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Jiabao Pan

2 accepted papers

2026

De-attribute to Forget for LLM Unlearning

ICML 2026poster

The rapid development of large language models (LLMs) has raised concerns regarding the inclusion of private or inappropriate data during training, which has led to growing interest in LLM unlearning. Many existing LLM unlearning approaches rely on prediction loss-based optimizations, such as maximi…

Cited by 0SourceScholar
2024

DynaThink: Fast or Slow? A Dynamic Decision-Making Framework for Large Language Models

EMNLP 2024main

Large language models (LLMs) have demonstrated emergent capabilities across diverse reasoning tasks via popular Chains-of-Thought (COT) prompting. However, such a simple and fast COT approach often encounters limitations in dealing with complicated problems, while a thorough method, which considers…