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https://arxiv.org/html/2407.03956v3
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https://arxiv.org/html/2608.00785v1
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Abstract
Content discovery systems depend on relevance judgment for search quality evaluation, but human annotation faces inter-annotator disagreement and scaling costs
https://arxiv.org/html/2508.19205v1
com/microsoft/VibeVoice
Hugging Face: microsoft/VibeVoice
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https://arxiv.org/html/2508.16279v1
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https://arxiv.org/html/2407.04503v4
fr Inria, Flowers team, Université de Bordeaux, France Grgur Kovač Inria, Flowers team, Université de Bordeaux, France Corentin Léger Inria, Flowers team, Université de Bordeaux, France Cédric Colas Inria, Flowers team, Université de Bordeaux, France MIT, Computational Cognitive Science Lab, Cambridge, MA, USA
https://arxiv.org/html/2506.01844v1
2 Related work
Vision-language models (VLMs).
Vision-language-action models (VLAs).
3 SmolVLA: small, efficient and capable
Overview.
3.1 Model architecture
Vision-language model (VLM).
State, action, and feature projectors.
Visual
https://arxiv.org/list/cs.SE/new
Through an analysis of 1,966 open source projects, 1,355 Github issues, 444 CVE reports, and 361 StackOverflow posts, we systematically map the feature support and real-world usage of globs across six common ecosystems that utilize globs