Long-term agent memory requires recovering answer-relevant evidence dispersed across turns and sessions. Existing systems increasingly use structured memories and adaptive retrieval, yet often pass retrieved or expanded units directly to the reader, coupling memory addressing with evidence presentation and leaving the...
Shang-Ze Li, Yan-Yu Yao, De-Rong Xu et al.· 0 citations
EviDep is presented, a multimodal evidential regression framework that integrates multi-scale temporal modeling and shared--private representation learning for uncertainty-aware depression estimation and shows competitive prediction accuracy, while both uncertainty estimates generally increase under controlled feature...
Fang-Yuan Liu, Si-Rui Zhao, Yang-Song Zhang et al.· 0 citations
This work proposes ATLAS, a dual-horizon diagnostic evaluation framework for industrial tool-use agents that instantiates LLM judge interfaces as executable signals with explicit evidence scopes and decision boundaries, and evaluates ATLAS on Meituan Xiaotuan production traffic.
Wei Chen, Pei-Lun Zhou, Zhao-Yu Hu et al.· 0 citations
This work proposes SAFE-G, a Structure-Aware Faithful Evidence-guided Generation framework, which enables precise evidence localization and trustworthy reasoning and introduces a reinforcement learning strategy with an evidence-grounded reward that assigns credit to correct answers only when the selected evidence is co...
Long Shu, Shuo-Chen Liu, Wei Chen et al.· 0 citations
Progressive Tree Drafting (PTD) is proposed, which employs a structured, guided parallel drafting strategy to harness the model's parallel potential by coupling a progressive tree structure with a stepwise pruning mechanism and actively guides the LLM to explore multiple semantic paths in a single forward pass.
