Adversarial attacks on bandits aim to mislead a learner toward a target arm while keeping the attack cost small. Existing attacks typically achieve this by suppressing non-target arms. In practice, however, manipulation such as fake reviews often directly promotes the target item. We study this gap through bounded offl...
Qi-Run Zeng, Man-Hin Poon, Xiang-Xiang Dai et al.· 0 citations
RBwA, a memory-efficient and sample-efficient progressive sampling algorithm for IM-PC and a memory-efficient rounding scheme called BwARound for coverage maximization subroutines, which only requires storing one fractional vector and takes maximal feasible steps rather than tiny ε-increments, are proposed.
Qixin Zhang, Qirun Zeng, Hui Lu et al.· Proceedings of the 32nd ACM...· 0 citations
This work delineates LLM reasoning boundaries and presents a new paradigm for fine-grained capability assessment, which suggests that genuine reasoning is demonstrated only when a model follows logical rules despite conflicting prior knowledge.
Fangfei Yan, Jianbo Yao, Michael K. Chen et al.· Proceedings of the 32nd ACM...· 1 citation
This work delineates LLM reasoning boundaries and presents a new paradigm for fine-grained capability assessment, which suggests that genuine reasoning is demonstrated only when a model follows logical rules despite conflicting prior knowledge.
Fangfei Yan, Jianbo Yao, Michael K. Chen et al.· Proceedings of the 32nd ACM...· 1 citation
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
