A Gaussian information-gain metric in embedding space quantifies semantic progress in dialogues via uncertainty reduction and shows competitive agreement with human judgments on MT-Bench and UltraFeedback.
An LLM feature-based framework for dialogue constructiveness assessment
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
An LM-guided counterfactual pipeline recommends minimal ordinal changes to communication features like tone and actionability, yielding a mean +6.41% gain in predicted positive feedback under independent auditor models.
citing papers explorer
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Measuring Semantic Progress in Multi-turn Dialogue via Information Gain
A Gaussian information-gain metric in embedding space quantifies semantic progress in dialogues via uncertainty reduction and shows competitive agreement with human judgments on MT-Bench and UltraFeedback.
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Improving Medical Communication using Rubric-Guided Counterfactual Recommendations
An LM-guided counterfactual pipeline recommends minimal ordinal changes to communication features like tone and actionability, yielding a mean +6.41% gain in predicted positive feedback under independent auditor models.