February 2024 arXiv papers — page 65

Madison Walder, Denis Erkal, Michelle Collins, David Martinez-Delgado

Stellar streams have proven to be powerful tools for measuring the Milky Way's gravitational potential and hence its dark matter halo. In the coming years, Vera Rubin, Euclid, ARRAKIHS, and NGRST will uncover a plethora of streams around external galaxies. Although great in number, observations of these distant streams will often be limited to only the on-sk

G. Palkanoglou, M. Stuck, A. Gezerlis

Any experimental evidence of nucleons paired in spin-triplet states will confirm the existence of an exotic phase of nuclear matter. This type of nuclear superfluidity has been hypothesized in heavy nuclei, where the antagonizing spin-orbit effects are damped, and there it oftentimes coexists with traditional spin-singlet pairing, leading to the possibility

Andrea Pizzi, Norman Y. Yao

Information theoretic measures have helped to sharpen our understanding of many-body quantum states. As perhaps the most well-known example, the entanglement entropy (or more generally, the bipartite mutual information) has become a powerful tool for characterizing the dynamical growth of quantum correlations. By contrast, although computable, the bipartite

Simon Schreyer

In this work, we study the decay of $\overline{D3}$-branes in the setup of Kachru, Pearson, and Verlinde (KPV) at higher order in $\alpha'$ from the perspective of a nonabelian $\overline{D3}$-brane stack. We extend the leading order analysis of KPV by including higher order commutators as well as higher derivative corrections. Recently, the KPV setup has be

Mikhail M. Ivanov, Carolina Cuesta-Lazaro, Siddharth Mishra-Sharma, Andrej Obuljen

Perturbative, or effective field theory (EFT)-based, full-shape analyses of galaxy clustering data involve ``nuisance parameters'' to capture various observational effects such as the galaxy-dark matter connection (galaxy bias). We present an efficient approach to set informative physically motivated priors on these parameters. We extract these priors from s

Matthew R. Buckley, Peizhi Du, Nicolas Fernandez, Mitchell J. Weikert

Cosmological first order phase transitions are typically associated with physics beyond the Standard Model, and thus of great theoretical and observational interest. Models of phase transitions where the energy is mostly converted to dark radiation can be constrained through limits on the dark radiation energy density (parameterized by $\Delta N_{\rm eff}$).

Santiago Giner Olavarrieta, Miaochen Jin, Carlos A. Argüelles, Pablo Fernández

In this letter, we study the potential of boosting the atmospheric neutrino experiments sensitivity to the neutrino mass ordering (NMO) sensitivity by incorporating inelasticity measurements. We show how this observable improves the sensitivity to the NMO and the precision of other neutrino oscillation parameters relevant to atmospheric neutrinos, specifical

Kaushik Borah, Richard J. Hill, Ryan Plestid

The anomalous dimension for heavy-heavy-light effective theory operators describing nuclear beta decay is computed through three-loop order in the static limit. The result at order $Z^2\alpha^3$ corrects a previous result in the literature. An all-orders symmetry is shown to relate the anomalous dimensions at leading and subleading powers of $Z$ at a given o

Fabio Tosi, Youmin Zhang, Ziren Gong, Erik Sandström

Over the past two decades, research in the field of Simultaneous Localization and Mapping (SLAM) has undergone a significant evolution, highlighting its critical role in enabling autonomous exploration of unknown environments. This evolution ranges from hand-crafted methods, through the era of deep learning, to more recent developments focused on Neural Radi

Jianrui Zhang, Mu Cai, Tengyang Xie, Yong Jae Lee

We propose CounterCurate, a framework to comprehensively improve the visio-linguistic compositional reasoning capability for both contrastive and generative multimodal models. In particular, we identify two critical under-explored problems: the neglect of the physically grounded reasoning (counting and position understanding) and the potential of using highl

Sara Pieri, Sahal Shaji Mullappilly, Fahad Shahbaz Khan, Rao Muhammad Anwer

In this paper, we introduce BiMediX, the first bilingual medical mixture of experts LLM designed for seamless interaction in both English and Arabic. Our model facilitates a wide range of medical interactions in English and Arabic, including multi-turn chats to inquire about additional details such as patient symptoms and medical history, multiple-choice que

Bo-Yu Cheng, Wei-Chen Chiu, Yu-Lun Liu

In this paper, we propose an algorithm that allows joint refinement of camera pose and scene geometry represented by decomposed low-rank tensor, using only 2D images as supervision. First, we conduct a pilot study based on a 1D signal and relate our findings to 3D scenarios, where the naive joint pose optimization on voxel-based NeRFs can easily lead to sub-

Kangle Deng, Timothy Omernick, Alexander Weiss, Deva Ramanan

Manually creating textures for 3D meshes is time-consuming, even for expert visual content creators. We propose a fast approach for automatically texturing an input 3D mesh based on a user-provided text prompt. Importantly, our approach disentangles lighting from surface material/reflectance in the resulting texture so that the mesh can be properly relit and

Md Mohaiminul Islam, Ngan Ho, Xitong Yang, Tushar Nagarajan

Most video captioning models are designed to process short video clips of few seconds and output text describing low-level visual concepts (e.g., objects, scenes, atomic actions). However, most real-world videos last for minutes or hours and have a complex hierarchical structure spanning different temporal granularities. We propose Video ReCap, a recursive v

Liyan Tang, Igor Shalyminov, Amy Wing-mei Wong, Jon Burnsky

Single document news summarization has seen substantial progress on faithfulness in recent years, driven by research on the evaluation of factual consistency, or hallucinations. We ask whether these advances carry over to other text summarization domains. We propose a new evaluation benchmark on topic-focused dialogue summarization, generated by LLMs of vary

Efren Hernández-Molina, Benjamin Ojeda-Magaña, Jose Guadalupe Robledo-Hernández, Ruben Ruelas

This paper presents the design of an artificial vision system prototype for automatic inspection and monitoring of objects over a conveyor belt and using a Smart camera 2D BOA-INS. The prototype consists of a conveyor belt and an embedded system based on an Arduino Mega card for system control, and it has as main peripherals the smart camera, a direct curren

Soohyun Park

We find an explicit formula for the gamma vector in terms of the input polynomial in a way that extends it to arbitrary polynomials. More specifically, we find explicit linear combination in terms of coefficients of the input polynomial (using Catalan numbers and binomial coefficients) and an expression involving the derivative of the input polynomial. The f

Mohsen Amiri

Consider a finite group $G$ of order $n$ with a prime divisor $p$. In this article, we establish, among other results, that if the Sylow $p$-subgroup of $G$ is neither cyclic nor generalized quaternion, then there exists a bijection $f$ from $G$ onto the abelian group $C_{\frac{n}{p}}\times C_p$ such that for every element $x$ in $G$, the order of $x$ divide

Akash Ghosh, Arkadeep Acharya, Sriparna Saha, Vinija Jain

The advent of Large Language Models (LLMs) has significantly reshaped the trajectory of the AI revolution. Nevertheless, these LLMs exhibit a notable limitation, as they are primarily adept at processing textual information. To address this constraint, researchers have endeavored to integrate visual capabilities with LLMs, resulting in the emergence of Visio

Irem Portakal, Javier Sendra-Arranz

An $n$-player game $X$ in normal form can be modeled via undirected discrete graphical models where the discrete random variables represent the players and their state spaces are the set of pure strategies. There exists an edge between the vertices of the graphical model whenever there is a dependency between the associated players. We study the Spohn condit

Wojciech J. Jankowski, Robert-Jan Slager

We show that certain three-dimensional multigap topological insulators can host quantized integrated shift photoconductivities due to bulk invariants that are defined under reality conditions imposed by additional symmetries. We recast the quantization in terms of the integrated torsion tensor and the non-Abelian Berry connection constituting Chern-Simons fo

Qiangeng Yang, Tess Christensen, Shlok Gilda, Juliana Fernandes

Fact-checking-specific search tools such as Google Fact Check are a promising way to combat misinformation on social media, especially during events bringing significant social influence, such as the COVID-19 pandemic and the U.S. presidential elections. However, the usability of such an approach has not been thoroughly studied. We evaluated the performance

Bo Jiang, Shaoyu Chen, Hao Gao, Bencheng Liao

Learning a human-like driving policy from large-scale driving demonstrations is promising, but the uncertainty and non-deterministic nature of planning make it challenging. Existing learning-based planning methods follow a deterministic paradigm to directly regress the action, failing to cope with the uncertainty problem. In this work, we propose a probabili

Nathan Geer, Aaron D. Lauda, Bertrand Patureau-Mirand, Joshua Sussan

We study the density of the Burau representation from the perspective of a non-semisimple TQFT at a fourth root of unity. This gives a TQFT construction of Squier's Hermitian form on the Burau representation with possibly mixed signature. We prove that the image of the braid group in the space of possibly indefinite unitary representations is dense. We also

Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang

Conventional causal discovery methods rely on centralized data, which is inconsistent with the decentralized nature of data in many real-world situations. This discrepancy has motivated the development of federated causal discovery (FCD) approaches. However, existing FCD methods may be limited by their potentially restrictive assumptions of identifiable func

S. Goswami, J. M. Vilchez, B. Perez-Diaz, L. Silva

Recent work presented increasing evidence of high, non-constant S/O abundance ratios observed in star-forming metal-poor galaxies, showing deviations from the constant canonical S/O across a large range of O/H abundance. Similar peculiar high Fe/O ratios have been also recently detected. We investigate whether these high S/O ratios at low metallicities could

John Lott

We give obstructions for a noncompact manifold to admit a complete Riemannian metric with (nonuniformly) positive scalar curvature. We treat both the finite volume and infinite volume cases.

R. Rossi, F. Simkovic, M. Ferrero, A. Georges

The spin-fermion (SF) model postulates that the dominant coupling between low-energy fermions in near critical metals is mediated by collective spin fluctuations (paramagnons) peaked at the N\'{e}el wave vector, ${\bf Q}_N$, connecting hot spots on opposite sides of the Fermi surface. It has been argued that strong correlations at hot spots lead to a Fermi s

Guillermo A. Perez, Shrisha Rao

A pushdown vector addition system with states (PVASS) extends the model of vector addition systems with a pushdown stack. The algorithmic analysis of PVASS has applications such as static analysis of recursive programs manipulating integer variables. Unfortunately, reachability analysis, even for one-dimensional PVASS is not known to be decidable. We relax t

Haibin Wu, Xuanjun Chen, Yi-Cheng Lin, Kai-wei Chang

Neural audio codecs are initially introduced to compress audio data into compact codes to reduce transmission latency. Researchers recently discovered the potential of codecs as suitable tokenizers for converting continuous audio into discrete codes, which can be employed to develop audio language models (LMs). Numerous high-performance neural audio codecs a

Zannatun Firdowzy Dey, Debajyoti Dutta

We address the consequence of invisible neutrino decay within the framework of two long base-line neutrino experiments: T2HKK (Tokai-to-Hyper-Kamiokande-to-Korea) and DUNE (Deep Underground Neutrino experiment). Our primary objective is to bring out the aspects of CC (charged current) and NC (neutral current) measurements at DUNE in the context of invisible

Lan Li, Jinpeng Lv

Semantic search, a process aimed at delivering highly relevant search results by comprehending the searcher's intent and the contextual meaning of terms within a searchable dataspace, plays a pivotal role in information retrieval. In this paper, we investigate the application of large language models to enhance semantic search capabilities, specifically tail

Junyao Wang, Mohammad Abdullah Al Faruque

Many real-world applications of the Internet of Things (IoT) employ machine learning (ML) algorithms to analyze time series information collected by interconnected sensors. However, distribution shift, a fundamental challenge in data-driven ML, arises when a model is deployed on a data distribution different from the training data and can substantially degra

Letian Fu, Gaurav Datta, Huang Huang, William Chung-Ho Panitch

Touch is an important sensing modality for humans, but it has not yet been incorporated into a multimodal generative language model. This is partially due to the difficulty of obtaining natural language labels for tactile data and the complexity of aligning tactile readings with both visual observations and language descriptions. As a step towards bridging t

Badr AlKhamissi, Muhammad ElNokrashy, Mai AlKhamissi, Mona Diab

The intricate relationship between language and culture has long been a subject of exploration within the realm of linguistic anthropology. Large Language Models (LLMs), promoted as repositories of collective human knowledge, raise a pivotal question: do these models genuinely encapsulate the diverse knowledge adopted by different cultures? Our study reveals

V. M. A. Gómez-González, Y. D. Mayya, J. Zaragoza-Cardiel, G. Bruzual

We present the analysis of archival Very Large Telescope (VLT) Multi-Unit Spectroscopic Explorer (MUSE) observations of 179 HII regions in the star-forming double-ring collisional galaxy AM 0644-741 at 98.6 Mpc. We determined ionic abundances of He, N, O and Fe using the direct method for the brightest H II region (ID 39); we report $\log\rm{(\frac{N}{O})}=-

Gregory Seregin

In the note, a certain scenario of potential Type II blowups of axisymmetric solutions to the Navier-Stokes equations is considered. The main tool of the treatment of such blowups is the corresponding Euler scaling.

Arka Pal, Deep Karkhanis, Samuel Dooley, Manley Roberts

Direct Preference Optimisation (DPO) is effective at significantly improving the performance of large language models (LLMs) on downstream tasks such as reasoning, summarisation, and alignment. Using pairs of preferred and dispreferred data, DPO models the relative probability of picking one response over another. In this work, first we show theoretically th

Sander Borst, Danish Kashaev, Zhuan Khye Koh

The online matching problem was introduced by Karp, Vazirani and Vazirani (STOC 1990) on bipartite graphs with vertex arrivals. It is well-known that the optimal competitive ratio is $1-1/e$ for both integral and fractional versions of the problem. Since then, there has been considerable effort to find optimal competitive ratios for other related settings. I

Tae Jun Jang, Chang Min Hyun

This article presents a novel undersampled magnetic resonance imaging (MRI) technique that leverages the concept of Neural Radiance Field (NeRF). With radial undersampling, the corresponding imaging problem can be reformulated into an image modeling task from sparse-view rendered data; therefore, a high dimensional MR image is obtainable from undersampled k-

Qiao Jin, Zhizheng Wang, Yifan Yang, Qingqing Zhu

Clinical calculators play a vital role in healthcare by offering accurate evidence-based predictions for various purposes such as prognosis. Nevertheless, their widespread utilization is frequently hindered by usability challenges, poor dissemination, and restricted functionality. Augmenting large language models with extensive collections of clinical calcul

Alban Puech, Tristan Rigaut, William Templier, Maud Tournoud

This paper introduces an Electric Vehicle Charging Station (EVCS) model that incorporates real-world constraints, such as slot power limitations, contract threshold overruns penalties, or early disconnections of electric vehicles (EVs). We propose a formulation of the problem of EVCS control under uncertainty, and implement two Multi-Stage Stochastic Program

Andrei Khurshudov

Cities worldwide are rapidly adopting smart technologies, transforming urban life. Despite this trend, a universally accepted definition of 'smart city' remains elusive. Past efforts to define it have not yielded a consensus, as evidenced by the numerous definitions in use. In this paper, we endeavored to create a new 'compromise' definition that should reso

Rebecca Gore, Steven Giacalone, Courtney D. Dressing, Emma V. Turtelboom

We collected near-infrared spectra of 65 cool stars with the NASA InfraRed Telescope Facility (IRTF) and analyze them to calculate accurate metallicities and stellar parameters. The sample of 55 M dwarfs and 10 K dwarfs includes 25 systems with confirmed planets and 27 systems with planet candidates identified by the K2 and TESS missions. Three of the 25 con

Adrian Cosma, Bogdan Iordache, Paolo Rosso

Recently, large language models (LLMs) have become increasingly powerful and have become capable of solving a plethora of tasks through proper instructions in natural language. However, the vast majority of testing suites assume that the instructions are written in English, the de facto prompting language. Code intelligence and problem solving still remain a

Ulrik Friis-Jensen, Frederik L. Johansen, Andy S. Anker, Erik B. Dam

Advances in graph machine learning (ML) have been driven by applications in chemistry as graphs have remained the most expressive representations of molecules. While early graph ML methods focused primarily on small organic molecules, recently, the scope of graph ML has expanded to include inorganic materials. Modelling the periodicity and symmetry of inorga

Yusu Qian, Haotian Zhang, Yinfei Yang, Zhe Gan

The remarkable advancements in Multimodal Large Language Models (MLLMs) have not rendered them immune to challenges, particularly in the context of handling deceptive information in prompts, thus producing hallucinated responses under such conditions. To quantitatively assess this vulnerability, we present MAD-Bench, a carefully curated benchmark that contai

Ammar N. Abbas, Chidera W. Amazu, Joseph Mietkiewicz, Houda Briwa

In complex industrial and chemical process control rooms, effective decision-making is crucial for safety and efficiency. The experiments in this paper evaluate the impact and applications of an AI-based decision support system integrated into an improved human-machine interface, using dynamic influence diagrams, a hidden Markov model, and deep reinforcement

Nikolai Bolik, Sandro Wimberger

Quantum walks have gained significant attention over the past decades, mainly because of their variety of implementations and applications. Atomic quantum walks are typically subject to spontaneous emissions arising from the control fields. We investigate spontaneous emission in an atom optics kicked rotor quantum walk. Here, spontaneous emission occurs natu

Long Zhao, Nitesh B. Gundavarapu, Liangzhe Yuan, Hao Zhou

We introduce VideoPrism, a general-purpose video encoder that tackles diverse video understanding tasks with a single frozen model. We pretrain VideoPrism on a heterogeneous corpus containing 36M high-quality video-caption pairs and 582M video clips with noisy parallel text (e.g., ASR transcripts). The pretraining approach improves upon masked autoencoding b

Ryosuke Shimada

Motivated by the problem of giving an explicit description of the basic locus in the reduction of Shimura varieties, G\"{o}rtz, He and Nie studied the cases where the basic affine Deligne-Lusztig variety, which serves as its group-theoretic model, is a union of classical Deligne-Lusztig varieties associated to Coxeter elements. In this paper, we study a natu

Md Shafkat Bin Hoque, Rachel A. Nye, Saman Zare, Stephanie Atkinson

The multifaceted applications of polymers are often limited by their thermal conductivity. Therefore, understanding the mechanisms of thermal transport in polymers is of vital interest. Here, we leverage molecular layer deposition to grow three types of hybrid metalcone (i.e., alucone, zincone, and tincone) films and study their thermal and acoustic properti

Benjamin Plaut, Nguyen X. Khanh, Tu Trinh

We study 15 large language models (LLMs) fine-tuned for chat and find that their maximum softmax probabilities (MSPs) are consistently miscalibrated on multiple-choice Q&A. However, those MSPs might still encode useful uncertainty information. Specifically, we hypothesized that wrong answers would be associated with smaller MSPs compared to correct answers.

Han Wang, Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

Generations from large language models (LLMs) can be improved by sampling and scoring multiple solutions to select a final answer. Current "sample and select" methods such as self-consistency (SC) rely on majority voting to score answers. However, when tasks have many distinct and valid answers, selection by voting requires a large number of samples. This ma

Dongjin Kang, Sunghwan Kim, Taeyoon Kwon, Seungjun Moon

Emotional Support Conversation (ESC) is a task aimed at alleviating individuals' emotional distress through daily conversation. Given its inherent complexity and non-intuitive nature, ESConv dataset incorporates support strategies to facilitate the generation of appropriate responses. Recently, despite the remarkable conversational ability of large language

Adam X. Yang, Maxime Robeyns, Thomas Coste, Zhengyan Shi

To ensure that large language model (LLM) responses are helpful and non-toxic, a reward model trained on human preference data is usually used. LLM responses with high rewards are then selected through best-of-$n$ (BoN) sampling or the LLM is further optimized to produce responses with high rewards through reinforcement learning from human feedback (RLHF). H

Edoardo Rizzi

We realize 4 of the 6 closed orientable flat 3-manifolds as a cusp section of an orientable finite-volume hyperbolic 4-manifold whose symmetry group acts transitively on the set of cusps.

Marco Gaido, Sara Papi, Matteo Negri, Luisa Bentivogli

The attention mechanism, a cornerstone of state-of-the-art neural models, faces computational hurdles in processing long sequences due to its quadratic complexity. Consequently, research efforts in the last few years focused on finding more efficient alternatives. Among them, Hyena (Poli et al., 2023) stands out for achieving competitive results in both lang

Patrik Milán Veres, Krisztina Éva Gabányi, Sándor Frey, Zsolt Paragi

Context. According to the hierarchical structure formation model, brightest cluster galaxies (BCGs) evolve into the most luminous and massive galaxies in the Universe through multiple merger events. The peculiar radio source 4C 35.06 is located at the core of the galaxy cluster Abell 407, overlapping with a compact group of nine galaxies. Low-frequency radio

Javier Álvarez-Vizoso

Two formulas for the classical number $C_n$ of lines on a generic hypersurface of degree $2n-3$ in $\mathbb{CP}^n$ are obtained which differ from the formulas by Dominici, Harris, Libgober, and van der Waerden-Zagier. We review the splitting principle computation by Harris obtaining a similar general closed-form formula in terms of the Catalan numbers and el

Jin Bakalis, Sergii Chernov, Ziling Li, Alice Kunin

The unique optical properties of graphene, with broadband absorption and ultrafast response, make it a critical component of optoelectronic and spintronic devices. Using time-resolved momentum microscopy with high data rate and high dynamic range, we report momentum-space measurements of electrons promoted to the graphene conduction band with visible light,

Halima Bouzidi, Smail Niar, Hamza Ouarnoughi, El-Ghazali Talbi

Recent advancements in Artificial Intelligence (AI), driven by Neural Networks (NN), demand innovative neural architecture designs, particularly within the constrained environments of Internet of Things (IoT) systems, to balance performance and efficiency. HW-aware Neural Architecture Search (HW-aware NAS) emerges as an attractive strategy to automate the de

Anna-Luisa E. Römling, Akashdeep Kamra

N\'eel ordered antiferromagnets exhibit two-mode squeezing such that their ground state is a nonclassical superposition of magnon Fock states. Here we theoretically demonstrate that antiferromagnets can couple to spin qubits via direct dispersive interaction stemming from, e.g., interfacial exchange. We demonstrate that this kind of coupling induces a magnon

Stefan Steinerberger

A Hadamard matrix is a scaled orthogonal matrix with $\pm 1$ entries. Such matrices exist in certain dimensions: the Hadamard conjecture is that such a matrix always exists when $n$ is a multiple of 4. A conjecture attributed to Ryser is that no circulant Hadamard matrices exist when $n > 4$. Recently, Dong and Rudelson proved the existence of approximate Ha

Orhan Eren Akgün, Néstor Cuevas, Matheus Farias, Daniel Garces

Resource-constrained robotic platforms are particularly useful for tasks that require low-cost hardware alternatives due to the risk of losing the robot, like in search-and-rescue applications, or the need for a large number of devices, like in swarm robotics. For this reason, it is crucial to find mechanisms for adapting reinforcement learning techniques to

Adrien Mounier

Let $\mathcal{A}$ be a finite set of positive integers and $y\geq 1$. We give an effective lower bound of the cardinality of the set $\{n\in\mathcal{A};\,p|n\Longrightarrow p\leq y\}$ under the condition of a good knowledge of the level of distribution of the set $\mathcal{A}$. Some consequences are studied: an application to the friable values of irreducibl

Alex Moriani

A polygonal surface in the pseudo-hyperbolic space H^(2,n) is a complete maximal surface bounded by a lightlike polygon in the Einstein universe Ein^(1,n) with finitely many vertices. In this article, we give several characterizations of them. Polygonal surfaces are characterized by finiteness of their total curvature and by asymptotic flatness. They have pa

Roman Pogodin, Antonin Schrab, Yazhe Li, Danica J. Sutherland

We describe a data-efficient, kernel-based approach to statistical testing of conditional independence. A major challenge of conditional independence testing is to obtain the correct test level (the specified upper bound on the rate of false positives), while still attaining competitive test power. Excess false positives arise due to bias in the test statist

Collin Hague, Nick Kakavitsas, Jincheng Zhang, Chris Beam

This paper describes the hardware design and flight demonstration of a small quadrotor with imaging sensors for urban mapping, hazard avoidance, and target tracking research. The vehicle is equipped with five cameras, including two pairs of fisheye stereo cameras that enable a nearly omnidirectional view and a two-axis gimbaled camera. An onboard NVIDIA Jets

Minglai Cai, Andreas Winter

We consider the private classical capacity of a quantum wiretap channel, where the users (sender Alice, receiver Bob, and eavesdropper Eve) have access to the resource of a shared quantum state, additionally to their channel inputs and outputs. An extreme case is maximal entanglement or a secret key between Alice and Bob, both of which would allow for onetim

Pedro E. Harunari, Sara Dal Cengio, Vivien Lecomte, Matteo Polettini

For continuous-time Markov chains and open unimolecular chemical reaction networks, we prove that any two stationary currents are linearly related upon perturbations of a single edge's transition rates, arbitrarily far from equilibrium. We extend the result to non-stationary currents in the frequency domain, provide and discuss an explicit expression for the

B. R. Vinay Kumar, Lasse Leskelä

This work studies queues in a Euclidean space. Consider $N$ servers that are distributed uniformly in $[0,1]^d$. Customers arrive at the servers according to independent stationary processes. Upon arrival, they probabilistically decide whether to join the queue they arrived at, or shift to one of the nearest neighbours. Such shifting strategies affect the lo

Francesco Salzano, Lodovica Marchesi, Remo Pareschi, Roberto Tonelli

Context: Blockchain-based Information Ecosystems (BBIEs) are a type of information ecosystem in which blockchain technology is used to provide a trust mechanism among parties and to manage shared business logic, breaking the traditional scheme of Information Ecosystems dominated by a leading company and leveraging the decentralization of data management, inf

Natalia Żywucka, Julian Sitarek, Dorota Sobczyńska, Mario Pecimotika

Context. The presence of clouds during observations with Imaging Atmospheric Cherenkov Telescopes can strongly affect the performance of the instrument due to additional absorption of light and scattering of light beyond the field of view of the instrument. If not corrected for, the presence of clouds leads to increased systematic errors in the results. Aims

Gopal R. Iyer, Noah Whelpley, Juha Tiihonen, Paul R. C. Kent

Stochastic electronic structure theories, e.g., Quantum Monte Carlo methods, enable highly accurate total energy calculations which in principle can be used to construct highly accurate potential energy surfaces. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms fo

Chao Xue, Di Liang, Pengfei Wang, Jing Zhang

Many models that leverage knowledge graphs (KGs) have recently demonstrated remarkable success in question answering (QA) tasks. In the real world, many facts contained in KGs are time-constrained thus temporal KGQA has received increasing attention. Despite the fruitful efforts of previous models in temporal KGQA, they still have several limitations. (I) Th

Lunjia Hu, Arun Jambulapati, Kevin Tian, Chutong Yang

In the recent literature on machine learning and decision making, calibration has emerged as a desirable and widely-studied statistical property of the outputs of binary prediction models. However, the algorithmic aspects of measuring model calibration have remained relatively less well-explored. Motivated by [BGHN23], which proposed a rigorous framework for

Jeongyoon Choi, Dukjae Jang, Youngshin Kwon, Gwangeon Seong

We investigate the evolution of non-extensivity in the photon distribution during the Big Bang Nucleosynthesis (BBN) epoch using Tsallis statistics. Assuming a minimal deviation from the Planck distribution, we construct the perturbed Boltzmann equation for photons, including the collision terms for pair creation and annihilation processes. We analyze the po

Jianhong Bai, Tianyu He, Yuchi Wang, Junliang Guo

Recent advances in text-guided video editing have showcased promising results in appearance editing (e.g., stylization). However, video motion editing in the temporal dimension (e.g., from eating to waving), which distinguishes video editing from image editing, is underexplored. In this work, we present UniEdit, a tuning-free framework that supports both vid

Zhaoqian Xue, Beichen Wang, Suiyuan Zhu, Kai Mei

This study introduces "CosmoAgent," an innovative artificial intelligence system that utilizes Large Language Models (LLMs) to simulate complex interactions between human and extraterrestrial civilizations. This paper introduces a mathematical model for quantifying the levels of civilization development and further employs a state transition matrix approach

Daniel D. Leister, Justin P. Koeln

Robust Model Predictive Control (MPC) for nonlinear systems is a problem that poses significant challenges as highlighted by the diversity of approaches proposed in the last decades. Often compromises with respect to computational load, conservatism, generality, or implementation complexity have to be made, and finding an approach that provides the right bal

Nikola Pavlovic, Sudeep Salgia, Qing Zhao

We consider distributed kernel bandits where $N$ agents aim to collaboratively maximize an unknown reward function that lies in a reproducing kernel Hilbert space. Each agent sequentially queries the function to obtain noisy observations at the query points. Agents can share information through a central server, with the objective of minimizing regret that i

Norman Di Palo, Edward Johns

We propose DINOBot, a novel imitation learning framework for robot manipulation, which leverages the image-level and pixel-level capabilities of features extracted from Vision Transformers trained with DINO. When interacting with a novel object, DINOBot first uses these features to retrieve the most visually similar object experienced during human demonstrat

Philipp Schmidt, Sören Arlt, Carlos Ruiz-Gonzalez, Xuemei Gu

Generative Artificial Intelligence (AI) models can propose solutions to scientific problems beyond human capability. To truly make conceptual contributions, researchers need to be capable of understanding the AI-generated structures and extracting the underlying concepts and ideas. When algorithms provide little explanatory reasoning alongside the output, sc

Lewis Picker, Ryosuke Hirai, Ilya Mandel

We explore the evolution of massive stars (>8 solar masses) with 1-D models and present analytical fits to the masses and binding energies of the convective portions of their envelopes. These fits are given as functions of total mass, metallicity, and surface temperature (used as a proxy for evolutionary phase). They enable the application of the two-stage c

Nathan Corbyn, Lukas Heidemann, Nick Hu, Chiara Sarti

We present the proof assistant homotopy.io for working with finitely-presented semistrict higher categories. The tool runs in the browser with a point-and-click interface, allowing direct manipulation of proof objects via a graphical representation. We describe the user interface and explain how the tool can be used in practice. We also describe the essentia

Guangzhi Xiong, Qiao Jin, Zhiyong Lu, Aidong Zhang

While large language models (LLMs) have achieved state-of-the-art performance on a wide range of medical question answering (QA) tasks, they still face challenges with hallucinations and outdated knowledge. Retrieval-augmented generation (RAG) is a promising solution and has been widely adopted. However, a RAG system can involve multiple flexible components,

Azin Yazdi, Sunder Ramachandran, Hoda Mohsenifard, Khaled Nawaser

Business research is facing the challenge of scattered knowledge, particularly in the realm of brand loyalty (BL). Although literature reviews on BL exist, they predominantly concentrate on the pre-sent state, neglecting future trends. Therefore, a comprehensive review is imperative to ascertain emerging trends in BL This study employs a bibliometric approac

Xiaotian Zou, Yongkang Chen, Ke Li

The rapid evolution of Large Language Models (LLMs) has rendered them indispensable in modern society. While security measures are typically to align LLMs with human values prior to release, recent studies have unveiled a concerning phenomenon named "Jailbreak". This term refers to the unexpected and potentially harmful responses generated by LLMs when promp

Camilla Brizzi, Gero Friesecke, Tobias Ried

We generalize the notion and theory of Wasserstein barycenters introduced by Agueh and Carlier (2011) from the quadratic cost to general smooth strictly convex costs $h$ with non-degenerate Hessian. We show the equivalence between a coupled two-marginal and a multi-marginal formulation and establish that the multi-marginal optimal plan is unique and of Monge

Raul Quiroga-Barranco

Building from ideas of hypercomplex analysis on the quaternionic unit ball, we introduce Hermitian, Riemannian and K\"ahler-like structures on the latter. These are built from the so-called regular M\"obius transformations. Such geometric structures are shown to be natural generalizations of those from the complex setup. Our structures can be considered as m

Zhen Lian, Yun-Mei Li, Li Yan, Lei Ma

The enhanced Coulomb interaction in two-dimensional (2D) semiconductors leads to the tightly bound electron-hole pairs known as excitons. The large binding energy of excitons enables the formation of Rydberg excitons with high principal quantum numbers (n), analogous to Rydberg atoms. Rydberg excitons possess strong interactions among themselves, as well as

Peixin Luo, Baolin Tan

Solar activities have a great impact on modern high-tech systems, such as human aerospace, satellite communication and navigation, deep space exploration, and related scientific research. Therefore, studying the long - term evolution trend of solar activity and accurately predicting the future solar cycles is highly anticipated. Based on wavelet transform an

Zhi-Yi Lin, Bofan Lyu, Judith Cueto Fernandez, Eline van der Kruk

Accurate 3D kinematics estimation of human body is crucial in various applications for human health and mobility, such as rehabilitation, injury prevention, and diagnosis, as it helps to understand the biomechanical loading experienced during movement. Conventional marker-based motion capture is expensive in terms of financial investment, time, and the exper

Tatiana Belova, Nikolai Chukhin, Alexander S. Kulikov, Ivan Mihajlin

More than 40 years ago, Schroeppel and Shamir presented an algorithm that solves the Subset Sum problem for $n$ integers in time $O^*(2^{0.5n})$ and space $O^*(2^{0.25n})$. The time upper bound remains unbeaten, but the space upper bound has been improved to $O^*(2^{0.249999n})$ in a recent breakthrough paper by Nederlof and W\k{e}grzycki (STOC 2021). Their

Roshan Lal Neupane, Ernest Bonnah, Bishnu Bhusal, Kiran Neupane

Insurance claims processing involves multi-domain entities and multi-source data, along with a number of human-agent interactions. Use of Blockchain technology-based platform can significantly improve scalability and response time for processing of claims which are otherwise manually-intensive and time-consuming. However, the chaincodes involved within the p

Benedikt Remlein, Udo Seifert

Chemical reaction networks can undergo nonequilibrium phase transitions upon variation of external control parameters like the chemical potential of a species. We investigate the flux in the associated chemostats that is proportional to the entropy production and its critical fluctuations within the Schl\"ogl model. Numerical simulations show that the corres

Josué Knorst, Christian Olivera, Alexandre B. de Souza

We study two interacting particle systems, both modeled as a system of $N$ stochastic differential equations driven by Brownian motions with singular kernels and moderate interaction. We show a quantitative result where the convergence rate depends on the moderate scaling parameter, the regularity of the solution of the limit equation and the dimension. Our

Samir D. Mathur, Madhur Mehta

An extremely compact object (ECO) is defined as a quantum object without horizon, whose radius is just a small distance $s$ outside its Schwarzschild radius. We show that any ECO of mass $M$ in $d+1$ dimensions with $s\ll (M/m_p)^{2/(d-2)(d+1)}l_p$ must have (at leading order) the same thermodynamic properties -- temperature, entropy and radiation rates -- a

P. J. Millican, R. J. Furnstahl, J. A. Melendez, D. R. Phillips

We test the BUQEYE model of correlated effective field theory (EFT) truncation errors on Reinert, Krebs, and Epelbaum's semi-local momentum-space implementation of the chiral EFT ($\chi$EFT) expansion of the nucleon-nucleon (NN) potential. This Bayesian model hypothesizes that dimensionless coefficient functions extracted from the order-by-order corrections