Papers
Research papers from arXiv and related sources
Knowledge Access Beats Model Size: Memory Augmented Routing for Persistent AI Agents
Production AI agents frequently receive user-specific queries that are highly repetitive, with up to 47\% being semantically similar to prior interactions, yet each query is typically processed wit...
Xunzhuo Liu, Bowei He, Xue Liu, Andy Luo, Haichen Zhang, Huamin Chen
Can Large Language Models Reason and Optimize Under Constraints?
Large Language Models (LLMs) have demonstrated great capabilities across diverse natural language tasks; yet their ability to solve abstraction and optimization problems with constraints remains sc...
Fabien Bernier, Salah Ghamizi, Pantelis Dogoulis, Maxime Cordy
JFTA-Bench: Evaluate LLM's Ability of Tracking and Analyzing Malfunctions Using Fault Trees
In the maintenance of complex systems, fault trees are used to locate problems and provide targeted solutions. To enable fault trees stored as images to be directly processed by large language mode...
Yuhui Wang, Zhixiong Yang, Ming Zhang, Shihan Dou, Zhiheng Xi, Enyu Zhou, Senjie Jin, Yujiong She...
Set-Valued Prediction for Large Language Models with Feasibility-Aware Coverage Guarantees
Large language models (LLMs) inherently operate over a large generation space, yet conventional usage typically reports the most likely generation (MLG) as a point prediction, which underestimates ...
Ye Li, Anqi Hu, Yuanchang Ye, Shiyan Tong, Zhiyuan Wang, Bo Fu
Toward Integrated Sensing, Communications, and Edge Intelligence Networks
Wireless systems are expanding their purposes, from merely connecting humans and things to connecting intelligence and opportunistically sensing of the environment through radio-frequency signals. ...
Mattia Merluzzi, Miltiadis C. Filippou, Paolo Di Lorenzo, George C. Alexandropoulos
Privacy-Preserving EHR Data Transformation via Geometric Operators: A Human-AI Co-Design Technical Report
Electronic health records (EHRs) and other real-world clinical data are essential for clinical research, medical artificial intelligence, and life science, but their sharing is severely limited by ...
Maolin Wang, Beining Bao, Gan Yuan, Hongyu Chen, Bingkun Zhao, Baoshuo Kan, Jiming Xu, Qi Shi, Yi...
Caption Generation for Dongba Paintings via Prompt Learning and Semantic Fusion
Dongba paintings, the treasured pictorial legacy of the Naxi people in southwestern China, feature richly layered visual elements, vivid color palettes, and pronounced ethnic and regional cultural ...
Shuangwu Qian, Xiaochan Yuan, Pengfei Liu
From Morality Installation in LLMs to LLMs in Morality-as-a-System
Work on morality in large language models (LLMs) has progressed via constitutional AI, reinforcement learning from human feedback (RLHF) and systematic benchmarking, yet it still lacks tools to con...
Gunter Bombaerts
PersonalQ: Select, Quantize, and Serve Personalized Diffusion Models for Efficient Inference
Personalized text-to-image generation lets users fine-tune diffusion models into repositories of concept-specific checkpoints, but serving these repositories efficiently is difficult for two reason...
Qirui Wang, Qi Guo, Yiding Sun, Junkai Yang, Dongxu Zhang, Shanmin Pang, Qing Guo
Optimizing Small Language Models for NL2SQL via Chain-of-Thought Fine-Tuning
Translating Natural Language to SQL (NL2SQL) remains a critical bottleneck for democratization of data in enterprises. Although Large Language Models (LLMs) like Gemini 2.5 and other LLMs have demo...
Anshul Solanki, Sanchit Latawa, Koushik Chakraborty, Navneet Kamboj
Ran Score: a LLM-based Evaluation Score for Radiology Report Generation
Chest X-ray report generation and automated evaluation are limited by poor recognition of low-prevalence abnormalities and inadequate handling of clinically important language, including negation a...
Ran Zhang, Yucong Lin, Zhaoli Su, Bowen Liu, Danni Ai, Tianyu Fu, Deqiang Xiao, Jingfan Fan, Yuan...
SoK: The Attack Surface of Agentic AI -- Tools, and Autonomy
Recent AI systems combine large language models with tools, external knowledge via retrieval-augmented generation (RAG), and even autonomous multi-agent decision loops. This agentic AI paradigm gre...
Ali Dehghantanha, Sajad Homayoun
The EU AI Act and the Rights-based Approach to Technological Governance
The EU AI Act constitutes an important development in shaping the Union's digital regulatory architecture. The Act places fundamental rights at the heart of a risk-based governance framework. The a...
Georgios Pavlidis
IntentWeave: A Progressive Entry Ladder for Multi-Surface Browser Agents in Cloud Portals
Browser agents built on LLMs can act in web interfaces, yet most remain confined to a single chat surface (e.g., a sidebar). This mismatch with real browsing can increase context-switching and redu...
Wanying Mo, Jijia Lai, Xiaoming Wang
Multilingual KokoroChat: A Multi-LLM Ensemble Translation Method for Creating a Multilingual Counseling Dialogue Dataset
To address the critical scarcity of high-quality, publicly available counseling dialogue datasets, we created Multilingual KokoroChat by translating KokoroChat, a large-scale manually authored Japa...
Ryoma Suzuki, Zhiyang Qi, Michimasa Inaba
From the AI Act to a European AI Agency: Completing the Union's Regulatory Architecture
As artificial intelligence (AI) technologies continue to advance, effective risk assessment, regulation, and oversight are necessary to ensure that AI development and deployment align with ethical ...
Georgios Pavlidis
EchoKV: Efficient KV Cache Compression via Similarity-Based Reconstruction
The increasing memory demand of the Key-Value (KV) cache poses a significant bottleneck for Large Language Models (LLMs) in long-context applications. Existing low-rank compression methods often re...
Yixuan Wang, Shiyu Ji, Yijun Liu, Qingfu Zhu, Wanxiang Che
Dual-Teacher Distillation with Subnetwork Rectification for Black-Box Domain Adaptation
Assuming that neither source data nor the source model is accessible, black box domain adaptation represents a highly practical yet extremely challenging setting, as transferable information is res...
Zhe Zhang, Jing Li, Wanli Xue, Xu Cheng, Jianhua Zhang, Qinghua Hu, Shengyong Chen
Separating Diagnosis from Control: Auditable Policy Adaptation in Agent-Based Simulations with LLM-Based Diagnostics
Mitigating elderly loneliness requires policy interventions that achieve both adaptability and auditability. Existing methods struggle to reconcile these objectives: traditional agent-based models ...
Shaoxin Zhong, Yuchen Su, Michael Witbrock
Task-Aware Positioning for Improvisational Tasks in Mobile Construction Robots via an AI Agent with Multi-LMM Modules
Due to the ever-changing nature of construction, many tasks on sites occur in an improvisational manner. Existing mobile construction robot studies remain limited in addressing improvisational task...
Seongju Jang, Francis Baek, SangHyun Lee