As LLMs increasingly act as delegated agents, they are expected to protect principals'interests when interacting with external parties. Standard alignment objectives, such as helpfulness, harmlessness, and honesty, do not specify how agents should protect principals'strategic interests under delegation. We formalize Ag...
Zi-Meng Huang, Shi-Lei Chen, Jia-Tong Zhao et al.· 1 citation
Large language models (LLMs) can sometimes report perturbations to their internal activations---even when the input provides no evidence that an intervention occurred. How do models detect and localize such internal changes? We study this question using a controlled task that keeps the input text fixed. We either injec...
Jia-Hong Zou, Xiang-Kun Sun, Ling-Kai Kong et al.· 0 citations
Experiments across diverse upstream models show that PILA consistently improves ad effectiveness while preserving response quality, highlighting its promise as a practical solution for LLM-native advertising.
GraceKV is proposed, a global approach for the allocation of resolution and coverage in KV cache compression, and the compression process is formulated as a global resource allocation problem under a fixed cache budget to validate the effectiveness of global budget allocation in coordinating information coverage and lo...
This work constructs the missing supervision through a psychologically grounded agent simulation framework, and distil it into a parameter-efficient evaluator that predicts click-through intent, together with the three companion dimensions of ad quality, as smooth, differentiable estimates.
John L. Turner-Smith, Zimeng Huang, Yuhan Fu et al.· arXiv.org· 0 citations
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