3 citations · 4 across the 11 of their papers we have counts for
4 papers · 1 filter
CARE-RL: Capability-Aware Reinforcement Learning for Mitigating Cross-Domain Conflicts
Rui Zhang, Xinle Wu, Yao Lu
Reinforcement learning (RL) with verifiable rewards has achieved strong progress in reasoning-oriented LLMs, but extending it to multi-domain RL remains challenging due to reward u…
Planner-Centric Reinforcement Learning for Deep Research with Structure-Aware Reward
Mustafa Anis Hussain, Xinle Wu, Yao Lu
Deep research tasks require LLMs to plan what to investigate, retrieve evidence, and synthesize long-form answers across multiple branches of inquiry. Existing training paradigms e…
Automatic Configuration of LLM Post-Training Pipelines
Channe Chwa, Xinle Wu, Yao Lu
LLM post-training pipelines that combine supervised fine-tuning and reinforcement learning are difficult to configure under realistic compute budgets: the configuration space is hi…
Towards Autonomous Memory Agents
Xinle Wu, Rui Zhang, Mustafa Anis Hussain +1
Recent memory agents improve LLMs by extracting experiences and conversation history into an external storage. This enables low-overhead context assembly and online memory update w…