ConSearcher generates query-based member personas in an LLM conversational tool, yielding higher information-seeking outcomes and engagement than baselines in a 27-person study, with noted risks of over-personalization.
Large language models reduce public knowledge sharing on online Q & A platforms
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A new sequential interaction framework lets LLMs propose questions to forums, with simulations on real Stack Exchange data showing players can reach roughly half the utility of an ideal full-information scenario despite incentive misalignment.
A study of seven LLMs finds that realistic prompt variations such as one-character misspellings trigger library hallucinations in up to 26% of cases, fabricated names in up to 99%, and time-based prompts in up to 85%, and introduces LibHalluBench for evaluation.
Difference-in-differences analysis exploiting Google's SFW/NSFW moderation policy finds AI Overviews increase Reddit daily comments by 12.0% and commenting users by 12.3% in SFW communities, concentrated in experience-based content, with gains largely eliminated by subsequent AI Mode rollout.
citing papers explorer
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ConSearcher: Supporting Conversational Information Seeking in Online Communities with Member Personas
ConSearcher generates query-based member personas in an LLM conversational tool, yielding higher information-seeking outcomes and engagement than baselines in a 27-person study, with noted risks of over-personalization.
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From Competition to Collaboration: Designing Sustainable Mechanisms Between LLMs and Online Forums
A new sequential interaction framework lets LLMs propose questions to forums, with simulations on real Stack Exchange data showing players can reach roughly half the utility of an ideal full-information scenario despite incentive misalignment.
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Library Hallucinations in LLM-Generated Code: A Risk Analysis Grounded in Developer Queries
A study of seven LLMs finds that realistic prompt variations such as one-character misspellings trigger library hallucinations in up to 26% of cases, fabricated names in up to 99%, and time-based prompts in up to 85%, and introduces LibHalluBench for evaluation.
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The Impact of AI Search on the Online Content Ecosystem: Evidence from Google and Reddit
Difference-in-differences analysis exploiting Google's SFW/NSFW moderation policy finds AI Overviews increase Reddit daily comments by 12.0% and commenting users by 12.3% in SFW communities, concentrated in experience-based content, with gains largely eliminated by subsequent AI Mode rollout.