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cs.HC2026
How Anthropomorphic Attitudes Toward Agents Divide User Behavior, and How Design Should Change
Tingyu Cao, Yan Tang, Keer Hu +6
Studies of conversational agents rely on interviews, surveys, lab tasks, or taxonomies. Whether anthropomorphic naming splits those patterns, and whether replies should change, lac…
cs.CL2026
Multi-level context Modeling for consistent expert selection in Mixture-of-Experts
Shuhan Huang, Naifan Zhang, Yuanbo Tang +2
Mixture-of-Experts (MoE) enables efficient scaling of Transformer models by routing tokens to a small subset of experts. However, existing routers typically condition expert select…