Internal-state probes enable truthfulness prediction before a large language model generates an answer. When detectors change both the layers they read and the rules used to combine them, the source of improved prediction becomes difficult to identify. We separate these choices and find that retaining more layers impro...
Zhi-Hao Guo, Zong-Han Wu, Huan Huo et al.· 0 citations
CorVer (Corpus Verify) is a lightweight training-time approach to process supervision that derives sentence-level rewards from corpus co-occurrence statistics and outperforms the unmodified models in all standard factual-QA settings.
Shi-Chen Fan, Hao-Chang Hao, De-Hai Min et al.· 5 citations
Long-term conversational agents rely on personal memory to maintain coherence and personalization, yet practical systems must operate under context budgets and cope with evolving or contradictory user information. We frame persona memory as a retrieval problem over a growing memory store, and propose REMAP, a reflectio...
Qingyang Xu, Xiao Liu, Zhou Fang et al.· Annual International ACM SIG...· 0 citations
Evidence of cross-lingual efficacy of code-based LLMs for Chinese QA tasks, further enhanced through Code Llama-M's expanded Chinese vocabulary is found, and successful application of the fine-tuned LLM in a live assistant system, enhancing user experience is demonstrated.
Jiajun Yu, Linghan Zheng, Hui Liu et al.· Annual International ACM SIG...· 0 citations
HalluTracer is introduced, a detection framework that reads and aggregates truthfulness evidence across every layer of the forward pass before the model emits any answer token, recasts hallucination detection from a layer-selection problem into a depth-aggregation problem governed by the geometric sparsity of the truth...
Zhi-Hao Guo, Zong-Han Wu, Huan Huo et al.· 0 citations
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