20 citations · 32 across the 20 of their papers we have counts for
3 papers · 2 filters
Mitigating Forgetting Between Supervised and Reinforcement Learning Yields Stronger Reasoners
Xiangchi Yuan, Xiang Chen, Tong Yu +4
Large Language Models (LLMs) show strong reasoning abilities, often amplified by Chain-of-Thought (CoT) prompting and reinforcement learning (RL). Although RL algorithms can substa…
A Penalty Goes a Long Way: Measuring Lexical Diversity in Synthetic Texts Under Prompt-Influenced Length Variations
Vijeta Deshpande, Ishita Dasgupta, Uttaran Bhattacharya +3
Synthetic text generated by Large Language Models (LLMs) is increasingly used for further training and improvement of LLMs. Diversity is crucial for the effectiveness of synthetic…
Detecting Ambiguities to Guide Query Rewrite for Robust Conversations in Enterprise AI Assistants
Md Mehrab Tanjim, Xiang Chen, Victor S. Bursztyn +8
Multi-turn conversations with an Enterprise AI Assistant can be challenging due to conversational dependencies in questions, leading to ambiguities and errors. To address this, we…