Papers by Tai-Wei Chang
RED: Unleashing Token-Level Rewards from Holistic Feedback via Reward Redistribution (2025.emnlp-main)
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| 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)
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| 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 . |