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cs.LG2024
Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs
Tianyu Guo, Druv Pai, Yu Bai +3
Practitioners have consistently observed three puzzling phenomena in transformer-based large language models (LLMs): attention sinks, value-state drains, and residual-state peaks,…
cs.LG2024★ 3 cited
Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning
Ruiqi Zhang, Licong Lin, Yu Bai +1
Large Language Models (LLMs) often memorize sensitive, private, or copyrighted data during pre-training. LLM unlearning aims to eliminate the influence of undesirable data from the…