AgenticFlict is a public dataset of 29K+ textual merge conflicts from AI agent PRs, collected via merge simulation on 107K processed PRs and showing a 27.67% conflict rate with variation across agents.
InInternational Working Conference on Source Code Analysis and Manipulation (SCAM)
3 Pith papers cite this work. Polarity classification is still indexing.
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A survey of 419 practitioners shows strong reliance on reusable GitHub Actions for core CI/CD tasks but limited adoption of reusable workflows, with copy-pasting remaining common due to versioning and trust issues.
A systematic literature review of explainability in multimodal attention models finds most studies focus on vision-language tasks with attention-based explanations, but evaluation methods lack consistency and modality-specific considerations.
citing papers explorer
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AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub
AgenticFlict is a public dataset of 29K+ textual merge conflicts from AI agent PRs, collected via merge simulation on 107K processed PRs and showing a 27.67% conflict rate with variation across agents.
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Automation and Reuse Practices in GitHub Actions Workflows: A Practitioner's Perspective
A survey of 419 practitioners shows strong reliance on reusable GitHub Actions for core CI/CD tasks but limited adoption of reusable workflows, with copy-pasting remaining common due to versioning and trust issues.
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Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Models
A systematic literature review of explainability in multimodal attention models finds most studies focus on vision-language tasks with attention-based explanations, but evaluation methods lack consistency and modality-specific considerations.