Papers by Jingyang Deng
Beyond Binary Preferences: Semi-Online Label-Free GRACE-KTO with Group-Wise Adaptive Calibration for High-Quality Long-Text Generation (2025.findings-emnlp)
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| Challenge: | Generating high-quality long-text remains challenging for Large Language Models (LLMs), as conventional supervised fine-tuning fails to ensure overall quality due to its teacher-forcing nature. |
| Approach: | They propose a semi-online framework that transforms KTO’s binary signals into dynamically calibrated intra-group rewards. |
| Outcome: | The proposed framework transforms binary signals into dynamically calibrated intra-group rewards. |