ExplainableML
eml-munich.bsky.social
Institute for Explainable Machine Learning at @www.helmholtz-munich.de and Interpretable and Reliable Machine Learning group at Technical University of Munich and part of @munichcenterml.bsky.social
👤 Joined on 20 November 2024
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- 20 Kas 2024, 13:12
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Happy to share that we have 8 papers accepted to #ICML2026! 🎉 Most of the authors will be traveling to Seoul, Korea 🇰🇷 — feel free to reach out and chat with them if you’re interested in the work. See the full thread below for our papers 👇
Show PostWe also have a great lineup of workshop presentations at #ICML2026! Most of our authors will be there too—come chat with them if you're interested. 👇 Details in the thread:
Show PostOur EML members are heading for Rio🇧🇷 for #ICLR2026! 🌴We’re excited to share our latest research — three poster presentations. Check out the thread below and come say hi to our authors
Show Post🥳Our proposal "TACO-VLM: Tackling challenges in large-scale multimodal learning" was granted 1.5M GPU-h on JUPITER @fz-juelich.de, Europe's first exascale supercomputer with ~24k NVIDIA GH200 GPUs. With JUPITER's support, we hope to push large-scale multimodal learning further.
Show PostResults. GenEval: SDXL 0.55→0.61 (notable gains in two objects, counting, color attribution). T2I-CompBench: broad boosts (esp. Color/Texture). DPG-Bench (SDXL): DSG 74.65→79.26, Q-Align 0.72→0.81; user study: RankDPO wins over SDXL & DPO-SDXL.
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