Diane Larlus

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Directory member with public evidence across AI research, Vision & synthetic media, Compute & infrastructure.

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Computer Vision & Machine Learning researcher at NAVER LABS europe she/her - https://dlarlus.github.io/

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We just released our #ECCV2026 paper on Model Merging for Computer Vision 🎓 arxiv.org/abs/2604.12935 Joint work w @pdejorge.bsky.social Cesar De Souza @bjoernmichele.bsky.social @mbsariyildiz.bsky.social @weinzaepfelp.bsky.social Florent Perronnin & @skamalas.bsky.social See P…

Task Alignment: A Simple Proxy for Practical Model Merging Across Diverse Vision Tasks arxiv.org
AI Weekly's analysis
  • A NAVER Labs Europe paper accepted at ECCV 2026 introduces a 'task alignment proxy' for selecting model-merging hyperparameters without training the decoder for each candidate.
  • The method targets heterogeneous vision tasks with trainable decoders, moving beyond the CLIP image classification setup that dominated prior model merging work.
  • The authors claim the proxy speeds up hyperparameter selection by orders of magnitude while retaining downstream performance.
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