Systematic study of inter-agent communication in LLM multi-agent systems shows reasoning and verification are critical for performance, with a new augmentation technique recovering 86.2% of failures.
Just put a human in the loop? investigating LLM-assisted annotation for subjective tasks
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Decomposing BP annotation into 14 skills shows 5 directly operable, 4 recoverable after re-annotation, and 5 structurally underspecified, with GPT-5.4 reaching 0.678 accuracy on retained skills and human-GPT difficulty correlating at r=0.881 at the skill level but near zero at instance and lexical-1
citing papers explorer
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What Do Agents Communicate? Characterizing Information Exchange in Multi-Agent Systems
Systematic study of inter-agent communication in LLM multi-agent systems shows reasoning and verification are critical for performance, with a new augmentation technique recovering 86.2% of failures.
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Exploring and Testing Skill-Based Behavioral Profile Annotation: Human Operability and LLM Feasibility under Schema-Guided Execution
Decomposing BP annotation into 14 skills shows 5 directly operable, 4 recoverable after re-annotation, and 5 structurally underspecified, with GPT-5.4 reaching 0.678 accuracy on retained skills and human-GPT difficulty correlating at r=0.881 at the skill level but near zero at instance and lexical-1