The More Popular, The Harder to Forget: Adaptive Popularity for LLM Unlearning
- 类型:arxiv
- 标识:2608.14229
- 链接:https://arxiv.org/abs/2608.14229
- 主分类:engineering
- 形态:benchmark
- 被引:0
- 被引来源:Semantic Scholar
- S2被引:0
- 影响力被引:0
- TLDR:The AdaPop (Adaptive Popularity) method is proposed, which combines local token confidence with a per-fact popularity-dependent exponent derived from an external proxy, and automates the forget-retain balance via a dual-ascent controller that adjusts the retain penalty each epoch.
- 待LLM分类:否
- 标题中文:越流行越难遗忘:面向 LLM 遗忘的自适应流行度方法
- TLDR中文:提出 AdaPop(自适应流行度)方法,将局部 token 置信度与源自外部代理的逐事实流行度相关指数相结合,并通过双上升控制器在每个 epoch 调整 retain 惩罚来自动平衡遗忘与保留。
- 来源文件:
- /inbox/tom/_candidates/2026-08-20-agent-rag-longcontext-candidates.json
- /inbox/tom/_candidates/2026-08-21-agent-rag-longcontext-candidates.json
- [S2 enrich]