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If an LLM Were a Character, Would It Know Its Own Story? Evaluating Lifelong Learning in LLMs

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学术前沿 5.0 分 — 中等质量:常规学术论文,有适度参考价值
原文: cs.AI updates on arXiv.org

评分 5.0 · 来源:cs.AI updates on arXiv.org · 发布于 2026-04-14

评分依据:中等质量:常规学术论文,有适度参考价值

If an LLM Were a Character, Would It Know Its Own Story? Evaluating Lifelong Learning in LLMs

arXiv:2503.23514v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can carry out human-like dialogue, but unlike humans, they are stateless due to the superposition property. However, during multi-turn, multi-agent interactions, LLMs begin to exhibit consistent, character-like behaviors, hinting at a form of emergent lifelong learning. Despite this, existing benchmarks often fail to capture these dynamics, primarily focusing on static, open-ended evaluations. To address this…