Papers
Research papers from arXiv and related sources
Modular Memory is the Key to Continual Learning Agents
Foundation models have transformed machine learning through large-scale pretraining and increased test-time compute. Despite surpassing human performance in several domains, these models remain fun...
Vaggelis Dorovatas, Malte Schwerin, Andrew D. Bagdanov, Lucas Caccia, Antonio Carta, Laurent Char...
Federated Agentic AI for Wireless Networks: Fundamentals, Approaches, and Applications
Agentic artificial intelligence (AI) presents a promising pathway toward realizing autonomous and self-improving wireless network services. However, resource-constrained, widely distributed, and da...
Lingyi Cai, Yu Zhang, Ruichen Zhang, Yinqiu Liu, Tao Jiang, Dusit Niyato, Wei Ni, Abbas Jamalipour
U-Net based particle localization in granular experiments: Accuracy limits and optimization
Identifying the positions of granular particles from experimental images is often complicated by their partial overlap in two dimensional projections. Uneven backgrounds and inhomogeneous illuminat...
Fahad Puthalath, Matthias Schröter, Nicoletta Sanvitale, Matthias Sperl, Peidong Yu
An Analysis of Multi-Task Architectures for the Hierarchic Multi-Label Problem of Vehicle Model and Make Classification
Most information in our world is organized hierarchically; however, many Deep Learning approaches do not leverage this semantically rich structure. Research suggests that human learning benefits fr...
Alexandru Manole, Laura Diosan
Action-Guided Attention for Video Action Anticipation
Anticipating future actions in videos is challenging, as the observed frames provide only evidence of past activities, requiring the inference of latent intentions to predict upcoming actions. Exis...
Tsung-Ming Tai, Sofia Casarin, Andrea Pilzer, Werner Nutt, Oswald Lanz
Bootstrapping Embeddings for Low Resource Languages
Embedding models are crucial to modern NLP. However, the creation of the most effective models relies on carefully constructed supervised finetuning data. For high resource languages, such as Engli...
Merve Basoz, Andrew Horne, Mattia Opper
Solving Inverse PDE Problems using Minimization Methods and AI
Many physical and engineering systems require solving direct problems to predict behavior and inverse problems to determine unknown parameters from measurement. In this work, we study both aspects ...
Noura Helwani, Sophie Moufawad, Georges Sakr
Numerical method for strongly variable-density flows at low Mach number: flame-sheet regularisation and a mass-flux immersed boundary method
A low-Mach-number flow, in the laminar regime, has intrinsically two characteristic spatial scales for a given time scale, or two characteristic temporal scales for a given spatial scale, and these...
Matheus P. Severino, Fernando F. Fachini, Elmer M. Gennaro, Daniel Rodríguez, Leandro F. Souza
GMP: A Benchmark for Content Moderation under Co-occurring Violations and Dynamic Rules
Online content moderation is essential for maintaining a healthy digital environment, and reliance on AI for this task continues to grow. Consider a user comment using national stereotypes to insul...
Houde Dong, Yifei She, Kai Ye, Liangcai Su, Chenxiong Qian, Jie Hao
Learning Domain-Aware Task Prompt Representations for Multi-Domain All-in-One Image Restoration
Recently, significant breakthroughs have been made in all-in-one image restoration (AiOIR), which can handle multiple restoration tasks with a single model. However, existing methods typically focu...
Guanglu Dong, Chunlei Li, Chao Ren, Jingliang Hu, Yilei Shi, Xiao Xiang Zhu, Lichao Mou
Local Gaussian copula inference with structural breaks: testing dependence predictability
We propose a score test for dependence predictability in conditional copulas that is robust to temporal instabilities. Our semiparametric procedure accommodates flexible dynamics in the marginal pr...
Alexander Mayer, Tatsushi Oka, Dominik Wied
Changes in Manuscript Length, Research Team Size, and International Collaboration in the Post-2022 Period: Evidence from PLOS ONE
Large language models (LLMs) have diffused rapidly into academic writing since late 2022. Using the complete population of 109,393 research articles published in \textit{PLOS ONE} between 2019 and ...
Yossi Ben-Zion, Eden Cohen, Nitza Davidovitch
A spatial scan statistical for categorical, functional data
We have developed and tested a spatial scan statistic for categorical, functional data (CFSS) - a data structure within which current approaches cannot identify spatial clusters. Our methodology co...
Camille Frévent, Moustapha Sarr, Sophie Dabo-Niang
Power and Sample Size Calculations for Bayes Factors in two-arm clinical Phase II Trials with binary Endpoints
Bayesian sample size calculations in clinical trials usually rely on complex Monte Carlo simulations in practice. Obtaining bounds on Bayesian notions of the false-positive rate and power often lac...
Riko Kelter
FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents
Fine-tuning large language models for vertical domains remains a labor-intensive and expensive process, requiring domain experts to curate data, configure training, and iteratively diagnose model b...
Qizheng Li, Yifei Zhang, Xiao Yang, Xu Yang, Zhuo Wang, Weiqing Liu, Jiang Bian
Legal RAG Bench: an end-to-end benchmark for legal RAG
We introduce Legal RAG Bench, a benchmark and evaluation methodology for assessing the end-to-end performance of legal RAG systems. As a benchmark, Legal RAG Bench consists of 4,876 passages from t...
Abdur-Rahman Butler, Umar Butler
A speciation simulation that partly passes open-endedness tests
One of the main goals of artificial life research is to recreate in artificial systems the trends for ever more complex and novel entities, interactions and processes that we see in Earth's biosphe...
Théo de Pinho, Lana Sinapayen
Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search
LLM-based agents for machine learning engineering (MLE) predominantly rely on tree search, a form of gradient-free optimization that uses scalar validation scores to rank candidates. As LLM reasoni...
Yifei Zhang, Xu Yang, Xiao Yang, Bowen Xian, Qizheng Li, Shikai Fang, Jingyuan Li, Jian Wang, Min...
Building a Strong Instruction Language Model for a Less-Resourced Language
Large language models (LLMs) have become an essential tool for natural language processing and artificial intelligence in general. Current open-source models are primarily trained on English texts,...
Domen Vreš, Tjaša Arčon, Timotej Petrič, Dario Vajda, Marko Robnik-Šikonja, Iztok Lebar Bajec
Predictive Importance Sampling Based Coverage Verification for Multi-UAV Trajectory Planning
Unmanned aerial vehicle (UAV) networks are emerging as a promising solution for ultra-reliable low-latency communication (URLLC) in next-generation wireless systems. A key challenge in millimeter w...
Snehashish Ghosh, Sasthi C. Ghosh