Papers
Research papers from arXiv and related sources
Enhancing Scientific Literature Chatbots with Retrieval-Augmented Generation: A Performance Evaluation of Vector and Graph-Based Systems
This paper investigates the enhancement of scientific literature chatbots through retrieval-augmented generation (RAG), with a focus on evaluating vector- and graph-based retrieval systems. The pro...
Hamideh Ghanadian, Amin Kamali, Mohammad Hossein Tekieh
On the Evaluation Protocol of Gesture Recognition for UAV-based Rescue Operation based on Deep Learning: A Subject-Independence Perspective
This paper presents a methodological analysis of the gesture-recognition approach proposed by Liu and Szirányi, with a particular focus on the validity of their evaluation protocol. We show that th...
Domonkos Varga
StableAML: Machine Learning for Behavioral Wallet Detection in Stablecoin Anti-Money Laundering on Ethereum
Global illicit fund flows exceed an estimated $3.1 trillion annually, with stablecoins emerging as a preferred laundering medium due to their liquidity. While decentralized protocols increasingly a...
Luciano Juvinski, Haochen Li, Alessio Brini
The Token Games: Evaluating Language Model Reasoning with Puzzle Duels
Evaluating the reasoning capabilities of Large Language Models is increasingly challenging as models improve. Human curation of hard questions is highly expensive, especially in recent benchmarks u...
Simon Henniger, Gabriel Poesia
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
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
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 $\boldsymbolθ^\...
Antoine Maillard, Tony Bonnaire, Giulio Biroli
Exact quantum decision diagrams with scaling guarantees for Clifford+$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
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...
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
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...
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
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
Adapting Actively on the Fly: Relevance-Guided Online Meta-Learning with Latent Concepts for Geospatial Discovery
In many real-world settings, such as environmental monitoring, disaster response, or public health, with costly and difficult data collection and dynamic environments, strategically sampling from u...
Jowaria Khan, Anindya Sarkar, Yevgeniy Vorobeychik, Elizabeth Bondi-Kelly
Stochastic galactic supernova flux of semi-relativistic particles
New exotic particles with MeV masses, such as axion-like particles or light dark matter, can be emitted from core-collapse supernovae (SNe) with semi-relativistic velocities. Due to their speed dis...
David Alonso-González, David Cerdeño, Marina Cermeño, Andres D. Perez
Asymptotic Smoothing of the Lipschitz Loss Landscape in Overparameterized One-Hidden-Layer ReLU Networks
We study the topology of the loss landscape of one-hidden-layer ReLU networks under overparameterization. On the theory side, we (i) prove that for convex $L$-Lipschitz losses with an $\ell_1$-regu...
Saveliy Baturin
BMW: Bayesian Model-Assisted Adaptive Phase II Clinical Trial Design for Win Ratio Statistic
The win ratio (WR) statistic is increasingly used to evaluate treatment effects based on prioritized composite endpoints, yet existing Bayesian adaptive designs are not directly applicable because ...
Di Zhu, Yong Zang
BMC4TimeSec: Verification Of Timed Security Protocols
We present BMC4TimeSec, an end-to-end tool for verifying Timed Security Protocols (TSP) based on SMT-based bounded model checking and multi-agent modelling in the form of Timed Interpreted Systems ...
Agnieszka M. Zbrzezny
Asymptotically Optimal Sequential Testing with Markovian Data
We study one-sided and $α$-correct sequential hypothesis testing for data generated by an ergodic Markov chain. The null hypothesis is that the unknown transition matrix belongs to a prescribed set...
Alhad Sethi, Kavali Sofia Sagar, Shubhada Agrawal, Debabrota Basu, P. N. Karthik