What if LLMs Ate Their Words: Causal History Effects in Multi-Turn Interaction
Overall, assistant-generated history has active but selective effects on multi-turn performance, motivating selective rather than uniform history management.
AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Overall, assistant-generated history has active but selective effects on multi-turn performance, motivating selective rather than uniform history management.
This work proposes MMPCBench, a comprehensive framework for evaluating MLLMs' proactive critique competence, which adopts a hierarchical evaluation protocol to measure models' error detection, diagnosis and resolution performance, and applies alignment-aware metrics to assess the coherence between internal reasoning an...
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