Papers by Runpeng Yu
CoT-Valve: Length-Compressible Chain-of-Thought Tuning (2025.acl-long)
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| Challenge: | Wei et al., 2022) have developed a powerful method for enhancing the reasoning capabilities of large language models. |
| Approach: | They propose to use a tuning and inference strategy to control the length of reasoning chains by a parameter space direction to control their length. |
| Outcome: | The proposed method reduces reasoning chains on GSM8K from 741 to 225 tokens with a minor performance drop (95.07% to 94.92%) and on AIME from 6827 to 4629 tokens, with only one additional incorrect answer. |
R1-RE: Cross-Domain Relation Extraction with RLVR (2026.acl-long)
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| Challenge: | Relation extraction (RE) is a core task in natural language processing. |
| Approach: | They propose a supervised learning task for relation extraction (RE) based on annotation guidelines. |
| Outcome: | The proposed model achieves an average OOD accuracy of 70%, on par with leading proprietary models such as GPT-4o. |