Large-scale analysis of wild LLM chat logs finds that user interaction patterns stabilize quickly after initial use and correlate with long-term outcomes like retention, creating an agency paradox of limited exploration in unconstrained systems.
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CanvasConvo presents a spatial canvas interface for branching LLM conversations, evaluated in a 5-7 day field study with 24 participants that found support for exploratory workflows.
VIDEE introduces a human-in-the-loop system using Monte-Carlo Tree Search for task decomposition, executable pipeline generation, and LLM-based evaluation with visualizations to support non-expert text analytics.
Binary groundedness judgments in AI evaluations should be replaced by a reader-centered taxonomy of support relations that distinguishes syntactic and interpretive moves between generated statements and source documents.
citing papers explorer
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Priming, Path-dependence, and Plasticity: Understanding the molding of user-LLM interaction and its implications from (many) chat logs in the wild
Large-scale analysis of wild LLM chat logs finds that user interaction patterns stabilize quickly after initial use and correlate with long-term outcomes like retention, creating an agency paradox of limited exploration in unconstrained systems.
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Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas
CanvasConvo presents a spatial canvas interface for branching LLM conversations, evaluated in a 5-7 day field study with 24 participants that found support for exploratory workflows.
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VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents
VIDEE introduces a human-in-the-loop system using Monte-Carlo Tree Search for task decomposition, executable pipeline generation, and LLM-based evaluation with visualizations to support non-expert text analytics.
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From Binary Groundedness to Support Relations: Towards a Reader-Centred Taxonomy for Comprehension of AI Output
Binary groundedness judgments in AI evaluations should be replaced by a reader-centered taxonomy of support relations that distinguishes syntactic and interpretive moves between generated statements and source documents.