Papers
Research papers from arXiv and related sources
Neural Synchrony Between Socially Interacting Language Models
Neuroscience has uncovered a fundamental mechanism of our social nature: human brain activity becomes synchronized with others in many social contexts involving interaction. Traditionally, social m...
Zhining Zhang, Wentao Zhu, Chi Han, Yizhou Wang, Heng Ji
VQPP: Video Query Performance Prediction Benchmark
Query performance prediction (QPP) is an important and actively studied information retrieval task, having various applications, such as query reformulation, query expansion, and retrieval system s...
Adrian Catalin Lutu, Eduard Poesina, Radu Tudor Ionescu
Reduced Forms: Feasibility, Extremality, Optimality
We study independent private values auction environments in which the auctioneer's revenue depends nonlinearly on bidders' interim winning probabilities. Our framework accommodates heterogeneity am...
Pasha Andreyanov, Ilia Krasikov, Alex Suzdaltsev
Collaborative Processing for Multi-Tenant Inference on Memory-Constrained Edge TPUs
IoT applications are increasingly relying on on-device AI accelerators to ensure high performance, especially in limited connectivity and safety-critical scenarios. However, the limited on-chip mem...
Nathan Ng, Walid A. Hanafy, Prashanthi Kadambi, Balachandra Sunil, Ayush Gupta, David Irwin, Yoge...
Exploiting Liquidity Exhaustion Attacks in Intent-Based Cross-Chain Bridges
Intent-based cross-chain bridges have emerged as an alternative to traditional interoperability protocols by allowing off-chain entities (\emph{solvers}) to immediately fulfill users' orders by fro...
André Augusto, Christof Ferreira Torres, André Vasconcelos, Miguel Correia
The Digital Divide in Generative AI: Evidence from Large Language Model Use in College Admissions Essays
Large language models (LLMs) have become popular writing tools among students and may expand access to high-quality feedback for students with less access to traditional writing support. At the sam...
Jinsook Lee, Conrad Borchers, AJ Alvero, Thorsten Joachims, Rene F. Kizilcec
Topological Exploration of High-Dimensional Empirical Risk Landscapes: general approach, and applications to phase retrieval
We consider the landscape of empirical risk minimization for high-dimensional Gaussian single-index models (generalized linear models). The objective is to recover an unknown signal $\boldsymbolθ^\...
Antoine Maillard, Tony Bonnaire, Giulio Biroli
Asking Forever: Universal Activations Behind Turn Amplification in Conversational LLMs
Multi-turn interaction length is a dominant factor in the operational costs of conversational LLMs. In this work, we present a new failure mode in conversational LLMs: turn amplification, in which ...
Zachary Coalson, Bo Fang, Sanghyun Hong
Exact quantum decision diagrams with scaling guarantees for Clifford+$T$ circuits and beyond
A decision diagram (DD) is a graph-like data structure for homomorphic compression of Boolean and pseudo-Boolean functions. Over the past decades, decision diagrams have been successfully applied t...
Arend-Jan Quist, Tim Coopmans, Alfons Laarman
CLUTCH: Contextualized Language model for Unlocking Text-Conditioned Hand motion modelling in the wild
Hands play a central role in daily life, yet modeling natural hand motions remains underexplored. Existing methods that tackle text-to-hand-motion generation or hand animation captioning rely on st...
Balamurugan Thambiraja, Omid Taheri, Radek Danecek, Giorgio Becherini, Gerard Pons-Moll, Justus T...
Minimal Dark Matter: Generalized Framework and Direct-Detection Sensitivity
Minimal electroweak dark matter models are compelling due to their simplicity, though calculations of their freezeout abundance are complicated by nonperturbative effects due to Sommerfeld enhancem...
Spencer Griffith, Juri Smirnov, Laura Lopez-Honorez, John F. Beacom
Identifying Exoplanets with Deep Learning VI. Enhancing neural network mitigation of stellar activity RV signals with additional metrics
The measurement of exoplanet masses using the radial velocity (RV) technique is currently limited by stellar activity, which introduces quasiperiodic variability signals that must be modeled and re...
Naomi McWilliam, Zoë L. de Beurs, Andrew Vanderburg, Javier Viaña, Annelies Mortier, Lars A. Buch...
Pushing spectral siren cosmology into the third-generation era: a blinded mock data challenge
Gravitational wave (GW) spectral sirens offer a promising method for measuring cosmological parameters using GW data only - without relying on external redshift information such as electromagnetic ...
Matteo Tagliazucchi, Michele Moresco, Alessandro Agapito, Michele Mancarella, Sarah Ferraiuolo, S...
Generating the fermion mass hierarchy at the TeV scale
We propose a class of theories to generate quark and lepton mass matrices where the scale of new physics is at the TeV scale, without inducing the large flavor and CP violating processes that are o...
Nima Arkani-Hamed, Carolina Figueiredo, Lawrence J. Hall, Claudio Andrea Manzari
Anisotropic marginal Fermi liquid for Coulomb interacting generalized Weyl fermions
Owing to the power-law anisotropy in the quasiparticle dispersion, yielding an enhanced density of states, the effects of long range Coulomb interaction get amplified in three-dimensional generaliz...
Gabriel Malavé, Rodrigo Soto-Garrido, Bitan Roy, Vladimir Juričić
Sink-Aware Pruning for Diffusion Language Models
Diffusion Language Models (DLMs) incur high inference cost due to iterative denoising, motivating efficient pruning. Existing pruning heuristics largely inherited from autoregressive (AR) LLMs, typ...
Aidar Myrzakhan, Tianyi Li, Bowei Guo, Shengkun Tang, Zhiqiang Shen
The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems
Agentic AI systems are increasingly capable of performing professional and personal tasks with limited human involvement. However, tracking these developments is difficult because the AI agent ecos...
Leon Staufer, Kevin Feng, Kevin Wei, Luke Bailey, Yawen Duan, Mick Yang, A. Pinar Ozisik, Stephen...
Mine and Refine: Optimizing Graded Relevance in E-commerce Search Retrieval
We propose a two-stage "Mine and Refine" contrastive training framework for semantic text embeddings to enhance multi-category e-commerce search retrieval. Large scale e-commerce search demands emb...
Jiaqi Xi, Raghav Saboo, Luming Chen, Martin Wang, Sudeep Das
The Effectiveness of a Virtual Reality-Based Training Program for Improving Body Awareness in Children with Attention Deficit and Hyperactivity Disorder
This study investigates the effectiveness of a Virtual Reality (VR)-based training program in improving body awareness among children with Attention Deficit Hyperactivity Disorder (ADHD). Utilizing...
Aya Abdelnaem El-Basha, Ebtsam ELSayed Mahmoud ELSayes, Ahmad Al-Kabbany
Multi-Round Human-AI Collaboration with User-Specified Requirements
As humans increasingly rely on multiround conversational AI for high stakes decisions, principled frameworks are needed to ensure such interactions reliably improve decision quality. We adopt a hum...
Sima Noorani, Shayan Kiyani, Hamed Hassani, George Pappas