The Pensieve Paradigm: Stateful Language Models Mastering Their Own Context
Xiaoyuan Liu · Tian Liang · Dongyang Ma · Deyu Zhou · Haitao Mi · Pinjia He · Yan Wang
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Xiaoyuan Liu · Tian Liang · Dongyang Ma · Deyu Zhou · Haitao Mi · Pinjia He · Yan Wang
Sihang Zhao · Kangrui Yu · Youliang Yuan · Pinjia He · Hongyi Wen
Large Language Models (LLMs) have been widely explored in educational scenarios. We identify a critical vulnerability in current educational LLMs, pedagogical jailbreaks, where students use answer-inducing prompts to elicit solutions rather than scaffolded instructions. To enable systematic study...
Youliang Yuan · Qiuyang Mang · Jingbang Chen · Hong Wan · Xiaoyuan Liu · Junjielong Xu · Jen-Tse Huang · Wenxuan Wang · Wenxiang Jiao · Pinjia He
In this paper, we observe that current models are susceptible to reward hacking, leading to a substantial overestimation of a model’s reasoning ability. This is evidenced by a high incidence of “false positives”—solutions that reach the correct answer through an unsound process.Through a systemat...
Jianbo Yu · Yixuan Li · Hai Xu · Kang Xu · Junjielong Xu · Zhijing Li · Pinjia He · Wanyuan Wang