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Hande Dong

2 accepted papers

2026

Scheduling Your LLM Reinforcement Learning with Reasoning Trees

ICLR 2026poster

Using Reinforcement Learning with Verifiable Rewards (RLVR) to optimize Large Language Models (LLMs) can be conceptualized as progressively editing a query's 'Reasoning Tree'. This process involves exploring nodes (tokens) and dynamically modifying the model's policy at each node. When combined with…

Cited by 0SourcecodeScholar
2025

ReDit: Reward Dithering for Improved LLM Policy Optimization

NeurIPS 2025poster

DeepSeek-R1 has successfully enhanced Large Language Model (LLM) reasoning capabilities through its rule-based reward system. While it's a ''perfect'' reward system that effectively mitigates reward hacking, such reward functions are often discrete. Our experimental observations suggest that discret…

Cited by 0SourceScholar