4 citations · 4 across the 3 of their papers we have counts for
4 papers
Giving Credit Where It's Due: Redundancy-Aware Learning for Efficient Reasoning
Yuqing Zhou, Hong Wang, Manqing Mao +8
Large reasoning models can produce correct yet unnecessarily long reasoning traces. Existing methods improve reasoning efficiency with trajectory-level objectives or local token- a…
Local Edits, Global Ripples: Replay-Informed Policy Adaptation for Workflow Synthesis
Manqing Mao, Hong Wang, Samson Koelle +8
Prompt-policy editing offers a practical way to improve agents that synthesize executable workflows without updating the underlying model. However, persistent prompt editing has tw…
Optimizing What Policies Learn From: Recoverability-aware Rollout Intervention Learning
Zheyuan Zhang, Manqing Mao, Hong Wang +8
Critic-free group-based reinforcement learning has become a scalable approach for post-training large language models. However, most existing methods allocate the same number of ro…
Multi-User Chat Assistant (MUCA): a Framework Using LLMs to Facilitate Group Conversations
Manqing Mao, Paishun Ting, Yijian Xiang +3
Recent advancements in large language models (LLMs) have provided a new avenue for chatbot development. Most existing research, however, has primarily centered on single-user chatb…