7 papers
SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution
Hongyi Liu, Haoyan Yang, Tao Jiang +4
Long-horizon LLM agents generate traces that could become reusable experience, but raw trajectories are noisy, local, and hard to govern. Agent Skills offer a structured artifact f…
SEDualVLN: A Spatially-Enhanced Dual-System Framework for Vision-Language Navigation
Jingzhi Huang, Junkai Huang, Wenxuan Song +6
Vision-Language Navigation (VLN) approaches have currently followed two primary paradigms: the end-to-end Vision-Language Model (VLM) policy fine-tuned on navigation trajectories t…
Capability Self-Assessment in Large Language Models
Haoyan Yang, Reza Shirkavand, Yukai Jin +3
The ability to recognize one's own limitations and decide whether to solve a problem or seek help is fundamental to reliable intelligent systems. Yet modern large language models t…
A Survey of Large Language Models for Perception and Measurement of Human Psychology
Yudong Li, Xiaoyi Chen, Jiawei Cai +4
Against the backdrop of the rapid advancement of Large Language Models (LLMs), their application in the field of psychology has garnered significant academic attention. A central i…
Self-Improvement of Large Language Models: A Technical Overview and Future Outlook
Haoyan Yang, Mario Xerri, Solha Park +4
As large language models (LLMs) continue to advance, improving them solely through human supervision is becoming increasingly costly and limited in scalability. As models approach…
Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector
Haoyan Yang, Runxue Bao, Cao Xiao +4
LLM-as-a-Judge has emerged as a promising tool for automatically evaluating generated outputs, but its reliability is often undermined by potential biases in judgment. Existing eff…
Dynamic Noise Preference Optimization: Self-Improvement of Large Language Models with Self-Synthetic Data
Haoyan Yang, Khiem Le, Ting Hua +7
Although LLMs have achieved significant success, their reliance on large volumes of human-annotated data has limited their potential for further scaling. In this situation, utilizi…