5 papers
Test-Time Policy Adaptation for Enhanced Multi-Turn Interactions with LLMs
Chenxing Wei, Hong Wang, Ying He +2
Large Language Models (LLMs) employ multi-turn interaction as a fundamental paradigm for completing complex tasks. However, their performance often degrades in extended interaction…
ReDit: Reward Dithering for Improved LLM Policy Optimization
Chenxing Wei, Jiarui Yu, Ying Tiffany He +3
DeepSeek-R1 has successfully enhanced Large Language Model (LLM) reasoning capabilities through its rule-based reward system. While it's a ''perfect'' reward system that effectivel…
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
Yao Shu, Wenyang Hu, See-Kiong Ng +2
Large Language Models (LLMs) have become indispensable in numerous real-world applications. However, fine-tuning these models at scale, especially in federated settings where data…
Flexora: Flexible Low Rank Adaptation for Large Language Models
Chenxing Wei, Yao Shu, Ying Tiffany He +1
Large Language Models (LLMs) are driving advancements in artificial intelligence by increasing the scale of model parameters, which has significantly enhanced generalization abilit…
OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations
Yao Shu, Jiongfeng Fang, Ying Tiffany He +1
First-order optimization (FOO) algorithms are pivotal in numerous computational domains such as machine learning and signal denoising. However, their application to complex tasks l…