Papers by Yixin Bu
LUME: LLM Unlearning with Multitask Evaluations (2025.findings-emnlp)
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Anil Ramakrishna, Yixin Wan, Xiaomeng Jin, Kai-Wei Chang, Zhiqi Bu, Bhanukiran Vinzamuri, Volkan Cevher, Mingyi Hong, Rahul Gupta
| Challenge: | Unlearning aims to remove copyrighted, sensitive, or private content from large language models without a full retraining. |
| Approach: | They propose a multi-task unlearning benchmark LUME that unlearns short novels, biographies and public biographie . |
| Outcome: | The proposed benchmark unlearns short novels, biographies and public biographie . it also releases fine-tuned models with 1B and 7B parameter sizes as targets . |
DUD: Decoupled Update Dynamics for Reliable Uncertainty Quantification in Large Language Models (2026.acl-long)
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| Challenge: | Accurate Uncertainty Quantification (UQ) is critical for reliable deployment of Large Language Models (LLMs). |
| Approach: | They propose a framework that explicitly decouples FFN and Attention contributions via noise-induced causal interventions to capture model's internal fragility. |
| Outcome: | The proposed framework outperforms state-of-the-art baselines in both uncertainty estimation and calibration while exhibiting superior cross-dataset generalization. |