ProactBench measures LLM conversational proactivity in three phases using 198 multi-agent dialogues and finds recovery behavior hard to predict from existing benchmarks.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Frontier LLMs miss dangerous actions in long coding agent transcripts 2-30 times more often after hundreds of thousands of benign tokens.
A deliberative council of Gemini agents using absence-based clinical rules achieves 0.382 F1 without fine-tuning and second place overall at 0.406 F1 on defense mechanism classification, with minority-class overrides adding 2.4pp.
citing papers explorer
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ProactBench: Beyond What The User Asked For
ProactBench measures LLM conversational proactivity in three phases using 198 multi-agent dialogues and finds recovery behavior hard to predict from existing benchmarks.
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Classifier Context Rot: Monitor Performance Degrades with Context Length
Frontier LLMs miss dangerous actions in long coding agent transcripts 2-30 times more often after hundreds of thousands of benign tokens.
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UTS at PsyDefDetect: Multi-Agent Councils and Absence-Based Reasoning for Defense Mechanism Classification
A deliberative council of Gemini agents using absence-based clinical rules achieves 0.382 F1 without fine-tuning and second place overall at 0.406 F1 on defense mechanism classification, with minority-class overrides adding 2.4pp.