AI evaluation pipelines often produce conflicting judgments rather than clean labels. In pairwise LLM evaluation, this conflict is especially visible: disagreement can arise from ambiguous items, underspecified rubrics, heterogeneous or unstable human raters, or an LLM judge whose verdict changes when the response orde...
Jia-Hao Zhang, Peng-Bin Feng, Chun-Lei Meng et al.· 0 citations
Adaptive Hierarchical Representation Alliance (AHRA), a hierarchical shared--private expert framework, is proposed, which consistently improves over strong baselines and remains robust under noisy and missing-modality settings.
Chun-Lei Meng, Peng-Bin Feng, Jacqueline J. Pang et al.· 2 citations
The proposed MRCF contains a Reliability-Aware Branch that estimates sample-specific modality reliability from intramodal quality cues and cross-modal semantic consistency, a Reliability-Guided Interaction Branch that uses the estimated scores to modulate cross-modal information flow, and a Reliability-Calibrated Fusio...
Chun-Lei Meng, Jacqueline J. Pang, Peng-Bin Feng et al.· 1 citation
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