Overview
The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.
Sponsorship Details
Platinum
Booth #J08
Accepted publications
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NAACL 2025 Workshop on TrustNLP, ICLR 20252025
Workshops
ICLR 2025 Workshop on Sparsity in LLMs
April 27
ICLR 2025 Workshop on Foundation Models in the Wild
April 27
In the era of AI-driven transformations, foundation models (FMs) have become pivotal in various applications, from natural language processing to computer vision. These models, with their immense capabilities, reshape the future of scientific research and the broader human society, but also introduce challenges in their in-the-wild deployments. The Workshop on FMs in the wild delves into the urgent need for these models to be useful when deployed in our societies. The significance of this topic cannot be overstated, as the real-world implications of these models impact everything from daily information access to critical decision-making in fields like medicine and finance. Stakeholders, from developers to end-users, care deeply about this because the successful integration of FMs into in-the-wild frameworks necessitates a careful consideration of many properties, including adaptivity, reliability, efficiency, and reasoning ability.
Website: https://fm-wild-community.github.io/
Website: https://fm-wild-community.github.io/
Latest news
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April 11, 2025Novel three-pronged approach combines claim-level evaluations, chain-of-thought reasoning, and classification of hallucination error types.
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April 10, 2025New tool lets customers build, train, and deploy machine learning models using only natural language.
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March 27, 2025Training separate models on different datasets and then merging them reduces computational costs by as much as 91%.