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cs.CL2024
Bridging the Language Gaps in Large Language Models with Inference-Time Cross-Lingual Intervention
Weixuan Wang, Minghao Wu, Barry Haddow +1
Large Language Models (LLMs) have shown remarkable capabilities in natural language processing but exhibit significant performance gaps among different languages. Most existing app…
cs.AI2024
Rewarding What Matters: Step-by-Step Reinforcement Learning for Task-Oriented Dialogue
Huifang Du, Shuqin Li, Minghao Wu +3
Reinforcement learning (RL) is a powerful approach to enhance task-oriented dialogue (TOD) systems. However, existing RL methods tend to mainly focus on generation tasks, such as d…