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Zhenyu Ding

2 accepted papers

2026

W2S-AlignTree: Weak-to-Strong Inference-Time Alignment for Large Language Models via Monte Carlo Tree Search

AAAI 2026technical

Large Language Models (LLMs) demonstrate impressive capabilities, yet their outputs often suffer from misalignment with human preferences due to the inadequacy of weak supervision and a lack of fine-grained control. Training-time alignment methods like Reinforcement Learning from Human Feedback (RLH

Cited by 0SourcePDFScholar
2025

Predictable Scale (Part II) --- Farseer: A Refined Scaling Law in LLMs

NeurIPS 2025spotlight

Training Large Language Models (LLMs) is prohibitively expensive, creating a critical scaling gap where insights from small-scale experiments often fail to transfer to resource-intensive production systems, thereby hindering efficient innovation. To bridge this, we introduce Farseer, a novel and ref…

Cited by 0SourcecodeScholar