Papers
Research papers from arXiv and related sources
AdaFuse: Accelerating Dynamic Adapter Inference via Token-Level Pre-Gating and Fused Kernel Optimization
The integration of dynamic, sparse structures like Mixture-of-Experts (MoE) with parameter-efficient adapters (e.g., LoRA) is a powerful technique for enhancing Large Language Models (LLMs). Howeve...
Qiyang Li, Rui Kong, Yuchen Li, Hengyi Cai, Shuaiqiang Wang, Linghe Kong, Guihai Chen, Dawei Yin
Social, Legal, Ethical, Empathetic and Cultural Norm Operationalisation for AI Agents
As AI agents are increasingly used in high-stakes domains like healthcare and law enforcement, aligning their behaviour with social, legal, ethical, empathetic, and cultural (SLEEC) norms has becom...
Radu Calinescu, Ana Cavalcanti, Marsha Chechik, Lina Marsso, Beverley Townsend
You Told Me to Do It: Measuring Instructional Text-induced Private Data Leakage in LLM Agents
High-privilege LLM agents that autonomously process external documentation are increasingly trusted to automate tasks by reading and executing project instructions, yet they are granted terminal ac...
Ching-Yu Kao, Xinfeng Li, Shenyu Dai, Tianze Qiu, Pengcheng Zhou, Eric Hanchen Jiang, Philip Sperl
The Landscape of Generative AI in Information Systems: A Synthesis of Secondary Reviews and Research Agendas
As organizations grapple with the rapid adoption of Generative AI (GenAI), this study synthesizes the state of knowledge through a systematic literature review of secondary studies and research age...
Aleksander Jarzębowicz, Adam Przybyłek, Jacinto Estima, Yen Ying Ng, Jakub Swacha, Beata Zielosko...
Hybrid Human-Agent Social Dilemmas in Energy Markets
In hybrid populations where humans delegate strategic decision-making to autonomous agents, understanding when and how cooperative behaviors can emerge remains a key challenge. We study this proble...
Isuri Perera, Frits de Nijs, Julian Garcia
Towards High-Fidelity CAD Generation via LLM-Driven Program Generation and Text-Based B-Rep Primitive Grounding
The field of Computer-Aided Design (CAD) generation has made significant progress in recent years. Existing methods typically fall into two separate categorie: parametric CAD modeling and direct bo...
Jiahao Li, Qingwang Zhang, Qiuyu Chen, Guozhan Qiu, Yunzhong Lou, Xiangdong Zhou
Large language models for optical network O&M: Agent-embedded workflow for automation
With the continuous expansion of optical networks and the increasing diversity of services, existing operation and maintenance (O&M) approaches are increasingly challenged to meet the rising demand...
Shengnan Li, Yidi Wang, Fubin Wang, Yujia Yang, Yao Zhang, Yuchen Song, Xiaotian Jiang, Yue Pang,...
Stuck on Suggestions: Automation Bias, the Anchoring Effect, and the Factors That Shape Them in Computational Pathology
Artificial intelligence (AI)-driven decision support systems can improve diagnostic accuracy and efficiency in computational pathology. However, collaboration between human experts and AI may intro...
Emely Rosbach, Jonas Ammeling, Jonathan Ganz, Christof Albert Bertram, Thomas Conrad, Andreas Rie...
OMNIA: Closing the Loop by Leveraging LLMs for Knowledge Graph Completion
Knowledge Graphs (KGs) are widely used to represent structured knowledge, yet their automatic construction, especially with Large Language Models (LLMs), often results in incomplete or noisy output...
Frédéric Ieng, Soror Sahri, Mourad Ouzzani, Massinissa Hammaz, Salima Benbernou, Hanieh Khorashad...
Automated Detection of Malignant Lesions in the Ovary Using Deep Learning Models and XAI
The unrestrained proliferation of cells that are malignant in nature is cancer. In recent times, medical professionals are constantly acquiring enhanced diagnostic and treatment abilities by implem...
Md. Hasin Sarwar Ifty, Nisharga Nirjan, Labib Islam, M. A. Diganta, Reeyad Ahmed Ornate, Anika Ta...
Automating Skill Acquisition through Large-Scale Mining of Open-Source Agentic Repositories: A Framework for Multi-Agent Procedural Knowledge Extraction
The transition from monolithic large language models (LLMs) to modular, skill-equipped agents represents a fundamental architectural shift in artificial intelligence deployment. While general-purpo...
Shuzhen Bi, Mengsong Wu, Hao Hao, Keqian Li, Wentao Liu, Siyu Song, Hongbo Zhao, Aimin Zhou
DocSage: An Information Structuring Agent for Multi-Doc Multi-Entity Question Answering
Multi-document Multi-entity Question Answering inherently demands models to track implicit logic between multiple entities across scattered documents. However, existing Large Language Models (LLMs)...
Teng Lin, Yizhang Zhu, Zhengxuan Zhang, Yuyu Luo, Nan Tang
Locating Demographic Bias at the Attention-Head Level in CLIP's Vision Encoder
Standard fairness audits of foundation models quantify that a model is biased, but not where inside the network the bias resides. We propose a mechanistic fairness audit that combines projected res...
Alaa Yasser, Kittipat Phunjanna, Marcos Escudero Viñolo, Catarina Barata, Jenny Benois-Pineau
Language Generation with Replay: A Learning-Theoretic View of Model Collapse
As scaling laws push the training of frontier large language models (LLMs) toward ever-growing data requirements, training pipelines are approaching a regime where much of the publicly available on...
Giorgio Racca, Michal Valko, Amartya Sanyal
From Debate to Deliberation: Structured Collective Reasoning with Typed Epistemic Acts
Multi-agent LLM systems increasingly tackle complex reasoning, yet their interaction patterns remain limited to voting, unstructured debate, or pipeline orchestration. None model deliberation: a ph...
Sunil Prakash
Trust Oriented Explainable AI for Fake News Detection
This article examines the application of Explainable Artificial Intelligence (XAI) in NLP based fake news detection and compares selected interpretability methods. The work outlines key aspects of ...
Krzysztof Siwek, Daniel Stankowski, Maciej Stodolski
Exploiting Expertise of Non-Expert and Diverse Agents in Social Bandit Learning: A Free Energy Approach
Personalized AI-based services involve a population of individual reinforcement learning agents. However, most reinforcement learning algorithms focus on harnessing individual learning and fail to ...
Erfan Mirzaei, Seyed Pooya Shariatpanahi, Alireza Tavakoli, Reshad Hosseini, Majid Nili Ahmadabadi
Controllable Egocentric Video Generation via Occlusion-Aware Sparse 3D Hand Joints
Motion-controllable video generation is crucial for egocentric applications in virtual reality and embodied AI. However, existing methods often struggle to achieve 3D-consistent fine-grained hand a...
Chenyangguang Zhang, Botao Ye, Boqi Chen, Alexandros Delitzas, Fangjinhua Wang, Marc Pollefeys, X...
Gender Bias in Generative AI-assisted Recruitment Processes
In recent years, generative artificial intelligence (GenAI) systems have assumed increasingly crucial roles in selection processes, personnel recruitment and analysis of candidates' profiles. Howev...
Martina Ullasci, Marco Rondina, Riccardo Coppola, Antonio Vetrò
When OpenClaw Meets Hospital: Toward an Agentic Operating System for Dynamic Clinical Workflows
Large language model (LLM) agents extend conventional generative models by integrating reasoning, tool invocation, and persistent memory. Recent studies suggest that such agents may significantly i...
Wenxian Yang, Hanzheng Qiu, Bangqun Zhang, Chengquan Li, Zhiyong Huang, Xiaobin Feng, Rongshan Yu...