, Kovi Rose, Sanne Bloot

At the sub-stellar boundary, signatures of magnetic fields begin to manifest at radio wavelengths, analogous to the auroral emission of the magnetised solar system planets. This emission provides a singular avenue for measuring magnetic fields at planetary scales in extrasolar systems. So far, exoplanets have eluded detection at radio wavelengths. However, u

Yiran Qin, Zhelun Shi, Jiwen Yu, Xijun Wang

Recent advancements in predictive models have demonstrated exceptional capabilities in predicting the future state of objects and scenes. However, the lack of categorization based on inherent characteristics continues to hinder the progress of predictive model development. Additionally, existing benchmarks are unable to effectively evaluate higher-capability

Yuxuan Xie, Tianhua Li, Wenqi Shao, Kaipeng Zhang

Recently, multimodal large language models (MLLMs) have received much attention for their impressive capabilities. The evaluation of MLLMs is becoming critical to analyzing attributes of MLLMs and providing valuable insights. However, current benchmarks overlook the problem of prompt sensitivity - minor prompt variations may lead to significant performance f

Luran Wang, Chaoran Cheng, Yizhen Liao, Yanru Qu

Controlled generation with pre-trained Diffusion and Flow Matching models has vast applications. One strategy for guiding ODE-based generative models is through optimizing a target loss $R(x_1)$ while staying close to the prior distribution. Along this line, some recent work showed the effectiveness of guiding flow model by differentiating through its ODE sa

Andrei Katsevich

We study RG flows between non-unitary minimal models and massive quantum theories using Truncated Conformal Space Approach (TCSA). We consider the integrable non-unitary Yang-Lee model perturbed by $i\phi$ and the $D$-series version of $M(3,10)$ which is a product of two Yang-Lee models, perturbing the latter by relevant operators $\phi_{1,3}$ and $i\phi^+_{

Samar M. Magdy, Fakhraddin Alwajih, Sang Yun Kwon, Reem Abdel-Salam

Writing has long been considered a hallmark of human intelligence and remains a pinnacle task for artificial intelligence (AI) due to the intricate cognitive processes involved. Recently, rapid advancements in generative AI, particularly through the development of Large Language Models (LLMs), have significantly transformed the landscape of writing assistanc

Jonathan Rawlinson

According to a result of Wigner and von Neumann [1], real symmetric matrices with a doubly degenerate lowest eigenvalue form a submanifold of codimension 2 within the space of all real symmetric matrices. This mathematical result has important consequences for chemistry. First, it implies that degeneracies do not occur within generic one-parameter families o

Valeria Ruscio, Umberto Nanni, Fabrizio Silvestri

This paper studies how Transformer models with Rotary Position Embeddings (RoPE) develop emergent, wavelet-like properties that compensate for the positional encoding's theoretical limitations. Through an analysis spanning model scales, architectures, and training checkpoints, we show that attention heads evolve to implement multi-resolution processing analo

Raman Ebrahimi, Kristen Vaccaro, Parinaz Naghizadeh

When humans are subject to an algorithmic decision system, they can strategically adjust their behavior accordingly (``game'' the system). While a growing line of literature on strategic classification has used game-theoretic modeling to understand and mitigate such gaming, these existing works consider standard models of fully rational agents. In this paper

Zihan Zhou, Animesh Garg, Dieter Fox, Caelan Garrett

Robot learning has proven to be a general and effective technique for programming manipulators. Imitation learning is able to teach robots solely from human demonstrations but is bottlenecked by the capabilities of the demonstrations. Reinforcement learning uses exploration to discover better behaviors; however, the space of possible improvements can be too

José Correia, Mark Hindmarsh, Joanes Lizarraga, Asier Lopez-Eiguren

We report on a study of axion string networks using fixed-grid simulations of up to $16384$ points per side. The length of string can be characterised in terms of standard dimensionless parameters $\zeta_\text{w}$ and $\zeta_\text{r}$, the length density measured in the cosmic rest frame and the string rest frame, scaled with the cosmic time. The motion of t

Hengxin Tan, Binghai Yan

The discovery of a charge density wave (CDW) in the antiferromagnetic kagome metal FeGe has prompted interest in the interplay between kagome physics, CDW, and magnetism. However, a crucial aspect for understanding these emergent phenomena-the precise CDW structure-remains ambiguous. Recent studies have assumed uniformly distributed Ge dimers, but this assum

Matthew D. Beckman, Sean Burke, Jack Fiochetta, Benjamin Fry

Undergraduate graders are frequently important contributors to an instructional team in post-secondary education settings. This study set out to investigate agreement for a team of undergraduate graders as they acquired training and experience for scoring responses to open-ended tasks. Results demonstrate evidence that undergraduate graders can develop the a

XLZD Collaboration, J. Aalbers, K. Abe, M. Adrover

The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60 to 80 t capable of probing the remaining WIMP-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that, based on the performance of currently operating detectors using the same technology and a realistic reduction

Anirban Bhaduri, Isaac Goldberg, Antonios-Alexandros Robotis

We compute several types of dimension for the bounded derived categories of coherent sheaves of orbifold curves. This completes the calculation of these dimensions for derived categories of noncommutative curves in the sense of Reiten-van den Bergh. Along the way we construct stability conditions for orbifold curves. We also obtain a characterisation of orbi

Jaime Sevilla, Nikolay Babakov, Ehud Reiter, Alberto Bugarin

In this paper, we propose a model for building natural language explanations for Bayesian Network Reasoning in terms of factor arguments, which are argumentation graphs of flowing evidence, relating the observed evidence to a target variable we want to learn about. We introduce the notion of factor argument independence to address the outstanding question of

Mohamed Habib Aliou Diallo Aoudi, Pascal Moyal, Vincent Robin

In this work, we propose a large-graph limit estimate of the matching coverage for several matching algorithms, on general graphs generated by the configuration model. For a wide class of {\em local} matching algorithms, namely, algorithms that only use information on the immediate neighborhood of the explored nodes, we propose a joint construction of the gr

Ronald Orozco López

In this paper, we introduce the Heine binomial operators H$_{n}(bD_{q})$ based on $q$-differential operator $D_{q}$. The motivation for introducing the operators H$_{n}(bD_{q})$ is that their limit turns out to be the $q$-exponential operator T$(bD_{q})$ given by Chen. The Hahn polynomials $\Phi_{m}^{(q^n)}(b,x|q)$ can easily be represented by using the oper

Alexey Dontsov, Dmitrii Korzh, Alexey Zhavoronkin, Boris Mikheev

Machine Unlearning (MU) is critical for removing private or hazardous information from deep learning models. While MU has advanced significantly in unimodal (text or vision) settings, multimodal unlearning (MMU) remains underexplored due to the lack of open benchmarks for evaluating cross-modal data removal. To address this gap, we introduce CLEAR, the first

Esra Güldoğan Lekesiz, Bayram Çekim, Mehmet Ali Özarslan

A new set of finite 2D biorthogonal polynomials is defined using the finite orthogonal polynomials $N_{n}^{(p)}(w)$ and the Konhauser polynomials. We present a connection between this finite 2D biorthogonal set and the generalized Laguerre-Konhauser polynomials. Also, we obtain several applications of finite bivariate biorthogonal $N$-Konhauser polynomials.

Andrea Stocco, Konstantinos Mitsopoulos, Yuxue C. Yang, Holly S. Hake

Cognitive architectures are influential, integrated computational frameworks for modeling cognitive processes. Due to a variety of factors, however, researchers using cognitive architectures to explain and predict human performance rarely employ model validation, comparison, and selection techniques based on likelihood. This paper provides a primer on how to

Huasheng Xie

The physical goal of fusion energy research is to confine fusion fuel in a certain way so that the energy released from fusion exceeds the energy consumed to sustain the fusion process, thereby achieving economically viable energy production. Based on fundamental physics, this book focuses on the physics of the core region in fusion energy reactors, discussi

Gaspard Thévenon, Kevin Nguetchouang, Kahina Lazri, Alain Tchana

System call filtering is widely used to secure programs in multi-tenant environments, and to sandbox applications in modern desktop software deployment and package management systems. Filtering rules are hard to write and maintain manually, hence generating them automatically is essential. To that aim, analysis tools able to identify every system call that c

Md Rahatul Islam Udoy, Md Mazharul Islam, Elijah Johnson, Ahmedullah Aziz

This paper presents an innovative in-pixel contrast enhancement circuit that performs image processing directly within the pixel circuit. The circuit can be tuned for different modes of operation. In foreground enhancement mode, it suppresses low-intensity background pixels to nearly zero, isolating the foreground for better object visibility. In contrast en

Fabien Poirier

Nowadays, many places use security cameras. Unfortunately, when an incident occurs, these technologies are used to show past events. So it can be considered as a deterrence tool than a detection tool. In this article, we will propose a deep learning approach trying to solve this problematic. This approach uses convolutional models (CNN) to extract relevant c

Qingfei Zhao, Ruobing Wang, Yukuo Cen, Daren Zha

Long-Context Question Answering (LCQA), a challenging task, aims to reason over long-context documents to yield accurate answers to questions. Existing long-context Large Language Models (LLMs) for LCQA often struggle with the "lost in the middle" issue. Retrieval-Augmented Generation (RAG) mitigates this issue by providing external factual evidence. However

João Faria Martins, Catherine Meusburger

We give a simple, geometric and explicit construction of 3d untwisted Dijkgraaf-Witten theory with defects of all codimensions. It is given as a symmetric monoidal functor from a defect cobordism category into the category of finite-dimensional complex vector spaces. The objects of this category are oriented stratified surfaces and its morphisms are equivale

Gérard Ben Arous, Cédric Gerbelot, Vanessa Piccolo

We study the high-dimensional dynamics of online stochastic gradient descent (SGD) for the multi-spiked tensor model. This multi-index model arises from the tensor principal component analysis (PCA) problem with multiple spikes, where the goal is to estimate $r$ unknown signal vectors within the $N$-dimensional unit sphere through maximum likelihood estimati