SPARK improves LLM-based test code fault localization by retrieving similar past faults and selectively annotating suspicious lines in new failing tests.
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WhiteTesseract deploys XR-based diminished reality and LLM dialogue in a Monet exhibition, raising average viewing time from 35.3 to 98.3 seconds and shifting 60% of 529 interactions toward analytical and emotional queries.
Medium personality expression in LLM agents yields the most positive user perceptions in goal-oriented tasks, further improved by trait alignment.
Experts can deliver helpful advice on over half of short 'nanoquestions' about feature-rich software in under one minute.
citing papers explorer
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Similar Pattern Annotation via Retrieval Knowledge for LLM-Based Test Code Fault Localization
SPARK improves LLM-based test code fault localization by retrieving similar past faults and selectively annotating suspicious lines in new failing tests.
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WhiteTesseract: Reframing the Interpretation of Cultural Heritage through XR and Conversational AI
WhiteTesseract deploys XR-based diminished reality and LLM dialogue in a Monet exhibition, raising average viewing time from 35.3 to 98.3 seconds and shifting 60% of 529 interactions toward analytical and emotional queries.
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Vibe Check: Understanding the Effects of LLM-Based Conversational Agents' Personality and Alignment on User Perceptions in Goal-Oriented Tasks
Medium personality expression in LLM agents yields the most positive user perceptions in goal-oriented tasks, further improved by trait alignment.
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Nanomentoring: Investigating How Quickly People Can Help People Learn Feature-Rich Software
Experts can deliver helpful advice on over half of short 'nanoquestions' about feature-rich software in under one minute.