PERSUASIONTRACE introduces a Bayesian-network simulated target for multi-turn persuasion that matches human belief dynamics (81 vs 80) better than LLM baselines (64) and enables process-level evaluation.
Persuasiveness of Generated Free-Text Rationales in Subjective Decisions: A Case Study on Pairwise Argument Ranking
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Fine-tuning a Gemma model on a mix of seed, generated, and general instruction data (ArgInstruct) improves zero-shot performance on unseen computational argumentation tasks while preserving general NLP performance.
EvalAI providing pro/con arguments improves provision-level accuracy and reduces misclassification distance in DSA illegal content reporting under AI error conditions versus conventional XAI.
citing papers explorer
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A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing
PERSUASIONTRACE introduces a Bayesian-network simulated target for multi-turn persuasion that matches human belief dynamics (81 vs 80) better than LLM baselines (64) and enables process-level evaluation.
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ArgInstruct: Specialized Instruction Fine-Tuning for Computational Argumentation
Fine-tuning a Gemma model on a mix of seed, generated, and general instruction data (ArgInstruct) improves zero-shot performance on unseen computational argumentation tasks while preserving general NLP performance.
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AI at the Front Lines of Platform Governance: Using LLMs to Support Illegal Content Reporting under the Digital Services Act
EvalAI providing pro/con arguments improves provision-level accuracy and reduces misclassification distance in DSA illegal content reporting under AI error conditions versus conventional XAI.