March 2024 arXiv papers — page 23

Christian Camilo Silva Villamil

Let $\varphi_0$ be a $C^2$-conservative diffeomorphism of a compact surface $S$ and let $\Lambda_0$ be a mixing horseshoe of $\varphi_0$. Given a smooth real function $f$ defined in $S$ and some diffeomorphism $\varphi$, close to $\varphi_0$, let $\mathcal{L}_{\varphi, f}$ be the Lagrange spectrum associated to the hyperbolic continuation $\Lambda(\varphi)$

Raphael Galicher, Axel Potier, Johan Mazoyer, Zahed Wahhaj

Imaging exoplanetary systems is essential to characterizing exoplanetary systems and to studying planet-disk interactions to understand planet formation. Such imaging in the visible and near-infrared is challenging because these objects are very faint relative to their star and only fractions of an arcsecond away. Coronagraphic instruments have already allow

Laura Bergomi, Tommaso M. Buonocore, Paolo Antonazzo, Lorenzo Alberghi

BACKGROUND: Radiology reports are typically written in a free-text format, making clinical information difficult to extract and use. Recently the adoption of structured reporting (SR) has been recommended by various medical societies thanks to the advantages it offers, e.g. standardization, completeness and information retrieval. We propose a pipeline to ext

Jonathan Sorce

The Unruh effect can be formulated as the statement that the Minkowski vacuum in a Rindler wedge has a boost as its modular flow. In recent years, other examples of states with geometrically local modular flow have played important roles in understanding energy and entropy in quantum field theory and quantum gravity. Here I initiate a general study of the se

Yiqi Xie, Deep Chatterjee, Gautham Narayan, Nicolás Yunes

The parametrized post-Einsteinian (ppE) framework and its variants are widely used to probe gravity through gravitational-wave tests that apply to a large class of theories beyond general relativity. However, the ppE framework is not truly theory-agnostic as it only captures certain types of deviations from general relativity: those that admit a post-Newtoni

Mohammad Moltafet, Hamid R. Sadjadpour, Zouheir Rezki

In the bounded storage model introduced by Maurer, the adversary is computationally unbounded and has a bounded storage capacity. In this model, information-theoretic secrecy is guaranteed by using a publicly available random string whose length is larger than the adversary storage capacity. The protocol proposed by Maurer is simple, from the perspective of

Ariel Tarifeno-Saldivia, Francisco Calvino, Alfredo De Blas, Benedetta Brusasco

The status of the LINrem project is presented, focusing on the development of innovative neutron dosimeters with enhanced energy sensitivity, time resolution, and portability. Designed to meet the technical demands of radiation protection in modern particle and nuclear facilities, these dosimeters are discussed in detail. Results from experimental campaigns

Nedjma Ousidhoum, Shamsuddeen Hassan Muhammad, Mohamed Abdalla, Idris Abdulmumin

We present the first shared task on Semantic Textual Relatedness (STR). While earlier shared tasks primarily focused on semantic similarity, we instead investigate the broader phenomenon of semantic relatedness across 14 languages: Afrikaans, Algerian Arabic, Amharic, English, Hausa, Hindi, Indonesian, Kinyarwanda, Marathi, Moroccan Arabic, Modern Standard A

Yejin Bang, Delong Chen, Nayeon Lee, Pascale Fung

We propose to measure political bias in LLMs by analyzing both the content and style of their generated content regarding political issues. Existing benchmarks and measures focus on gender and racial biases. However, political bias exists in LLMs and can lead to polarization and other harms in downstream applications. In order to provide transparency to user

Nora Doll, Terry Loring, Hermann Schulz-Baldes

A variety of local index formulas is constructed for quantum Hamiltonians with periodic boundary conditions. All dimensions of physical space as well as many symmetry constraints are covered, notably one-dimensional systems in Class DIII as well as two- and three-dimensional systems in Class AII. The constructions are based on several periodic variations of

Grgur Palle

In a series of recent articles, Liu, Yang, Pan, et al. claim to have determined the exact dressed electron-boson vertex for a number of very general interacting many-body problems by inverting certain Ward-Takahashi identities. Here, we point out that their Ward-Takahashi identities are missing terms which make the inversion of the identities impossible. One

Angelo Felice Lopez, Debaditya Raychaudhury

We characterize $q$-ample Ulrich bundles on a variety $X \subseteq \mathbb P^N$ with respect to $(q+1)$-dimensional linear spaces contained in $X$.

Dhrumil Patel, Shi Jie Samuel Tan, Yigit Subasi, Andrew T. Sornborger

Due to its significance as a subroutine, in this work, we consider the coherent version of the quantum phase estimation problem, where given an arbitrary input state and black-box access to unitaries $U$ and controlled-$U$, the goal is to estimate the phases of $U$ in superposition. Most existing phase estimation algorithms involve intermediary measurements

Stan Gudder

This article begins with a study of convex effect-state spaces. We point out that such spaces are equivalent to interval effect algebras that generate an ordered linear space and possess an order-determining set of states. We then discuss operations and instruments on interval effect algebras under the assumption of an unrestrictive condition. Effects measur

Pritam Kumar Bhoi, Rudranarayan Padhy, Sudhansu Sekhar Rout

Let $(X_{k})_{k\geq 1}$ and $(Y_k)_{k\geq 1}$ be the sequence of $X$ and $Y$-coordinates of the positive integer solutions $(x, y)$ of the equation $x^2 - dy^2 = t$. In this paper we completely describe those recurrence sequences such that sums of two terms recurrence sequences in the solution sets of generalized Pell equations are infinitely many. Further,

Mukund Varma T, Peihao Wang, Zhiwen Fan, Zhangyang Wang

In recent years, there has been an explosion of 2D vision models for numerous tasks such as semantic segmentation, style transfer or scene editing, enabled by large-scale 2D image datasets. At the same time, there has been renewed interest in 3D scene representations such as neural radiance fields from multi-view images. However, the availability of 3D or mu

Petros Toupas, Zhewen Yu, Christos-Savvas Bouganis, Dimitrios Tzovaras

Convolutional Neural Networks (CNNs) have demonstrated their effectiveness in numerous vision tasks. However, their high processing requirements necessitate efficient hardware acceleration to meet the application's performance targets. In the space of FPGAs, streaming-based dataflow architectures are often adopted by users, as significant performance gains c

Oliver Klingefjord, Ryan Lowe, Joe Edelman

There is an emerging consensus that we need to align AI systems with human values (Gabriel, 2020; Ji et al., 2024), but it remains unclear how to apply this to language models in practice. We split the problem of "aligning to human values" into three parts: first, eliciting values from people; second, reconciling those values into an alignment target for tra

Aditya Golatkar, Alessandro Achille, Luca Zancato, Yu-Xiang Wang

Retrieval Augmented Generation (RAG) is emerging as a flexible and robust technique to adapt models to private users data without training, to handle credit attribution, and to allow efficient machine unlearning at scale. However, RAG techniques for image generation may lead to parts of the retrieved samples being copied in the model's output. To reduce risk

Quentin Jacquet, Nataliia Mozhzhukhina, Peter N. O. Gillespie, Gilles Wittmann

The intimate correlation between the local atomic arrangement and electronic states in Li-ion battery cathode materials plays a crucial role in determining their electrochemical properties, including capacity, cycling stability, and rate capability. Despite almost 30 years of research efforts on high performance cathodes based on Ni rich layered oxides, ther

Lars Beckers, Stefan Gerlach, Ole Lübke, Alexander Schlaefer

In robotic radiation therapy, high-energy photon beams from different directions are directed at a target within the patient. Target motion can be tracked by robotic ultrasound and then compensated by synchronous beam motion. However, moving the beams may result in beams passing through the ultrasound transducer or the robot carrying it. While this can be av

Bjarne Johansson, Bahman Pourvatan, Zahra Moezkarimi, Alessandro Papadopoulos

A potential problem that may arise in the domain of distributed control systems is the existence of more than one primary controller in redundancy plans that may lead to inconsistency. An algorithm called NRP FD is proposed to solve this issue by prioritizing consistency over availability. In this paper, we demonstrate how by using modeling and formal verifi

Parth Bora, Pham Duc Minh, Tim A. C. Willemse

The consensus problem is a fundamental problem in distributed systems. It involves a set of actors, or entities, that need to agree on some values or decisions. The Raft algorithm is a solution to the consensus problem that has gained widespread popularity as an easy-to-understand and implement alternative to Lamport's Paxos algorithm. In this paper we discu

Edward Fish, Andrew Gilbert

Few-shot temporal action localization (TAL) methods that adapt large models via single-prompt tuning often fail to produce precise temporal boundaries. This stems from the model learning a non-discriminative mean representation of an action from sparse data, which compromises generalization. We address this by proposing a new paradigm based on multi-prompt e

François Rondeau

We build a covariant holographic entanglement entropy prescription for a class of closed FRW cosmologies, generalizing a recent holographic proposal in de Sitter space. Starting from the Bousso covariant entropy bound, we describe the location of two holographic screens associated with a pair of antipodal observers, and then state our holographic proposal. W

Luigi Piccinelli, Yung-Hsu Yang, Christos Sakaridis, Mattia Segu

Accurate monocular metric depth estimation (MMDE) is crucial to solving downstream tasks in 3D perception and modeling. However, the remarkable accuracy of recent MMDE methods is confined to their training domains. These methods fail to generalize to unseen domains even in the presence of moderate domain gaps, which hinders their practical applicability. We

A. Agnello, N. C. Amorisco, A. Keats, G. K. Holt

The optimisation of scenarios and design of real-time-control in tokamaks, especially for machines still in design phase, requires a comprehensive exploration of solutions to the Grad-Shafranov (GS) equation over a high-dimensional space of plasma and coil parameters. Emulators can bypass the numerical issues in the GS equation, if a large enough library of

Davide Lazzati, Rosalba Perna, Taeho Ryu, Katelyn Breivik

At least three members of the recently identified class of fast luminous blue optical transient show evidence of late-time electromagnetic activity in great excess of what predicted by an extrapolation of the early time emission. In particular, AT2022tsd displays fast, bright optical fluctuations approximately a month after the initial detection. Here, we pr

Hamidreza Kamkari, Brendan Leigh Ross, Jesse C. Cresswell, Anthony L. Caterini

Likelihood-based deep generative models (DGMs) commonly exhibit a puzzling behaviour: when trained on a relatively complex dataset, they assign higher likelihood values to out-of-distribution (OOD) data from simpler sources. Adding to the mystery, OOD samples are never generated by these DGMs despite having higher likelihoods. This two-pronged paradox has ye

Mizuki Nishiwaki

Volcanic eruptions are driven by decompression-induced vesiculation of supersaturated volatile components in magma. The initial phase of this phenomenon has long been described as nucleation and growth. Recently, it was proposed that spinodal decomposition (an energetically spontaneous phase separation that does not require the formation of a distinct interf

Yasuyuki Ihara

Multiple object tracking (MOT), a key task in image recognition, presents a persistent challenge in balancing processing speed and tracking accuracy. This study introduces a novel approach that leverages quantum annealing (QA) to expedite computation speed, while enhancing tracking accuracy through the ensembling of object tracking processes. A method to imp

Brenden Bowen, Nishant Agarwal, Archana Kamal

A quantum system that interacts with an environment generally undergoes nonunitary evolution described by a non-Markovian or Markovian master equation. In this paper, we construct the non-Markovian Redfield master equation for a quantum scalar field that interacts with a second field through a bilinear or nonlinear interaction on a Minkowski background. We u

Peter Prelovšek, Sourav Nandy, Marcin Mierzejewski

We investigate chains of interacting spinless fermions subject to a finite external field $F$ (also called Stark chains) and focus on the regime where the charge thermalization follows the subdiffusive hydrodynamics. First, we study reduced models conserving the dipole moment and derive an explicit Einstein relation which links the subdiffusive transport coe

M. Tanious, R. Le Gal, R. Neri, A. Faure

Over the past few years, chemical studies have revealed multiple structures in the vicinity of young stellar objects (YSOs). It has become evident that specific physical conditions are associated with the emission of particular molecular lines, allowing us to use molecular probes of the YSO physics. Consequently, chemical surveys are now necessary to fully c

M. A. Keskiner, Pouyan Ghaemi, M. Ö. Oktel, Onur Erten

Motivated by the recent experimental developments in van der Waals heterostructures, we investigate the emergent magnetism in Mott insulator - semimetal moir\'e superlattices by deriving effective spin models and exploring their phase diagram by Monte Carlo simulations. Our analysis indicates that the stacking-dependent interlayer Kondo interaction can give

Christopher Lam, Sarah Ballard

The sample of host stars with multiple transiting planets has illuminated the orbital architectures of exoplanetary systems. These architectures may be shaped mostly by formation conditions, be continually sculpted by ongoing dynamical processes, or both. As more studies place planet occurrence within a galactic context, evidence has emerged for variable pla

Massimo Pascale, Brenda L. Frye, Justin D. R. Pierel, Wenlei Chen

The first James Webb Space Telescope ({\it JWST}) Near InfraRed Camera (NIRCam) imaging in the field of the galaxy cluster PLCK G165.7+67.0 ($z=0.35$) uncovered a Type Ia supernova (SN Ia) at $z=1.78$, called ``SN H0pe." Three different images of this one SN were detected as a result of strong gravitational lensing, each one traversing a different path in sp

Anqi Gong, Sebastian Cammerer, Joseph M. Renes

We introduce a sliding window decoder based on belief propagation (BP) with guided decimation for the purposes of decoding quantum low-density parity-check codes in the presence of circuit-level noise. Windowed decoding keeps the decoding complexity reasonable when, as is typically the case, repeated rounds of syndrome extraction are required to decode. With

Vadym Kliuchnikov, Eddie Schoute

Non-Clifford gates are frequently exclusively implemented on fault-tolerant architectures by first distilling magic states in specialised magic-state factories. In the rest of the architecture, the computational space, magic states can then be consumed by a stabilizer circuit to implement non-Clifford operations. We show that the connectivity between the com

David R. M. Arvidsson-Shukur, William F. Braasch, Stephan De Bievre, Justin Dressel

Recent years have seen the Kirkwood-Dirac (KD) distribution come to the forefront as a powerful quasi-probability distribution for analysing quantum mechanics. The KD distribution allows tools from statistics and probability theory to be applied to problems in quantum-information processing. A notable difference to the Wigner function is that the KD distribu

Silas R. Beane, Domenico Orlando, Susanne Reffert

The large-charge master field which generates all n-point correlation functions with an insertion of large charge Q in non-relativistic conformal field theory is obtained. This field is used to compute Schr\"odinger-invariant n-point correlation functions of large-charge operators via a direct evaluation of the path integral. Conformal dimensions are found t

Chi Sun, Kristian Mæland, Even Thingstad, Asle Sudbø

We use strong-coupling Eliashberg theory to study the competition of separate superconducting orders at low temperatures. Specifically, we study magnon-mediated superconductivity in a trilayer heterostructure with a thin normal metal between two antiferromagnetic insulators. Spin-triplet $p$-wave, spin-triplet $f$-wave, and spin-singlet $d$-wave superconduct

Walker Melton, Atul Sharma, Andrew Strominger, Tianli Wang

It is shown that a 2D CFT consisting of a central charge $c$ Liouville theory, a chiral level one, rank $N$ Kac-Moody algebra and a weight $-3/2$ free fermion holographically generate 4D MHV tree-level scattering amplitudes. The correlators of this 2D CFT give directly the 4D leaf amplitudes associated to a single hyperbolic slice of flat space. The 4D celes

Dominic Agius, Rouven Essig, Daniele Gaggero, Francesca Scarcella

If present in the early universe, primordial black holes (PBHs) will accrete matter and emit high-energy photons, altering the statistical properties of the {Cosmic Microwave Background (CMB)}. This mechanism has been used to constrain the fraction of dark matter that is in the form of PBHs to be much smaller than unity for PBH masses well above one solar ma

Connor Cheverall, Nikku Madhusudhan

In recent years, high-resolution transmission spectroscopy in the near-infrared has led to detections of prominent molecules in several giant exoplanets on close-in orbits. This approach has traditionally relied on the large Doppler shifts of the planetary spectral lines induced by the high velocities of the close-in planets, which were considered necessary

Himanish Ganjoo, M. Sten Delos

In cosmologies with hidden sector dark matter, the lightest hidden sector species can come to dominate the energy budget of the universe and cause an early matter-dominated era (EMDE). EMDEs amplify the matter power spectrum on small scales, leading to dense, early-forming microhalos which massively boost the dark matter annihilation signal. We use the Fermi

Bjoern Hassfeld, Arthur Hebecker

One of the leading ideas for the beginning of the Universe is the Hartle-Hawking `No-Boundary Proposal.' Since the Cobordism Conjecture claims that any spacetime allows for a dynamical boundary, we suggest that one may equally well consider a `Boundary Proposal'. Specifically, the corresponding euclidean instanton is a sphere with two holes around north and

Samuel H. C. Cabot, Nikku Madhusudhan, Savvas Constantinou, Diana Valencia

The study of temperate sub-Neptunes is the new frontier in exoplanetary science. A major development in the past year has been the first detection of carbon-bearing molecules in the atmosphere of a temperate sub-Neptune, K2-18 b, a possible Hycean world, with the James Webb Space Telescope (JWST). The JWST is poised to characterise the atmospheres of several

Jason Youm, Joseph T. Iosue, Adam Ehrenberg, Yu-Xin Wang

Recently, many experiments have been conducted with the goal of demonstrating a quantum advantage over classical computation. One popular framework for these experiments is Gaussian Boson Sampling, where quadratic photonic input states are interfered via a linear optical unitary and subsequently measured in the Fock basis. In this work, we study the modal en

Martin Hoferichter

Pion $\beta$ decay, $\pi^+ \to\pi^0 e^+ \nu_e$, offers a pristine way to measure the CKM matrix element $V_{ud}$ in a purely mesonic system, with excellent control over the hadronic matrix elements. We review the physics goals and current status of the PIONEER experiment, which aims at major improvements in the branching fractions for the $\pi^+\to e^+ \nu_e

Valentina La Torre, Anna Sajina, Andy D. Goulding, Danilo Marchesini

The current and upcoming large data volume galaxy surveys require the use of machine learning techniques to maximize their scientific return. This study explores the use of Self-Organizing Maps (SOMs) to estimate galaxy parameters with a focus on handling cases of missing data and providing realistic probability distribution functions for the parameters. We

Ryohei Kobayashi, Yuxuan Zhang, Yan-Qi Wang, Maissam Barkeshli

It is common in condensed matter systems for reflection ($R$) and time-reversal ($T$) symmetry to both be broken while the combination $RT$ is preserved. In this paper we study invariants that arise due to $RT$ symmetry. We consider many-body systems of interacting fermions with fermionic symmetry groups $G_f = \mathbb{Z}_2^f \times \mathbb{Z}_2^{RT}$, $U(1)

Ziyang Chen, Israel D. Gebru, Christian Richardt, Anurag Kumar

We present a new dataset called Real Acoustic Fields (RAF) that captures real acoustic room data from multiple modalities. The dataset includes high-quality and densely captured room impulse response data paired with multi-view images, and precise 6DoF pose tracking data for sound emitters and listeners in the rooms. We used this dataset to evaluate existing

Guoxing Sun, Rishabh Dabral, Pascal Fua, Christian Theobalt

Faithful human performance capture and free-view rendering from sparse RGB observations is a long-standing problem in Vision and Graphics. The main challenges are the lack of observations and the inherent ambiguities of the setting, e.g. occlusions and depth ambiguity. As a result, radiance fields, which have shown great promise in capturing high-frequency a

Shweta Singh, Aayan Yadav, Jitesh Jain, Humphrey Shi

The Common Objects in Context (COCO) dataset has been instrumental in benchmarking object detectors over the past decade. Like every dataset, COCO contains subtle errors and imperfections stemming from its annotation procedure. With the advent of high-performing models, we ask whether these errors of COCO are hindering its utility in reliably benchmarking fu

Daniel Winter, Matan Cohen, Shlomi Fruchter, Yael Pritch

Diffusion models have revolutionized image editing but often generate images that violate physical laws, particularly the effects of objects on the scene, e.g., occlusions, shadows, and reflections. By analyzing the limitations of self-supervised approaches, we propose a practical solution centered on a \q{counterfactual} dataset. Our method involves capturi

Archisman Panigrahi, Leonid Levitov

Recently, a wide family of electronic orders was unveiled in graphene flat bands, such as spin- and valley-polarized phases as well as nematic momentum-polarized phases, stabilized by exchange interactions via a generalized Stoner mechanism. Momentum polarization involves orbital degrees of freedom and is therefore expected to impact resistivity in a way tha

Nikolaos Sarafianos, Tuur Stuyck, Xiaoyu Xiang, Yilei Li

We introduce Garment3DGen a new method to synthesize 3D garment assets from a base mesh given a single input image as guidance. Our proposed approach allows users to generate 3D textured clothes based on both real and synthetic images, such as those generated by text prompts. The generated assets can be directly draped and simulated on human bodies. We lever

Huiyi Wang, Haodong Lu, Lina Yao, Dong Gong

Continual learning (CL) aims to continually accumulate knowledge from a non-stationary data stream without catastrophic forgetting of learned knowledge, requiring a balance between stability and adaptability. Relying on the generalizable representation in pre-trained models (PTMs), PTM-based CL methods perform effective continual adaptation on downstream tas

J. J. Sánchez-Gabites

In Conley index theory one may study an invariant set $S$ by decomposing it into an attractor $A$, a repeller $R$, and the orbits connecting the two. The Conley indices of $S$, $A$ and $R$ fit into an exact sequence where a certain connection homomorphism $\Gamma$ plays an important role. In this paper we provide a dynamical interpretation of this map. Rough

Yanwei Li, Yuechen Zhang, Chengyao Wang, Zhisheng Zhong

In this work, we introduce Mini-Gemini, a simple and effective framework enhancing multi-modality Vision Language Models (VLMs). Despite the advancements in VLMs facilitating basic visual dialog and reasoning, a performance gap persists compared to advanced models like GPT-4 and Gemini. We try to narrow the gap by mining the potential of VLMs for better perf

Jingyi Mei, Tim Coopmans, Marcello Bonsangue, Alfons Laarman

Verifying equivalence between two quantum circuits is a hard problem, that is nonetheless crucial in compiling and optimizing quantum algorithms for real-world devices. This paper gives a Turing reduction of the (universal) quantum circuits equivalence problem to weighted model counting (WMC). Our starting point is a folklore theorem showing that equivalence

Tomasz Kociumaka, Jakob Nogler, Philip Wellnitz

The decades-old Pattern Matching with Edits problem, given a length-$n$ string $T$ (the text), a length-$m$ string $P$ (the pattern), and a positive integer $k$ (the threshold), asks to list all fragments of $T$ that are at edit distance at most $k$ from $P$. The one-way communication complexity of this problem is the minimum amount of space needed to encode

Li Siyao, Tianpei Gu, Zhitao Yang, Zhengyu Lin

We introduce a novel task within the field of 3D dance generation, termed dance accompaniment, which necessitates the generation of responsive movements from a dance partner, the "follower", synchronized with the lead dancer's movements and the underlying musical rhythm. Unlike existing solo or group dance generation tasks, a duet dance scenario entails a he

Frederik Köhne, Friedrich M. Philipp, Manuel Schaller, Anton Schiela

Extended dynamic mode decomposition (EDMD) is a well-established method to generate a data-driven approximation of the Koopman operator for analysis and prediction of nonlinear dynamical systems. Recently, kernel EDMD (kEDMD) has gained popularity due to its ability to resolve the challenging task of choosing a suitable dictionary by using the kernel's canon

Jari Desmet

We show that a primitive axial algebra of Jordan type $\eta = \tfrac{1}{2}$ is a Jordan algebra if and only if every $2$-generated subalgebra is \emph{solid}, a notion introduced recently by Ilya Gorshkov, Sergey Shpectorov and Alexei Staroletov. As a byproduct, we show that a subalgebra generated by axes $a,b$ is solid if and only if the associator $[L_a,L_

Suraj Patni, Aradhye Agarwal, Chetan Arora

In the absence of parallax cues, a learning-based single image depth estimation (SIDE) model relies heavily on shading and contextual cues in the image. While this simplicity is attractive, it is necessary to train such models on large and varied datasets, which are difficult to capture. It has been shown that using embeddings from pre-trained foundational m

J. J. Sánchez-Gabites

Consider a continuous flow in $\mathbb{R}^3$ or any orientable $3$-manifold. Let $(Q_1, Q_0)$ be an index pair in the sense of Conley and consider the region $N := \overline{Q_1 - Q_0}$. (An example of this is a compact $3$-manifold $N$ such that trajectories of the flow cross $\partial N$ inwards or outwards transversally, or bounce off it from the outside)

Mateusz Klimaszewski, Piotr Andruszkiewicz, Alexandra Birch

The rise of Modular Deep Learning showcases its potential in various Natural Language Processing applications. Parameter-efficient fine-tuning (PEFT) modularity has been shown to work for various use cases, from domain adaptation to multilingual setups. However, all this work covers the case where the modular components are trained and deployed within one si

Hillary Dawkins, Isar Nejadgholi, Daniel Gillis, Judi McCuaig

Mitigation of gender bias in NLP has a long history tied to debiasing static word embeddings. More recently, attention has shifted to debiasing pre-trained language models. We study to what extent the simplest projective debiasing methods, developed for word embeddings, can help when applied to BERT's internal representations. Projective methods are fast to

Jerry Wei, Chengrun Yang, Xinying Song, Yifeng Lu

Large language models (LLMs) often generate content that contains factual errors when responding to fact-seeking prompts on open-ended topics. To benchmark a model's long-form factuality in open domains, we first use GPT-4 to generate LongFact, a prompt set comprising thousands of questions spanning 38 topics. We then propose that LLM agents can be used as a

Bijan Bagchi, Aritra Ghosh, Miloslav Znojil

Time and again, non-conventional forms of Lagrangians with non-quadratic velocity dependence have found attention in the literature. For one thing, such Lagrangians have deep connections with several aspects of nonlinear dynamics including specifically the types of the Li\'{e}nard class; for another, very often the problem of their quantization opens up mult

Jack West, Lea Thiemt, Shimaa Ahmed, Maggie Bartig

Mobile apps have embraced user privacy by moving their data processing to the user's smartphone. Advanced machine learning (ML) models, such as vision models, can now locally analyze user images to extract insights that drive several functionalities. Capitalizing on this new processing model of locally analyzing user images, we analyze two popular social med

M. A. Reyes, C. Dalfó, M. A. Fiol

The $k$-token graph $F_k(G)$ of a graph $G$ is the graph whose vertices are the $k$-subsets of vertices from $G$, two of which being adjacent whenever their symmetric difference is a pair of adjacent vertices in $G$. In this article, we describe some properties of the Laplacian matrix $\L_k$ of $F_k(G)$ and the Laplacian matrix $\overline{\L}_k$ of the $k$-t

Fabrice Baudoin, Maria Gordina, Rohan Sarkar

We study stability under tensorization and projection-type operations of gradient-type estimates and other functional inequalities for Markov semigroups on metric spaces. Using transportation-type inequalities obtained by F. Baudoin and N. Eldredge in 2021, we prove that constants in the gradient estimates can be chosen to be independent of the dimension. Ou

Dietmar Ferger

Let E be a locally compact second countable Hausdorff space and F the pertaining family of all closed sets. We endow F respectively with the Fell-topology, the upper Fell topology or the upper Vietoris-topology and investigate weak convergence of probability measures on the corresponding hyperspaces with a focus on the upper Fell topology. The results can be

Zeyu Yan, Jiasheng Li, Zining Zhang, Huaishu Peng

The iterative prototyping process for printed circuit boards (PCBs) frequently employs surface-mounted device (SMD) components, which are often discarded rather than reused due to the challenges associated with desoldering, leading to unnecessary electronic waste. This paper introduces SolderlessPCB, a collection of techniques for solder-free PCB prototyping

Jingtao Zhan, Qingyao Ai, Yiqun Liu, Jia Chen

Text-to-image generation systems have emerged as revolutionary tools in the realm of artistic creation, offering unprecedented ease in transforming textual prompts into visual art. However, the efficacy of these systems is intricately linked to the quality of user-provided prompts, which often poses a challenge to users unfamiliar with prompt crafting. This

Qiuhong Shen, Zike Wu, Xuanyu Yi, Pan Zhou

We tackle the challenge of efficiently reconstructing a 3D asset from a single image at millisecond speed. Existing methods for single-image 3D reconstruction are primarily based on Score Distillation Sampling (SDS) with Neural 3D representations. Despite promising results, these approaches encounter practical limitations due to lengthy optimizations and sig

Eric R. Heller, David T. Limmer

Equilibrium rate theories play a crucial role in understanding rare, reactive events. However, they are inapplicable to a range of irreversible processes in systems driven far from thermodynamic equilibrium like active and biological matter. Here, we develop an efficient numerical method to compute the rate constant of rare nonequilibrium events in the weak-

David Layden, Bradley Mitchell, Karthik Siva

Quantum error mitigation techniques mimic noiseless quantum circuits by running several related noisy circuits and combining their outputs in particular ways. How well such techniques work is thought to depend strongly on how noisy the underlying gates are. Weakly-entangling gates, like $R_{ZZ}(\theta)$ for small angles $\theta$, can be much less noisy than

Alina Bendt, Sandra C. Chapman, Thierry Dudok de Wit

The Solar Orbiter (SO) mission provides the opportunity to study the evolution of solar wind turbulence. We use SO observations of nine extended intervals of homogeneous turbulence to determine when turbulent magnetic field fluctuations may be characterized as: (i) wave-packets and (ii) coherent structures (CS). We perform the first systematic scale-by-scale

Tianfu Wang, Guosheng Hu, Hongguang Wang

Estimating the pose of objects from images is a crucial task of 3D scene understanding, and recent approaches have shown promising results on very large benchmarks. However, these methods experience a significant performance drop when dealing with unseen objects. We believe that it results from the limited generalizability of image features. To address this

Qiongyuan Wu, Diana A. Chisholm, Rafael Muffato, Tiberius Georgescu

Squeezing is a crucial resource for quantum information processing and quantum sensing. In levitated nanomechanics, squeezed states of motion can be generated via temporal control of the trapping frequency of a massive particle. However, the amount of achievable squeezing typically suffers from detrimental environmental effects. We analyze the performance of

En-Hung Chao

In this contribution, we present recent progress from the RBC/UKQCD collaboration on the first calculation of the long-distance two-photon contribution to the decay amplitude of a long-lived kaon into a pair of charged muons.

Z. Brown, R. Demina, A. G. Adame, S. Avila

Surveys of cosmological large-scale structure (LSS) are sensitive to the presence of local primordial non-Gaussianity (PNG), and may be used to constrain models of inflation. Local PNG, characterized by fNL, the amplitude of the quadratic correction to the potential of a Gaussian random field, is traditionally measured from LSS two-point and three-point clus

João Romeiras Amado, Francisco Pereira, David Pissarra, Salvatore Signorello

Malicious traffic detectors leveraging machine learning (ML), namely those incorporating deep learning techniques, exhibit impressive detection capabilities across multiple attacks. However, their effectiveness becomes compromised when deployed in networks handling Terabit-speed traffic. In practice, these systems require substantial traffic sampling to reco

Christopher Chalhoub, Alexander Drewitz, Alexis Prévost, Pierre-François Rodriguez

We consider a class of percolation models where the local occupation variables have long-range correlations decaying as a power law $\sim r^{-a}$ at large distances $r$, for some $0< a< d$ where $d$ is the underlying spatial dimension. For several of these models, we present both, rigorous analytical results and matching simulations that determine the critic

H. Read, S. Benaglia, L. Fumagalli

Understanding the adsorption and physical characteristics of supported lipid membranes is crucial for their effective use as model cell membranes. Their morphological and thermodynamic properties at the nanoscale have traditionally been studied on hydrophilic substrates, such as mica and silicon oxide, which have proved to facilitate the reconstruction of bi

Huanchen Hu, Paulo C. C. Freire

Neutron stars (NSs) are compact objects that host the densest forms of matter in the observable universe, providing unique opportunities to study the behaviour of matter at extreme densities. While precision measurements of NS masses through pulsar timing have imposed effective constraints on the equation of state (EoS) of dense matter, accurately determinin

Jiahao Luo, Jing Liu, James Davis

We present SplatFace, a novel Gaussian splatting framework designed for 3D human face reconstruction without reliance on accurate pre-determined geometry. Our method is designed to simultaneously deliver both high-quality novel view rendering and accurate 3D mesh reconstructions. We incorporate a generic 3D Morphable Model (3DMM) to provide a surface geometr

Rricha Jalota, Lyan Verwimp, Markus Nussbaum-Thom, Amr Mousa

Neural Network Language Models (NNLMs) for Virtual Assistants (VAs) are generally language-, region-, and in some cases, device-dependent, which increases the effort to scale and maintain them. Combining NNLMs for one or more of the categories is one way to improve scalability. In this work, we combine regional variants of English to build a ``World English'

Jay Bartroff, Alexander G. Tartakovsky

Gary Lorden provided several fundamental and novel insights into sequential hypothesis testing and changepoint detection. In this article, we provide an overview of Lorden's contributions in the context of existing results in those areas, and some extensions made possible by Lorden's work. We also mention some of Lorden's significant consulting work, includi

Ruoxu Cen, Jason Li, Debmalya Panigrahi

The hypergraph unreliability problem asks for the probability that a hypergraph gets disconnected when every hyperedge fails independently with a given probability. For graphs, the unreliability problem has been studied over many decades, and multiple fully polynomial-time approximation schemes are known starting with the work of Karger (STOC 1995). In contr

P. Montealegre Macías, J. J. Sánchez-Gabites

A toroidal set is a compactum $K \subseteq \mathbb{R}^3$ which has a neighbourhood basis of solid tori. We study the topological entropy of toroidal attractors $K$, bounding it from below in terms of purely topological properties of $K$. In particular, we show that for a toroidal set $K$, either any smooth attracting dynamics on $K$ has an entropy at least $

Jakub K. Sowa, Danielle M. Cadena, Arshad Mehmood, Benjamin G. Levine

Surfaces of colloidal nanocrystals are frequently passivated with carboxylate ligands which exert significant effects on their optoelectronic properties and chemical stability. Experimentally, binding geometries of such ligands are typically investigated using vibrational spectroscopy, but the interpretation of the IR signal is usually not trivial. Here, usi

Ehsan Latif

Much worldly semantic knowledge can be encoded in large language models (LLMs). Such information could be of great use to robots that want to carry out high-level, temporally extended commands stated in natural language. However, the lack of real-world experience that language models have is a key limitation that makes it challenging to use them for decision

Eric Blais, Cameron Seth

The graph and hypergraph container methods are powerful tools with a wide range of applications across combinatorics. Recently, Blais and Seth (FOCS 2023) showed that the graph container method is particularly well-suited for the analysis of the natural canonical tester for two fundamental graph properties: having a large independent set and $k$-colorability

Yiyao Zhang, Ke Chen, Shang-Hua Yang

Data acquisition, image processing, and image quality are the long-lasting issues for terahertz (THz) 3D reconstructed imaging. Existing methods are primarily designed for 2D scenarios, given the challenges associated with obtaining super-resolution (SR) data and the absence of an efficient SR 3D reconstruction framework in conventional computed tomography (

Chenshuang Zhang, Fei Pan, Junmo Kim, In So Kweon

We establish rigorous benchmarks for visual perception robustness. Synthetic images such as ImageNet-C, ImageNet-9, and Stylized ImageNet provide specific type of evaluation over synthetic corruptions, backgrounds, and textures, yet those robustness benchmarks are restricted in specified variations and have low synthetic quality. In this work, we introduce g