Papers
Research papers from arXiv and related sources
PromptTuner: SLO-Aware Elastic System for LLM Prompt Tuning
Prompt tuning has become a prominent strategy for enhancing the performance of Large Language Models (LLMs) on downstream tasks. Many IT enterprises now offer Prompt-Tuning-as-a-Service to fulfill ...
Wei Gao, Peng Sun, Dmitrii Ustiugov, Tianwei Zhang, Yonggang Wen
Jagarin: A Three-Layer Architecture for Hibernating Personal Duty Agents on Mobile
Personal AI agents face a fundamental deployment paradox on mobile: persistent background execution drains battery and violates platform sandboxing policies, yet purely reactive agents miss time-se...
Ravi Kiran Kadaboina
Cyber Threat Intelligence for Artificial Intelligence Systems
As artificial intelligence (AI) becomes deeply embedded in critical services and everyday products, it is increasingly exposed to security threats which traditional cyber defenses were not designed...
Natalia Krawczyk, Mateusz Szczepkowski, Adrian Brodzik, Krzysztof Bocianiak
NeuronMoE: Neuron-Guided Mixture-of-Experts for Efficient Multilingual LLM Extension
Extending large language models to low-resource languages is essential for global accessibility, but training separate models per language is prohibitively expensive. Mixture-of-Experts (MoE) archi...
Rongzhi Li, Hitomi Yanaka
WebFactory: Automated Compression of Foundational Language Intelligence into Grounded Web Agents
Current paradigms for training GUI agents are fundamentally limited by a reliance on either unsafe, non-reproducible live web interactions or costly, scarce human-crafted data and environments. We ...
Sicheng Fan, Qingyun Shi, Shengze Xu, Shengbo Cai, Tieyong Zeng, Li Ling, Yanyi Shang, Dehan Kong
Why Do You Contribute to Stack Overflow? Understanding Cross-Cultural Motivations and Usage Patterns before the Age of LLMs
Understanding motivations of contributors for participating in community question and answer platforms is crucial for sustaining knowledge-sharing ecosystem, which is necessary to advance the disci...
Sherlock A. Licorish, Elijah Zolduoarrati, Tony Savarimuthu, Rashina Hoda, Ronnie De Souza Santos...
The Trilingual Triad Framework: Integrating Design, AI, and Domain Knowledge in No-code AI Smart City Course
This paper introduces the "Trilingual Triad" framework, a model that explains how students learn to design with generative artificial intelligence (AI) through the integration of Design, AI, and Do...
Qian Huang, King Wang Poon
Good-Enough LLM Obfuscation (GELO)
Large Language Models (LLMs) are increasingly served on shared accelerators where an adversary with read access to device memory can observe KV caches and hidden states, threatening prompt privacy ...
Anatoly Belikov, Ilya Fedotov
The "Gold Rush" in AI and Robotics Patenting Activity. Do innovation systems have a role?
This paper studies patenting trends in artificial intelligence (AI) and robotics from 1980 to 2019. We introduce a novel distinction between traditional robotics and robotics embedding AI functiona...
Giovanni Guidetti, Riccardo Leoncini, Mariele Macaluso
AegisUI: Behavioral Anomaly Detection for Structured User Interface Protocols in AI Agent Systems
AI agents that build user interfaces on the fly assembling buttons, forms, and data displays from structured protocol payloads are becoming common in production systems. The trouble is that a paylo...
Mohd Safwan Uddin, Saba Hajira
Survive at All Costs: Exploring LLM's Risky Behaviors under Survival Pressure
As Large Language Models (LLMs) evolve from chatbots to agentic assistants, they are increasingly observed to exhibit risky behaviors when subjected to survival pressure, such as the threat of bein...
Yida Lu, Jianwei Fang, Xuyang Shao, Zixuan Chen, Shiyao Cui, Shanshan Bian, Guangyao Su, Pei Ke, ...
S5-SHB Agent: Society 5.0 enabled Multi-model Agentic Blockchain Framework for Smart Home
The smart home is a key application domain within the Society 5.0 vision for a human-centered society. As smart home ecosystems expand with heterogeneous IoT protocols, diverse devices, and evolvin...
Janani Rangila, Akila Siriweera, Incheon Paik, Keitaro Naruse, Isuru Jayanada, Vishmika Devindi
RepoLaunch: Automating Build&Test Pipeline of Code Repositories on ANY Language and ANY Platform
Building software repositories typically requires significant manual effort. Recent advances in large language model (LLM) agents have accelerated automation in software engineering (SWE). We intro...
Kenan Li, Rongzhi Li, Linghao Zhang, Qirui Jin, Liao Zhu, Xiaosong Huang, Geng Zhang, Yikai Zhang...
Measuring the Fragility of Trust: Devising Credibility Index via Explanation Stability (CIES) for Business Decision Support Systems
Explainable Artificial Intelligence (XAI) methods (SHAP, LIME) are increasingly adopted to interpret models in high-stakes businesses. However, the credibility of these explanations, their stabilit...
Alin-Gabriel Vaduva, Simona-Vasilica Oprea, Adela Bara
BioLLMAgent: A Hybrid Framework with Enhanced Structural Interpretability for Simulating Human Decision-Making in Computational Psychiatry
Computational psychiatry faces a fundamental trade-off: traditional reinforcement learning (RL) models offer interpretability but lack behavioral realism, while large language model (LLM) agents ge...
Zuo Fei, Kezhi Wang, Xiaomin Chen, Yizhou Huang
Tell2Adapt: A Unified Framework for Source Free Unsupervised Domain Adaptation via Vision Foundation Model
Source Free Unsupervised Domain Adaptation (SFUDA) is critical for deploying deep learning models across diverse clinical settings. However, existing methods are typically designed for low-gap, spe...
Yulong Shi, Shijie Li, Ziyi Li, Lin Qi
ThaiSafetyBench: Assessing Language Model Safety in Thai Cultural Contexts
The safety evaluation of large language models (LLMs) remains largely centered on English, leaving non-English languages and culturally grounded risks underexplored. In this work, we investigate LL...
Trapoom Ukarapol, Nut Chukamphaeng, Kunat Pipatanakul, Pakhapoom Sarapat
Training for Technology: Adoption and Productive Use of Generative AI in Legal Analysis
Can targeted user training unlock the productive potential of generative artificial intelligence (GenAI) in professional settings? We investigate this question using a randomized study involving 16...
Benjamin M. Chen, Hong Bao
3D-RFT: Reinforcement Fine-Tuning for Video-based 3D Scene Understanding
Reinforcement Learning with Verifiable Rewards ( RLVR ) has emerged as a transformative paradigm for enhancing the reasoning capabilities of Large Language Models ( LLMs), yet its potential in 3D s...
Xiongkun Linghu, Jiangyong Huang, Baoxiong Jia, Siyuan Huang
VRM: Teaching Reward Models to Understand Authentic Human Preferences
Large Language Models (LLMs) have achieved remarkable success across diverse natural language tasks, yet the reward models employed for aligning LLMs often encounter challenges of reward hacking, w...
Biao Liu, Ning Xu, Junming Yang, Hao Xu, Xin Geng