February 2024 arXiv papers — page 28

Ye Wang, Xinrun Xu, Zhiming Ding

When completing knowledge-intensive tasks, humans sometimes need an answer and a corresponding reference passage for auxiliary reading. Previous methods required obtaining pre-segmented article chunks through additional retrieval models. This paper explores leveraging the parameterized knowledge stored during the pre-training phase of large language models (

Damir Kinzebulatov

For finite interacting particle systems with strong repulsing-attracting or general interactions, we prove global weak well-posedness almost up to the critical threshold of the strengths of attracting interactions (independent of the number of particles), and establish other regularity results, such as a heat kernel bound in the regions where strongly attrac

John Salvador, Naman Bansal, Mousumi Akter, Souvika Sarkar

Semantic Overlap Summarization (SOS) is a constrained multi-document summarization task, where the constraint is to capture the common/overlapping information between two alternative narratives. In this work, we perform a benchmarking study of popular Large Language Models (LLMs) exclusively on the SOS task. Additionally, we introduce the PrivacyPolicyPairs

Karol Horodecki, Leonard Sikorski, Siddhartha Das, Mark M. Wilde

In this paper, we develop the resource theory of quantum secret key. Operating under the assumption that entangled states with zero distillable key do not exist, we define the key cost of a quantum state, and device. We study its properties through the lens of a quantity that we call the key of formation. The main result of our paper is that the regularized

Jan Röder, Eduardo Ros, Frank Schinzel, Andrei Lobanov

The flat-spectrum radio quasar 3C 345 has been showing gamma-ray activity since the mid-2000s along with activity across the electromagnetic spectrum. A gamma-ray burst in 2009 was successfully linked to relativistic outflow in 43 GHz VLBI observations and has since been analyzed also using single dish measurements. A multi-wavelength follow-up VLBI observat

Lily Major, Dave Davies, Amanda Clare, Jacqueline W. Daykin

The Burrows-Wheeler Transform (BWT) is an efficient invertible text transformation algorithm with the properties of tending to group identical characters together in a run, and enabling search of the text. This transformation has extensive uses particularly in lossless compression algorithms, indexing, and within bioinformatics for sequence alignment tasks.

Deidre A. Hunter, Bruce G. Elmegreen, Suzanne C. Madden

Dwarf irregulars (dIrrs) are among the most common type of galaxy in the Universe. They typically have gas-rich, low surface-brightness, metal-poor, and relatively-thick disks. Here we summarize the current state of our knowledge of the interstellar medium (ISM), including atomic, molecular and ionized gas, along with their dust properties and metals. We als

Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty

Online reinforcement learning (RL) algorithms offer great potential for personalizing treatment for participants in clinical trials. However, deploying an online, autonomous algorithm in the high-stakes healthcare setting makes quality control and data quality especially difficult to achieve. This paper proposes algorithm fidelity as a critical requirement f

Dongsung Huh

We investigate a principled approach for symbolic operation completion (SOC), a minimal task for studying symbolic reasoning. While conceptually similar to matrix completion, SOC poses a unique challenge in modeling abstract relationships between discrete symbols. We demonstrate that SOC can be efficiently solved by a minimal model - a bilinear map - with a

Z. M. McIntyre, W. A. Coish

Long range, multi-qubit parity checks have applications in both quantum error correction and measurement-based entanglement generation. Such parity checks could be performed using qubit-state-dependent phase shifts on propagating pulses of light described by coherent states $\vert\alpha\rangle$ of the electromagnetic field. We consider "flying-cat" parity ch

Tomáš Masopust, Petr Osička

Opacity is a general framework modeling security properties of systems interacting with a passive attacker. Initial-and-final-state opacity (IFO) generalizes the classical notions of opacity, such as current-state opacity and initial-state opacity. In IFO, the secret is whether the system evolved from a given initial state to a given final state or not. Ther

Rahul Shastri, Chao Jiang, Guo-Hua Xu, B. Prasanna Venkatesh

We propose and analyze a universal method to obtain fast charging of a quantum battery by a driven charger system using controlled, pure dephasing of the charger. While the battery displays coherent underdamped oscillations of energy for weak charger dephasing, the quantum Zeno freezing of the charger energy at high dephasing suppresses the rate of transfer

Jerry Ngo, Yoon Kim

This work explores whether language models encode meaningfully grounded representations of sounds of objects. We learn a linear probe that retrieves the correct text representation of an object given a snippet of audio related to that object, where the sound representation is given by a pretrained audio model. This probe is trained via a contrastive loss tha

Xiaowen Li

This thesis gives an overview of the state-of-the-art randomized linear algebra algorithms for singular value decomposition (SVD), including the presentation of existing pseudo-codes and theoretical error analysis. Our main focus is on presenting numerical experiments illustrating image restoration using various randomized singular value decomposition (RSVD)

C. Cascante, J. Fábrega, D. Pascuas, J. A. Peláez

In a recent paper of the authors together with A. Aleman, it is shown that the Bloch space $\mathcal{B}$ in the unit disc has the following radicality property: if an analytic function $g$ satisfies that $g^n\in \mathcal{B}$, then $g^m\in \mathcal{B}$, for all $m\le n$. Since $\mathcal{B}$ coincides with the space $\mathcal{T}(A^p_\alpha)$ of analytic symbol

Muhammad Suffian, Jose M. Alonso-Moral, Alessandro Bogliolo

Machine learning models are widely used in real-world applications. However, their complexity makes it often challenging to interpret the rationale behind their decisions. Counterfactual explanations (CEs) have emerged as a viable solution for generating comprehensible explanations in eXplainable Artificial Intelligence (XAI). CE provides actionable informat

Milán András Fodor, Tamás Gábor Csapó, Frigyes Viktor Arthur

The aim of the study is to investigate the complex mechanisms of speech perception and ultimately decode the electrical changes in the brain accruing while listening to speech. We attempt to decode heard speech from intracranial electroencephalographic (iEEG) data using deep learning methods. The goal is to aid the advancement of brain-computer interface (BC

Alexander B. Boyd, James P. Crutchfield, Mile Gu, Felix C. Binder

Efficiently harvesting thermodynamic resources requires a precise understanding of their structure. This becomes explicit through the lens of information engines -- thermodynamic engines that use information as fuel. Maximizing the work harvested using available information is a form of physically-instantiated machine learning that drives information engines

Dmitry Petrov, Pradyumn Goyal, Vikas Thamizharasan, Vladimir G. Kim

We introduce GEM3D -- a new deep, topology-aware generative model of 3D shapes. The key ingredient of our method is a neural skeleton-based representation encoding information on both shape topology and geometry. Through a denoising diffusion probabilistic model, our method first generates skeleton-based representations following the Medial Axis Transform (M

Han Wang, Zhe Fu, Jonathan Lee, Hossein Nick Zinat Matin

This paper introduces a novel control framework for Lagrangian variable speed limits in hybrid traffic flow environments utilizing automated vehicles (AVs). The framework was validated using a fleet of 100 connected automated vehicles as part of the largest coordinated open-road test designed to smooth traffic flow. The framework includes two main components

Grégoire Ferré

We study large deviations for the time average of the Ornstein-Uhlenbeck process raised to an arbitrary power. We prove that beyond a critical value, large deviations are subexponential in time, with a non-convex rate function whose main coefficient is given by the solution to a Hamilton-Jacobi problem. Although a similar problem was addressed in a recent wo

Antonio Sclocchi, Alessandro Favero, Matthieu Wyart

Understanding the structure of real data is paramount in advancing modern deep-learning methodologies. Natural data such as images are believed to be composed of features organized in a hierarchical and combinatorial manner, which neural networks capture during learning. Recent advancements show that diffusion models can generate high-quality images, hinting

Ali Aghdaei, Zhuo Feng

This work presents inGRASS, a novel algorithm designed for incremental spectral sparsification of large undirected graphs. The proposed inGRASS algorithm is highly scalable and parallel-friendly, having a nearly-linear time complexity for the setup phase and the ability to update the spectral sparsifier in $O(\log N)$ time for each incremental change made to

Evgeny A. Kuznetsov, Evgeny A. Mikhailov

As well known, magnetic fields in space are distributed very inhomogeneously. Some-times field distributions have forms of filaments with high magnetic field values. As many ob-servations show, such a filamentation takes place in convective cells in the Sun and other astro-physical objects. This effect is associated with the frozenness of the magnetic field

Deepayan Banik, Kristen Menou

Time-dependent meridional circulation and differential rotation in radiative zones are central open issues in stellar evolution theory. We streamline this challenging problem using the downward control principle of atmospheric science, under a geostrophic f-plane approximation. We recover the known stellar physics result that the steady-state meridional circ

H. Sana, F. Tramper, M. Abdul-Masih, R. Blomme

Using the medium resolution spectrograph X-shooter, spectra of 235 OB and Wolf-Rayet (WR) stars in sub-solar metallicity environments have been secured. [...]This second paper focuses on the optical observations of 232 Magellanic Clouds targets. It describes the uniform reduction of the UVB (300 - 560 nm) and VIS (550 - 1020 nm) XShootU data as well as the p

Ankan Mullick, Ayan Kumar Bhowmick, Raghav R, Ravi Kokku

Dialog summarization has become increasingly important in managing and comprehending large-scale conversations across various domains. This task presents unique challenges in capturing the key points, context, and nuances of multi-turn long conversations for summarization. It is worth noting that the summarization techniques may vary based on specific requir

Luke Marris, Ian Gemp, Siqi Liu, Joel Z. Leibo

Normal-form games with two players, each with two strategies, are the most studied class of games. These so-called 2x2 games are used to model a variety of strategic interactions. They appear in game theory, economics, and artificial intelligence research. However, there lacks tools for describing and visualizing such games. This work introduces a LaTeX pack

Ayush Basu, Griffin Johnston, Vojtěch Rödl, Marcelo Sales

In their classical paper, Erd\H{o}s, Goodman and P\'{o}sa studied the representation of a graph with vertex set $[n]$ by a family of subsets $S_1,\dots, S_n$ with the property that $\{i,j\}$ is an edge if and only if $S_i\cap S_j\neq \emptyset$. In this note, we consider a similar representation of bounded degree $r$-uniform hypergraphs and establish some bo

Lebing Chen, Xiaokun Teng, Ding Hu, Feng Ye

We use elastic and inelastic neutron scattering (INS) to study the antiferromagnetic (AF) phase transitions and spin excitations in the two-dimensional (2D) zig-zag antiferromagnet FePSe$_3$. By determining the magnetic order parameter across the AF phase transition, we conclude that the AF phase transition in FePSe$_3$ is first-order in nature. In addition,

Lisa Oakley, Steven Holtzen, Alina Oprea

Programmatically generating tight differential privacy (DP) bounds is a hard problem. Two core challenges are (1) finding expressive, compact, and efficient encodings of the distributions of DP algorithms, and (2) state space explosion stemming from the multiple quantifiers and relational properties of the DP definition. We address the first challenge by dev

Baptiste Genest, Nicolas Courty, David Coeurjolly

In machine learning and computer graphics, a fundamental task is the approximation of a probability density function through a well-dispersed collection of samples. Providing a formal metric for measuring the distance between probability measures on general spaces, Optimal Transport (OT) emerges as a pivotal theoretical framework within this context. However

Yong Qi, Fanghan Zhao

Buddha statues, as a symbol of many religions, have significant cultural implications that are crucial for understanding the culture and history of different regions, and the recognition of Buddha statues is therefore the pivotal link in the field of Buddha study. However, the Buddha statue recognition requires extensive time and effort from knowledgeable pr

Juan Felipe Gomez, Caio Vieira Machado, Lucas Monteiro Paes, Flavio P. Calmon

Machine learning (ML) is widely used to moderate online content. Despite its scalability relative to human moderation, the use of ML introduces unique challenges to content moderation. One such challenge is predictive multiplicity: multiple competing models for content classification may perform equally well on average, yet assign conflicting predictions to

Xiang Chen, Faqiang Wang, Jun Liu, Li Cui

The Unbalanced Optimal Transport (UOT) problem plays increasingly important roles in computational biology, computational imaging and deep learning. Scaling algorithm is widely used to solve UOT due to its convenience and good convergence properties. However, this algorithm has lower accuracy for large regularization parameters, and due to stability issues,

Erva Nihan Kandemir, Jill-Jenn Vie, Adam Sanchez-Ayte, Olivier Palombi

Accurate estimation of question difficulty and prediction of student performance play key roles in optimizing educational instruction and enhancing learning outcomes within digital learning platforms. The Elo rating system is widely recognized for its proficiency in predicting student performance by estimating both question difficulty and student ability whi

Smita Ghaisas, Anmol Singhal

Across the dynamic business landscape today, enterprises face an ever-increasing range of challenges. These include the constantly evolving regulatory environment, the growing demand for personalization within software applications, and the heightened emphasis on governance. In response to these multifaceted demands, large enterprises have been adopting auto

Eleftheria Malami

In this presentation, we discuss recent key topics in theoretical analyses of CP violation in benchmarks decays of the $B$ meson. We provide the most updated values of the mixing phases and discuss the importance of including the penguin contributions in their studies. Exploring intriguing patterns in purely tree decays, interesting new methodologies can be

Polina Baron

In his paper "The Mumford Dynamical System and Hyperelliptic Kleinian Functions" (see arXiv:2402.09218), Victor Buchstaber developed the differential-algebraic theory of the Mumford dynamical system. The key object of this theory is the (P,Q)-recursion introduced in his paper. In the present paper, we further develop the theory of (P,Q)-recursion and describ

Rankeya Datta, Karl Schwede, Kevin Tucker

Let $S$ be a submonoid of a free Abelian group of finite rank. We show that if $k$ is a field of prime characteristic such that the monoid $k$-algebra $k[S]$ is split $F$-regular, then $k[S]$ is a finitely generated $k$-algebra, or equivalently, that $S$ is a finitely generated monoid. Split $F$-regular rings are possibly non-Noetherian or non-$F$-finite rin

Lingjun Zhao, Khanh Nguyen, Hal Daumé

Language models will inevitably err in situations with which they are unfamiliar. However, by effectively communicating uncertainties, they can still guide humans toward making sound decisions in those contexts. We demonstrate this idea by developing HEAR, a system that can successfully guide humans in simulated residential environments despite generating po

Tomer Ezra, Daniel Schoepflin, Ariel Shaulker

We consider the problem of designing auctions which maximize consumer surplus (i.e., the social welfare minus the payments charged to the buyers). In the consumer surplus maximization problem, a seller with a set of goods faces a set of strategic buyers with private values, each of whom aims to maximize their own individual utility. The seller, in contrast,

J. M. Joel Ong, Marc Teng Yen Hon, Melinda Soares-Furtado, Alexander P. Stephan

We report the discovery and characterisation of TIC 350842552 ("Zvrk"), an apparently isolated, rapidly-rotating ($P_\text{rot} \sim 99\ \mathrm{d}$) red giant observed by TESS in its Southern Continuous Viewing Zone. The star's fast surface rotation is independently verified by the use of p-mode asteroseismology, strong periodicity in TESS and ASAS-SN photo

Marco Castronovo, Mikhail Gorsky, José Simental, David E Speyer

Affine cluster varieties are covered up to codimension 2 by open algebraic tori. We put forth a general conjecture (based on earlier conversation between Vivek Shende and the last author) characterizing their deep locus, i.e. the complement of all cluster charts, as the locus of points with non-trivial stabilizer under the action of cluster automorphisms. We

Denis Agniel, Layla Parast

The development of statistical methods to evaluate surrogate markers is an active area of research. In many clinical settings, the surrogate marker is not simply a single measurement but is instead a longitudinal trajectory of measurements over time, e.g., fasting plasma glucose measured every 6 months for 3 years. In general, available methods developed for

Gabriel de Jesus Coelho da Silva, Carlos Becker Westphall

Large Language Models (LLMs) have quickly risen to prominence due to their ability to perform at or close to the state-of-the-art in a variety of fields while handling natural language. An important field of research is the application of such models at the cybersecurity context. This survey aims to identify where in the field of cybersecurity LLMs have alre

Nimish P. Hathi, Dean C. Hines, Yotam Cohen, Norman A. Grogin

Imaging spectropolarimetry is a new observing mode on the Advanced Camera for Surveys (ACS) aboard the Hubble Space Telescope (HST) that was commissioned in Cycle 30 and is available to HST observers starting in Cycle 31 (i.e., from 2023). It is a technique that is accessible from ground-based observatories, but the superb spatial resolution afforded by HST/

P. Baldini, G. Lanzuisi, M. Brusa, A. Merloni

Powerful outflows from active galactic nuclei (AGN) can significantly impact the gas reservoirs of their host galaxies. However, it is still unclear how these outflows can propagate from the very central regions of galaxies to their outskirts, and whether nuclear winds can be driven by and/or be responsible for drastic spectral transitions. In this work we t

Fangzhou Wu, Shutong Wu, Yulong Cao, Chaowei Xiao

With the fast development of large language models (LLMs), LLM-driven Web Agents (Web Agents for short) have obtained tons of attention due to their superior capability where LLMs serve as the core part of making decisions like the human brain equipped with multiple web tools to actively interact with external deployed websites. As uncountable Web Agents hav

Raffaele Salvia, Vittorio Giovannetti

We study the possibility of deterministic protocols for extracting work from quantum systems. Focusing on the two-point measurement work extraction scenario, we prove that, with enough copies of the system, such zero-fluctuation protocols always exist if the Hamiltonian has a rational spectrum. Leveraging this result, we show that for any Hamiltonian, it is

Gui-Jun Ding, Jose W. F. Valle

The Standard Model lacks an organizing principle to describe quark and lepton ``flavours''. Neutrino oscillation experiments show that leptons mix very differently from quarks, adding a major challenge to the flavour puzzle. We briefly sketch the seesaw and the dark-matter-mediated ``scotogenic'' neutrino mass generation approaches. We discuss the limitation

Jacco H. Terwel, Kate Maguire, Georgios Dimitriadis, Mat Smith

The nature of the progenitor systems and explosion mechanisms that give rise to Type Ia supernovae (SNe Ia) are still debated. The interaction signature of circumstellar material (CSM) being swept up by expanding ejecta can constrain the type of system from which it was ejected. Most previous studies have focused on finding CSM ejected shortly before the SN

Matthew Baumgart, Panagiotis Christeas

Naive intuition about scale decoupling breaks down in the presence of fermion masses. Kinematic enhancements can greatly extend the range where one needs to keep a finite mass in calculations to obtain a correct result at even the O(1) level. Treating a light fermion as massive though, leads to a known but somewhat obscure paradox, a seeming leading-order se

I. Arrazola, Y. Minoguchi, M. -A. Lemonde, A. Sipahigil

We analyze the implementation of high-fidelity, phonon-mediated gate operations and quantum simulation schemes for spin qubits associated with silicon vacancy centers in diamond. Specifically, we show how the application of continuous dynamical decoupling techniques can substantially boost the coherence of the qubit states while increasing at the same time t

McKenna Leichty, Peter Garnavich, Colin Littlefield, Axel D. Schwope

We analyze 15 years of eclipse timings of the polar V808 Aur. The rapid ingress/egress of the white dwarf and bright accretion region provide timings as precise as a few tenths of a second for rapid cadence photometric data. We find that between 2015 and 2018, the eclipse timings deviated from a linear ephemeris by more than 30 s. The rapid timing change is

Simon Clery, Marcos A. G. Garcia, Yann Mambrini, Keith A. Olive

We consider the effects of a bare mass term for the inflaton, when the inflationary potential takes the form $V(\phi)= \lambda \phi^k$ about its minimum with $k \ge 4$. We concentrate on $k=4$, but discuss general cases as well. Further, we assume $\lambda \phi_{\rm end}^2 \gg m_\phi^2$, where $\phi_{\rm end}$ is the inflaton field value when the inflationar

Edvige Corbelli, Andreas Burkert

We investigate a possible close encounter between M33 and M31 in the past to understand the role of galaxy-galaxy interactions in shaping the matter distribution in galaxy outskirts. We recovered possible orbital trajectories of M33, M31 and the Milky Way in the past, which are compatible with the Early Third Data Release of the Gaia mission and with mass es

Noushin Karim, Michelle L. M. Collins, Duncan A. Forbes, Justin I. Read

We report the discovery of 23 globular cluster (GC) candidates around the relatively isolated dwarf galaxy IC 2574 within the Messier 81 (M81) group, at a distance of 3.86 Mpc. We use observations from the HST Advanced Camera for Surveys (ACS) to analyse the imaging in the F814W and F555W broadband filters. Our GC candidates have luminosities ranging from $-

Rayna Rampalli, Melissa K. Ness, Graham H. Edwards, Elisabeth R. Newton

The elemental abundances of stars, particularly the refractory elements (e.g., Fe, Si, Mg), play an important role in connecting stars to their planets. Most Sun-like stars do not have refractory abundance measurements since obtaining a large sample of high-resolution spectra is difficult with oversubscribed observing resources. In this work we infer abundan

Sabya Sachi Chatterjee, Stéphane Lavignac, O. G. Miranda, G. Sanchez Garcia

After the first observation of coherent elastic neutrino-nucleus scattering (CE$\nu$NS) by the COHERENT collaboration, many efforts are being made to improve the measurement of this process, making it possible to constrain new physics in the neutrino sector. In this paper, we study the sensitivity to non-standard interactions (NSIs) and generalized neutrino

YuZheng Xie, Andrew Hardy, Arun Paramekanti

Motivated by systems where a high temperature non-Fermi liquid gives way to low temperature $\mathbb{Z}_3$ Potts nematic order, we studied a three-orbital Sachdev-Ye-Kitaev (SYK) model in the large-$N$ limit. In the single-site limit, this model exhibits a spontaneous orbital-selective transition which preserves average particle-hole symmetry, with two orbit

Joseph Callow, Or Graur, Peter Clark, Antonella Palmese

High-ionization iron coronal lines (CLs) are a rare phenomenon observed in galaxy and quasi-stellar object spectra that are thought to be created by high-energy emission from active galactic nuclei and certain types of transients. In cases known as extreme coronal line emitting galaxies (ECLEs), these CLs are strong and fade away on a timescale of years. The

Tom Steudtner

We revisit the scalar potential in the Litim-Sannino model. We compute for the first time the full quantum corrections to the classical potential and show that they significantly ameliorate the stability analysis at the UV fixed point. The quantum effective potential is computed at two-loop order and the numerical precision is further improved using resummat

John S. Van Dyke, Zackary White, Gregory Quiroz

Zero-noise extrapolation (ZNE), a technique to estimate quantum circuit expectation values through noise scaling and extrapolation, is well-studied in the context of quantum computing. We examine the applicability of ZNE to the field of quantum sensing. Focusing on the problem of DC magnetometry using the Ramsey protocol, we show that the sensitivity (in the

Gaia Fabj, Johan Samsing

There are indications that stellar-origin black holes (BHs) are efficiently paired up in binary black holes (BBHs) in Active Galactic Nuclei (AGN) disc environments, which can undergo interactions with single BHs in the disc. Such binary-single interactions can potentially lead to an exceptionally high fraction of gravitational-wave mergers with measurable e

Dhruva K. S, Deep Mazumdar, Shivang Yadav

In this paper, we study the implications of conformal invariance in momentum space for correlation functions in quantum mechanics. We find that three point functions of arbitrary operators can be written in terms of the $_2 F_1$ hypergeometric function. We then show that generic four-point functions can be expressed in terms of Appell's generalized hypergeom

Gideon Ilani, Kuan-Chou Hou, Uri Keshet

We detect a highly significant excess of X-ray (2RXS) and radio (NVSS, GMRT, VLSSr) catalog sources when stacked around MCXC galaxy clusters and groups, narrowly confined within $\lesssim100\mathrm{\,kpc}$ of the $\sim2.4 R_{500}$ virial shock radius (inferred from previous continuum stacking), with similar X-ray ($\sim4\sigma$ for $443$ clusters) and radio

Connor A. Painter, Michael Boylan-Kolchin, Philip Mocz, Mark Vogelsberger

Fuzzy Dark Matter (FDM) comprised of ultralight ($m \sim 10^{-22}~\rm{eV}$) boson particles has received significant attention as a viable alternative to Cold Dark Matter (CDM), as it approximates CDM on large scales ($\gtrsim 1$ Mpc) while potentially resolving some of its small-scale problems via kiloparsec-scale quantum interference. However, the most bas

Shiyu Zhou, Yi Teng, Claudio Chamon, Claudio Castelnovo

We introduce a synthetic Mach-Zehnder interferometer for digitized quantum computing devices to probe fractional exchange statistics of anyonic excitations that appear in quantum spin liquids. Employing an IonQ quantum computer, we apply this scheme to the toric ladder, a quasi-one-dimensional reduction of the toric code. We observe interference patterns res

Z. Igo, A. Merloni, D. Hoang, J. Buchner

Radio jets are present in a diverse sample of AGN. However, the mechanisms of jet powering are not fully understood, and it is yet unclear to what extent they obey mass-invariant scaling relations, similar to those found for the triggering and fuelling of X-ray selected AGN. We study the incidence of eROSITA/eFEDS X-ray and LOFAR radio AGN as a function of s

Pablo G. Pérez-González, Pierluigi Rinaldi, Karina I. Caputi, Javier Álvarez-Márquez

We report the discovery of Cerberus, an extremely red object detected with the MIRI Deep Imaging Survey (MIDIS) observations in the F1000W filter of the Hubble Ultra Deep Field. The object is detected at $S/N\sim6$, with $\mathrm{F1000W}\sim27$ mag, and undetected in the NIRCam data gathered by the JWST Advanced Deep Extragalactic Survey, JADES, fainter than

Jasminder S. Sidhu, Rocco Maggi, Saverio Pascazio, Cosmo Lupo

Quantum key distribution (QKD) promises everlasting security based on the laws of physics. Most common protocols are grouped into two distinct categories based on the degrees of freedom used to carry information, which can be either discrete or continuous, each presenting unique advantages in either performance, feasibility for near-term implementation, and

Eetu Loisa, Jim Talbert

We study the matching of Froggatt-Nielsen theories of flavour onto the Standard Model Effective Field Theory (SMEFT), upon integrating out a heavy Beyond-the-Standard-Model (BSM) scalar `flavon' whose vacuum expectation value breaks an Abelian flavour symmetry at energies $\Lambda_\text{FN}$ well above the electroweak scale, $\Lambda_\text{FN} > \Lambda_\tex

Amos Chan, Andrea De Luca

The projected ensemble is based on the study of the quantum state of a subsystem $A$ conditioned on projective measurements in its complement. Recent studies have observed that a more refined measure of the thermalization of a chaotic quantum system can be defined on the basis of convergence of the projected ensemble to a quantum state design, i.e. a system

Kurt Hinterbichler

We catalog all the electromagnetic-like dualities that exist between free dynamical bosonic fields of arbitrary symmetry type and mass on (anti-) de Sitter space in all dimensions, including dualities among the partially massless and shift symmetric fields. This generalizes to all these field types the well known fact that a massless $p$-form is dual to a ma

Jong Yeon Lee

The toric code is a canonical example of a topological error-correcting code. Two logical qubits stored within the toric code are robust against local decoherence, ensuring that these qubits can be faithfully retrieved as long as the error rate remains below a certain threshold. Recent studies have explored such a threshold behavior as an intrinsic informati

Oleksandr Tomalak, Ivan Vitev

Interactions of charged leptons with nuclei and the naive tree-level kinematics of these processes are affected by radiation of photons induced by the QED nuclear medium. We evaluate cross-section modifications at leading orders of the number of correlated interactions inside the nucleus, known as the opacity expansion. We derive results for soft and colline

Jaewon Kim, Ehud Altman, Shubhayu Chatterjee

Several strongly correlated metals display B-linear magnetoresistance (LMR) with a universal slope, in sharp contrast to the $B^2$ scaling predicted by Fermi liquid theory. We provide a unifying explanation of the origin of LMR by focusing on a common feature in their phase diagrams -- proximity to symmetry-breaking orders. Specifically, we demonstrate via t

Juan Urrutia, Ville Vaskonen

Gravitational wave timbre, the relative amplitude and phase of the different frequency harmonics, can change due to interactions with low-mass halos. We focus on binaries in the LISA range and find that the integrated lens effect of cold dark matter structures can be used to probe the existence of $M_{\rm v}\lesssim 10\, M_{\odot}$ halos if a single binary w

Babak Ehteshami Bejnordi, Gaurav Kumar, Amelie Royer, Christos Louizos

Jointly learning multiple tasks with a unified model can improve accuracy and data efficiency, but it faces the challenge of task interference, where optimizing one task objective may inadvertently compromise the performance of another. A solution to mitigate this issue is to allocate task-specific parameters, free from interference, on top of shared feature

Mihail Stoian

We study the fundamental scheduling problem $1\|\sum p_jU_j$. Given a set of $n$ jobs with processing times $p_j$ and deadlines $d_j$, the problem is to select a subset of jobs such that the total processing time is maximized without violating the deadlines. In the midst of a flourishing line of research, Fischer and Wennmann have recently devised the sought

Yichi Zhang, Ziqiao Ma, Xiaofeng Gao, Suhaila Shakiah

Most multimodal large language models (MLLMs) learn language-to-object grounding through causal language modeling where grounded objects are captured by bounding boxes as sequences of location tokens. This paradigm lacks pixel-level representations that are important for fine-grained visual understanding and diagnosis. In this work, we introduce GROUNDHOG, a

Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth

Neural operators learn mappings between function spaces, which is practical for learning solution operators of PDEs and other scientific modeling applications. Among them, the Fourier neural operator (FNO) is a popular architecture that performs global convolutions in the Fourier space. However, such global operations are often prone to over-smoothing and ma

Benjamin Bergner, Andrii Skliar, Amelie Royer, Tijmen Blankevoort

Large language models (LLMs) have become ubiquitous in practice and are widely used for generation tasks such as translation, summarization and instruction following. However, their enormous size and reliance on autoregressive decoding increase deployment costs and complicate their use in latency-critical applications. In this work, we propose a hybrid appro

Ming Zhong, Yelong Shen, Shuohang Wang, Yadong Lu

Low-Rank Adaptation (LoRA) is extensively utilized in text-to-image models for the accurate rendition of specific elements like distinct characters or unique styles in generated images. Nonetheless, existing methods face challenges in effectively composing multiple LoRAs, especially as the number of LoRAs to be integrated grows, thus hindering the creation o

Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde

Parameter-efficient fine-tuning optimizes large, pre-trained foundation models by updating a subset of parameters; in this class, Low-Rank Adaptation (LoRA) is particularly effective. Inspired by an effort to investigate the different roles of LoRA matrices during fine-tuning, this paper characterizes and leverages unexpected asymmetry in the importance of l

Ke Liao, Lexin Ding, Christian Schilling

The simultaneous treatment of static and dynamical correlations in strongly-correlated electron systems is a critical challenge. In particular, finding a universal scheme for identifying a single-particle orbital basis that minimizes the representational complexity of the many-body wavefunction is a formidable and longstanding problem. As a substantial contr

Omkar Thawakar, Ashmal Vayani, Salman Khan, Hisham Cholakal

"Bigger the better" has been the predominant trend in recent Large Language Models (LLMs) development. However, LLMs do not suit well for scenarios that require on-device processing, energy efficiency, low memory footprint, and response efficiency. These requisites are crucial for privacy, security, and sustainable deployment. This paper explores the "less i

Linzhuo Li, Yiling Lin, Lingfei Wu

Recent research on the decline in the paper disruption index (D-index) has sparked heated debates among scholars and garnered significant attention from policymakers and research institution leaders globally. To bridge the gap between policymakers' interest and scholars' skepticism about the D-index, we present this article summarizing key insights from our

Sebastián Donoso, Felipe Hernández, Alejandro Maass

We study the topological recurrence phenomenon of actions of locally compact abelian groups on compact metric spaces. In the case of $\mathbb{Z}^d$-actions we develop new techniques to analyze Bohr recurrence sets. These techniques include finding and manipulating correlations between the coordinates of the set of recurrence. Using this, we show that Bohr re

Sohee Yang, Elena Gribovskaya, Nora Kassner, Mor Geva

We study whether Large Language Models (LLMs) latently perform multi-hop reasoning with complex prompts such as "The mother of the singer of 'Superstition' is". We look for evidence of a latent reasoning pathway where an LLM (1) latently identifies "the singer of 'Superstition'" as Stevie Wonder, the bridge entity, and (2) uses its knowledge of Stevie Wonder

Dingkun Guo, Yuqi Xiang, Shuqi Zhao, Xinghao Zhu

Robotic grasping is a fundamental aspect of robot functionality, defining how robots interact with objects. Despite substantial progress, its generalizability to counter-intuitive or long-tailed scenarios, such as objects with uncommon materials or shapes, remains a challenge. In contrast, humans can easily apply their intuitive physics to grasp skillfully a

Aengus Lynch, Phillip Guo, Aidan Ewart, Stephen Casper

Machine unlearning can be useful for removing harmful capabilities and memorized text from large language models (LLMs), but there are not yet standardized methods for rigorously evaluating it. In this paper, we first survey techniques and limitations of existing unlearning evaluations. Second, we apply a comprehensive set of tests for the robustness and com

Sayan Das, Christian Serio

We consider the point-to-point half-space log-gamma polymer model in the unbound phase. We prove that the free energy increment process on the anti-diagonal path converges to the top marginal of a two-layer Markov chain with an explicit description, which can be interpreted as two random walks conditioned softly never to intersect. This limiting law is a sta

Fanny Kassel

Discrete subgroups of SL(2,R) are well understood, and classified by the geometry of the corresponding hyperbolic surfaces. Discrete subgroups of higher-rank semisimple Lie groups, such as SL(n,R) for n>2, remain more mysterious. While lattices in this setting are rigid, there also exist more flexible, "thinner" discrete subgroups, which may have large and i

Gaurav Verma, Minje Choi, Kartik Sharma, Jamelle Watson-Daniels

Multimodal large language models (MLLMs) like LLaVA and GPT-4(V) enable general-purpose conversations about images with the language modality. As off-the-shelf MLLMs may have limited capabilities on images from domains like dermatology and agriculture, they must be fine-tuned to unlock domain-specific applications. The prevalent architecture of current open-

Tibor Rakovszky, Vedika Khemani

We continue the study of classical and quantum low-density parity check (LDPC) codes from a physical perspective. We focus on constructive approaches and formulate a general framework for systematically constructing codes with various features on generic Euclidean and non-Euclidean graphs. These codes can serve as fixed-point limits for phases of matter. To

Luca Zampierin, Ghouthi Boukli Hacene, Bac Nguyen, Mirco Ravanelli

Self-supervised learning (SSL) has achieved remarkable success across various speech-processing tasks. To enhance its efficiency, previous works often leverage the use of compression techniques. A notable recent attempt is DPHuBERT, which applies joint knowledge distillation (KD) and structured pruning to learn a significantly smaller SSL model. In this pape

Aivin V. Solatorio

Embedding models are integral to AI applications like semantic search, personalized recommendations, and retrieval augmented generation for LLMs, necessitating high-quality training data. However, the limited scalability of manual data curation prompts the need for automated methods to ensure data integrity. Traditional unsupervised triplet mining automates

Minyoung Huh, Brian Cheung, Jeremy Bernstein, Phillip Isola

The scalability of deep learning models is fundamentally limited by computing resources, memory, and communication. Although methods like low-rank adaptation (LoRA) have reduced the cost of model finetuning, its application in model pre-training remains largely unexplored. This paper explores extending LoRA to model pre-training, identifying the inherent con