Developers using AI assistants exhibit more stable emotions and greater focus on code creation, evaluation, and verification, captured in a new four-dimensional S-IASE model from retrospective labeling of screen recordings, surveys, and interviews.
Personagen: A tool for generating personas from user feedback
6 Pith papers cite this work. Polarity classification is still indexing.
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PerGent, an agentic critique-refinement system for persona generation, reaches 96.9% expert approval in an industrial evaluation at Kinaxis and reproduces more pre-LLM expert content than single-shot baselines.
LLM approaches ExArch and ArTEMiS reach F1 scores of 0.86 and 0.81 for architecture entity recognition and traceability, matching or approaching baselines that require manual models.
LENS uses LLMs to extract explicit requirements (84.4% F1) and infer latent requirements (75% rated useful by experts) from 12 cybersecurity stakeholder interview transcripts.
A research roadmap analyzing the current state of search-based software engineering with foundation models, outlining challenges and directions across three integration aspects.
Researchers clustered 41,300 Moltbook posts from AI agents with k-means and retrieval-augmented generation to produce validated personas that represent behavioral diversity in agent populations.
citing papers explorer
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How Do Developers Interact with AI? An Exploratory Study on Modeling Developer Programming Behavior
Developers using AI assistants exhibit more stable emotions and greater focus on code creation, evaluation, and verification, captured in a new four-dimensional S-IASE model from retrospective labeling of screen recordings, surveys, and interviews.
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Agentic Persona Generation with Critique-Refinement: An Industrial Evaluation
PerGent, an agentic critique-refinement system for persona generation, reaches 96.9% expert approval in an industrial evaluation at Kinaxis and reproduces more pre-LLM expert content than single-shot baselines.
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LLM-Based Discovery of Latent Requirements from Stakeholder Conversations: Preliminary Results from Industry
LENS uses LLMs to extract explicit requirements (84.4% F1) and infer latent requirements (75% rated useful by experts) from 12 cybersecurity stakeholder interview transcripts.
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How to Model AI Agents as Personas?: Applying the Persona Ecosystem Playground to 41,300 Posts on Moltbook for Behavioral Insights
Researchers clustered 41,300 Moltbook posts from AI agents with k-means and retrieval-augmented generation to produce validated personas that represent behavioral diversity in agent populations.