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cs.AI2026

SymFold: Synergizing Evolutionary and Structural Priors for Accurate Protein Inverse Folding

Handong Wang, Jiaxin Qi, Baisheng Lai +1

Protein inverse folding aims to recover amino acid sequences for a given 3D protein structure, underpinning broad applications such as enzyme engineering and drug discovery.Current…

cs.AI2026

Experience is the Best Teacher: Motivating Effective Exploration in Reinforcement Learning for LLMs

Wenjian Zhang, Kongcheng Zhang, Jiaxin Qi +2

Reinforcement Learning (RL) with rubric-based rewards has recently shown remarkable progress in enhancing general reasoning capabilities of Large Language Models (LLMs), yet still…

cs.AI2025

Replay Failures as Successes: Sample-Efficient Reinforcement Learning for Instruction Following

Kongcheng Zhang, Qi Yao, Shunyu Liu +7

Reinforcement Learning (RL) has shown promise for aligning Large Language Models (LLMs) to follow instructions with various constraints. Despite the encouraging results, RL improve…

cs.AI2025

Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM Reasoning

Kongcheng Zhang, Qi Yao, Shunyu Liu +5

Recent advances of Reinforcement Learning (RL) have highlighted its potential in complex reasoning tasks, yet effective training often relies on external supervision, which limits…

cs.AI2025

Reasoning with Reinforced Functional Token Tuning

Kongcheng Zhang, Qi Yao, Baisheng Lai +5

In this work, we propose Reinforced Functional Token Tuning (RFTT), a novel reinforced fine-tuning framework that empowers Large Language Models (LLMs) with self-play learn-to-reas…