Large language models have achieved significant progress in event forecasting, yet their probability outputs exhibit systematic calibration bias that varies heterogeneously across different domains and question types, undermining the trustworthiness of probabilistic outputs for decision-making under uncertainty. Howeve...
Wen-Jin Liu, Chen-Xi Wang, Yue Lu et al.· 0 citations
Experimental results show that CataOPD outperforms current baselines, extends independent student reasoning to still-unrecovered problems, and improves out-of-distribution generalization under catalyst-free inference.
Wen-Jin Liu, Chen-Xi Wang, Jia-Pu Wang et al.· 0 citations
MMDynOpt-Agent is a lightweight multimodal agent that models the dynamic optimization of multimodal reasoning as a Markov decision process via end-to-end reinforcement learning, designed to reduce the cost of multimodal reasoning.
Wen-Jin Liu, Hao-Ran Luo, Fa-Yuan Ke et al.· 0 citations
TIEM, a timestamp-gated framework with three coordinated components: an Event-Evidence Hypergraph (EEH) for timestamp-filtered multi-tier retrieval; a Case-based Skill Memory (CSM) for source-tagged temporal skills; and Heterogeneous Evidence-Experience Fusion Reasoning (HEFR) for evidence-experience fusion and predict...
Wen-Jin Liu, Shengjie Pang, Chen-Xi Wang et al.· 1 citation
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