Papers by Tai-Wei Chang

2 papers
RED: Unleashing Token-Level Rewards from Holistic Feedback via Reward Redistribution (2025.emnlp-main)

Copied to clipboard

Challenge: Experimental results demonstrate the superiority of our approach to aligning large language models with human preferences.
Approach: They propose a method that evaluates and assigns specific credit to each token using an off-the-shelf reward model.
Outcome: The proposed method evaluates and assigns specific credit to each token using an off-the-shelf reward model.
Optimizing Language Models with Fair and Stable Reward Composition in Reinforcement Learning (2024.emnlp-main)

Copied to clipboard

Challenge: Recent research has developed algorithms for reinforcement learning from human feedback and AI-generated feedback.
Approach: They propose a method for reinforcement learning from human feedback and AI-generated feedback that incorporates weighting, ranking, and constraining to handle disparate rewards.
Outcome: The proposed method reduces disparity and enhances stability among rewards . empirical results show that the proposed method is efficient and straightforward .

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations