From the 1 of 5 linked papers with an AI index.
5 papers
FARS: A Fully Automated Research System Deployed at Scale
Qiong Tang, Tianxiang Sun, Xiangkun Hu +54
FARS is an AI-driven system that autonomously creates research projects, runs experiments, and writes full AI/ML papers across many topics, and its output was evaluated through str…
NLL-Guided Full-Attention Layer Selection for Training-Free Sliding-Window Adaptation
Qiong Tang, Xiangkun Hu, Xiangyang Liu +2
Hybrid attention models that mix full and sliding-window attention across layers offer a promising approach to efficient long-context inference, but the critical question of \emph{…
Output-Space Allocation Costs for Calibration-Guided LLM Compression: An Empirical Study
Qiong Tang, Xiangkun Hu, Xiangyang Liu +2
Training-free compression methods for large language models (LLMs) often use calibration data to guide compression decisions. ROCKET, a recent method combining sparse-dictionary fa…
Quantifying Fairness in LLMs Beyond Tokens: A Semantic and Statistical Perspective
Weijie Xu, Yiwen Wang, Chi Xue +4
Large Language Models (LLMs) often generate responses with inherent biases, undermining their reliability in real-world applications. Existing evaluation methods often overlook bia…
Explicit Preference Optimization: No Need for an Implicit Reward Model
Xiangkun Hu, Lemin Kong, Tong He +1
The generated responses of large language models (LLMs) are often fine-tuned to human preferences through a process called reinforcement learning from human feedback (RLHF). As RLH…