Papers
Research papers from arXiv and related sources
A Platform-Agnostic Multimodal Digital Human Modelling Framework: Neurophysiological Sensing in Game-Based Interaction
Digital Human Modelling (DHM) is increasingly shaped by advances in AI, wearable biosensing, and interactive digital environments, particularly in research addressing accessibility and inclusion. H...
Daniel J. Buxton, Mufti Mahmud, Jordan J. Bird, Thomas Hughes-Roberts, David J. Brown
From Education to Evidence: A Collaborative Practice Research Platform for AI-Integrated Agile Development
Agile software development evolves so rapidly that research struggles to remain timely and transferable - an issue heightened by the swift adoption of generative AI and agentic tools. Earlier discu...
Tobias Geger, Andreas Rausch, Ina Schiering, Frauke Stenzel, Stefan Wittek
Emulating Clinician Cognition via Self-Evolving Deep Clinical Research
Clinical diagnosis is a complex cognitive process, grounded in dynamic cue acquisition and continuous expertise accumulation. Yet most current artificial intelligence (AI) systems are misaligned wi...
Ruiyang Ren, Yuhao Wang, Yunsen Liang, Lan Luo, Jing Liu, Haifeng Wang, Cong Feng, Yinan Zhang, C...
Breaking User-Centric Agency: A Tri-Party Framework for Agent-Based Recommendation
Recent advances in large language models (LLMs) have stimulated growing interest in agent-based recommender systems, enabling language-driven interaction and reasoning for more expressive preferenc...
Yaxin Gong, Chongming Gao, Chenxiao Fan, Wenjie Wang, Fuli Feng, Xiangnan He
Terminal Is All You Need: Design Properties for Human-AI Agent Collaboration
While research on AI agents focuses on enabling them to operate graphical user interfaces, the most effective and widely adopted agent tools in practice are terminal-based. We argue that this conve...
Alexandre De Masi
ESG Reporting Lifecycle Management with Large Language Models and AI Agents
Environmental, Social, and Governance (ESG) standards have been increasingly adopted by organizations to demonstrate accountability towards ethical, social, and sustainability goals. However, gener...
Thong Hoang, Mykhailo Klymenko, Xiwei Xu, Shidong Pan, Yi Ding, Xushuo Tang, Zhengyi Yang, Jieke ...
Making Bielik LLM Reason (Better): A Field Report
This paper presents a research program dedicated to evaluating and advancing the reasoning capabilities of Bielik, a Polish large language model. The study describes a number of stages of work: ini...
Adam Trybus, Bartosz Bartnicki, Remigiusz Kinas
Splat2Real: Novel-view Scaling for Physical AI with 3D Gaussian Splatting
Physical AI faces viewpoint shift between training and deployment, and novel-view robustness is essential for monocular RGB-to-3D perception. We cast Real2Render2Real monocular depth pretraining as...
Hansol Lim, Jongseong Brad Choi
Disentangling Similarity and Relatedness in Topic Models
The recent advancement of large language models has spurred a growing trend of integrating pre-trained language model (PLM) embeddings into topic models, fundamentally reshaping how topics capture ...
Hanlin Xiao, Mauricio A. Álvarez, Rainer Breitling
Formulation of intrinsic nonlinear thermal conductivity for bosonic systems using quantum kinetic equation
Nonlinear responses in transport phenomena have attracted significant attention because they can arise even when linear responses are forbidden by symmetry, with the quantum geometry of Bloch wave ...
Aoi Kuwabara, Joji Nasu
Trajectory-Informed Memory Generation for Self-Improving Agent Systems
LLM-powered agents face a persistent challenge: learning from their execution experiences to improve future performance. While agents can successfully complete many tasks, they often repeat ineffic...
Gaodan Fang, Vatche Isahagian, K. R. Jayaram, Ritesh Kumar, Vinod Muthusamy, Punleuk Oum, Gegi Th...
Layer Consistency Matters: Elegant Latent Transition Discrepancy for Generalizable Synthetic Image Detection
Recent rapid advancement of generative models has significantly improved the fidelity and accessibility of AI-generated synthetic images. While enabling various innovative applications, the unprece...
Yawen Yang, Feng Li, Shuqi Kong, Yunfeng Diao, Xinjian Gao, Zenglin Shi, Meng Wang
Does LLM Alignment Really Need Diversity? An Empirical Study of Adapting RLVR Methods for Moral Reasoning
Reinforcement learning with verifiable rewards (RLVR) has achieved remarkable success in logical reasoning tasks, yet whether large language model (LLM) alignment requires fundamentally different a...
Zhaowei Zhang, Xiaohan Liu, Xuekai Zhu, Junchao Huang, Ceyao Zhang, Zhiyuan Feng, Yaodong Yang, X...
Distilling LLM Semantic Priors into Encoder-Only Multi-Talker ASR with Talker-Count Routing
Large language models (LLMs) provide strong semantic priors that can improve multi-talker automatic speech recognition (MT-ASR), but using an LLM as an autoregressive decoder is computationally exp...
Hao Shi, Yusuke Fujita, Roman Koshkin, Mengjie Zhao, Yuan Gao, Lianbo Liu, Yui Sudo
Attribution as Retrieval: Model-Agnostic AI-Generated Image Attribution
With the rapid advancement of AIGC technologies, image forensics will encounter unprecedented challenges. Traditional methods are incapable of dealing with increasingly realistic images generated b...
Hongsong Wang, Renxi Cheng, Chaolei Han, Jie Gui
End-to-End Chatbot Evaluation with Adaptive Reasoning and Uncertainty Filtering
Large language models (LLMs) combined with retrieval augmented generation have enabled the deployment of domain-specific chatbots, but these systems remain prone to generating unsupported or incorr...
Nhi Dang, Tung Le, Huy Tien Nguyen
Adaptive RAN Slicing Control via Reward-Free Self-Finetuning Agents
The integration of Generative AI models into AI-native network systems offers a transformative path toward achieving autonomous and adaptive control. However, the application of such models to cont...
Yuanhao Li, Haozhe Wang, Geyong Min, Nektarios Georgalas, Wang Miao
PET-F2I: A Comprehensive Benchmark and Parameter-Efficient Fine-Tuning of LLMs for PET/CT Report Impression Generation
PET/CT imaging is pivotal in oncology and nuclear medicine, yet summarizing complex findings into precise diagnostic impressions is labor-intensive. While LLMs have shown promise in medical text ge...
Yuchen Liu, Wenbo Zhang, Liling Peng, Yichi Zhang, Yu Fu, Xin Guo, Chao Qu, Yuan Qi, Le Xue
CD-Raft: Reducing the Latency of Distributed Consensus in Cross-Domain Sites
Today's massive AI computation loads push heavy data synchronization across sites, i.e., nodes in data centers. Any reduction in such consensus latency can significantly improve the overall perform...
Yangyang Wang, Ziqian Cheng, Yucong Dong, Zichen Xu
Towards Cognitive Defect Analysis in Active Infrared Thermography with Vision-Text Cues
Active infrared thermography (AIRT) is currently witnessing a surge of artificial intelligence (AI) methodologies being deployed for automated subsurface defect analysis of high performance carbon ...
Mohammed Salah, Eman Ouda, Giuseppe Dell'Avvocato, Fabrizio Sarasini, Ester D'Accardi, Jorge Dias...