Analysis of 14,727 security and privacy prompts from WildChat finds commercial LLMs give higher-quality responses than open-weight models but can produce inconsistent answers across repeated queries.
Large language models reduce public knowledge sharing on online Q & A platforms
6 Pith papers cite this work, alongside 27 external citations. Polarity classification is still indexing.
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27
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representative citing papers
AI Overviews boost Reddit engagement in safe communities by 12% but conversational AI Mode reverses gains for experience-based content.
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.
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.
ChatGPT retains 94.8% of information-seeking occasions without outbound referrals and wider access displaces 9.4% of traditional search queries, with losses concentrated on informational and ad-supported destinations.
citing papers explorer
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Security and Privacy Prompts in the Wild: What Users Ask LLMs and How LLMs Respond
Analysis of 14,727 security and privacy prompts from WildChat finds commercial LLMs give higher-quality responses than open-weight models but can produce inconsistent answers across repeated queries.
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The Impact of AI Search on the Online Content Ecosystem: Evidence from Google and Reddit
AI Overviews boost Reddit engagement in safe communities by 12% but conversational AI Mode reverses gains for experience-based content.
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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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Answering Without Referring: How AI Search Rewrites the Web's Economic Bargain
ChatGPT retains 94.8% of information-seeking occasions without outbound referrals and wider access displaces 9.4% of traditional search queries, with losses concentrated on informational and ad-supported destinations.