Multi-turn simulations of grounded support narratives show LLMs reduce teaching-oriented responses as estimated user distress rises, with community context also shaping strategy choice.
The shrink- ing landscape of linguistic diversity in the age of large language models
3 Pith papers cite this work. Polarity classification is still indexing.
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Self-training restructures language by amplifying surface markers and collapsing deep syntax according to structural depth rather than frequency, as evidenced by correlations across multiple models and a human fine-tuning control.
AI writing distorts perceived writer personas across 29 dimensions in large experiments, and reward-model mitigation reduces but does not eliminate user preference for the AI.
citing papers explorer
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Auditing Support Strategies in LLMs through Grounded Multi-Turn Social Simulation
Multi-turn simulations of grounded support narratives show LLMs reduce teaching-oriented responses as estimated user distress rises, with community context also shaping strategy choice.
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Self-Training Doesn't Flatten Language -- It Restructures It: Surface Markers Amplify While Deep Syntax Dies
Self-training restructures language by amplifying surface markers and collapsing deep syntax according to structural depth rather than frequency, as evidenced by correlations across multiple models and a human fine-tuning control.