Papers
Research papers from arXiv and related sources
Automated LLM-Based Accessibility Remediation: From Conventional Websites to Angular Single-Page Applications
Web accessibility remains an unresolved issue for a large part of the web content. There are many tools to detect errors automatically, but fixing those issues is still mostly a manual, slow, and c...
Carla Fernández-Navarro, Francisco Chicano
El Agente Sólido: A New Age(nt) for Solid State Simulations
Quantum chemistry calculations are a key component of the materials discovery process. The results from first-principles explorations enable the prediction of material properties prior to experimen...
Sai Govind Hari Kumar, Yunheng Zou, Andrew Wang, Jesús Valdés-Hernández, Tsz Wai Ko, Nathan Yue, ...
The mean-field control problem for heterogeneous forward-backward systems
We study the problem of mean-field control when the state dynamics are given by general systems of forward-backward stochastic differential equations (FBSDEs) with heterogeneous mean-field interact...
Andreas Sojmark, Zeng Zhang
Understanding the Fine-Grained Knowledge Capabilities of Vision-Language Models
Vision-language models (VLMs) have made substantial progress across a wide range of visual question answering benchmarks, spanning visual reasoning, document understanding, and multimodal dialogue....
Dhruba Ghosh, Yuhui Zhang, Ludwig Schmidt
Learning Compact Video Representations for Efficient Long-form Video Understanding in Large Multimodal Models
With recent advancements in video backbone architectures, combined with the remarkable achievements of large language models (LLMs), the analysis of long-form videos spanning tens of minutes has be...
Yuxiao Chen, Jue Wang, Zhikang Zhang, Jingru Yi, Xu Zhang, Yang Zou, Zhaowei Cai, Jianbo Yuan, Xi...
MantisV2: Closing the Zero-Shot Gap in Time Series Classification with Synthetic Data and Test-Time Strategies
Developing foundation models for time series classification is of high practical relevance, as such models can serve as universal feature extractors for diverse downstream tasks. Although early mod...
Vasilii Feofanov, Songkang Wen, Jianfeng Zhang, Lujia Pan, Ievgen Redko
ADAPT: Hybrid Prompt Optimization for LLM Feature Visualization
Understanding what features are encoded by learned directions in LLM activation space requires identifying inputs that strongly activate them. Feature visualization, which optimizes inputs to maxim...
João N. Cardoso, Arlindo L. Oliveira, Bruno Martins
Simple non-invasive methods for obtaining the intensity and timing of arterial pulse waves
Contraction of the left ventricle of the heart increases aortic root blood pressure (P), diameter (D) and blood velocity (U). When contraction diminishes, all three properties decrease. These pertu...
Ethan M. Rowland, Peter D. Weinberg
Exploring The Impact Of Proactive Generative AI Agent Roles In Time-Sensitive Collaborative Problem-Solving Tasks
Collaborative problem-solving under time pressure is common but difficult, as teams must generate ideas quickly, coordinate actions, and track progress. Generative AI offers new opportunities to as...
Anirban Mukhopadhyay, Kevin Salubre, Hifza Javed, Shashank Mehrotra, Kumar Akash
Quantum superresolution and noise spectroscopy with quantum computing
Quantum metrology of an incoherent signal is a canonical sensing problem related to superresolution and noise spectroscopy. We show that quantum computing can accelerate searches for a weak incoher...
James W. Gardner, Federico Belliardo, Gideon Lee, Tuvia Gefen, Liang Jiang
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
Dual Length Codes for Lossless Compression of BFloat16
Training and serving Large Language Models (LLMs) relies heavily on parallelization and collective operations, which are frequently bottlenecked by network bandwidth. Lossless compression using e.g...
Aditya Agrawal, Albert Magyar, Hiteshwar Eswaraiah, Patrick Sheridan, Pradeep Janedula, Ravi Kris...
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
Strange Undercurrents: A Critical Outlook on AI's Cultural Influence
While generative artificial intelligence (generative AI) is being examined extensively, some issues it epitomizes call for more refined scrutiny and deeper contextualization. Besides the lack of nu...
Dejan Grba
Examining LLMs Ability to Summarize Code Through Mutation-Analysis
As developers increasingly rely on LLM-generated code summaries for documentation, testing, and review, it is important to study whether these summaries accurately reflect what the program actually...
Lara Khatib, Micheal Pu, Bogdan Vasilescu, Meiyappan Nagappan
TFL: Targeted Bit-Flip Attack on Large Language Model
Large language models (LLMs) are increasingly deployed in safety and security critical applications, raising concerns about their robustness to model parameter fault injection attacks. Recent studi...
Jingkai Guo, Chaitali Chakrabarti, Deliang Fan
Influence-Preserving Proxies for Gradient-Based Data Selection in LLM Fine-tuning
Supervised fine-tuning (SFT) relies critically on selecting training data that most benefits a model's downstream performance. Gradient-based data selection methods such as TracIn and Influence Fun...
Sirui Chen, Yunzhe Qi, Mengting Ai, Yifan Sun, Ruizhong Qiu, Jiaru Zou, Jingrui He
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
Causality by Abstraction: Symbolic Rule Learning in Multivariate Timeseries with Large Language Models
Inferring causal relations in timeseries data with delayed effects is a fundamental challenge, especially when the underlying system exhibits complex dynamics that cannot be captured by simple func...
Preetom Biswas, Giulia Pedrielli, K. Selçuk Candan