Papers by Yeeho Song
TLPO: Token-Level Policy Optimization for Mitigating Language Confusion in Large Language Models (2026.acl-long)
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| Challenge: | Prior mitigation approaches that optimize entire responses operate at the level of entire responses and can lead to unintended degradation of general model capabilities. |
| Approach: | They propose a fine-tuning framework to mitigate erroneous outputs by localizing and updating the policy at a granular level. |
| Outcome: | The proposed framework outperforms baselines on multiple multilingual LLMs across diverse languages while preserving task accuracy. |