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WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild
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Published as a conference paper at ICLR 2025 WILDBENCH: BENCHMARKING LLMS WITH CHALLENGING TASKS FROM REAL USERS IN THE WILD Bill Yuchen Lin♡♢ Yuntian Deng♡ Khyathi Chandu♡ Faeze Brahman♡ Abhilasha Ravichander♡ Valentina Pyatkin♡ Nouha Dziri♡ Ronan Le Bras♡ Yejin Choi♡♢ ♡Allen Institute for AI ♢University of Washin...
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NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models
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Published as a conference paper at ICLR 2025 NV-EMBED: IMPROVED TECHNIQUES FOR TRAINING LLMS AS GENERALIST EMBEDDING MODELS Chankyu Lee ∗ 1 Rajarshi Roy 1 Mengyao Xu 1 Jonathan Raiman 1 Mohammad Shoeybi 1 Bryan Catanzaro 1 Wei Ping ∗ 1 NVIDIA ABSTRACT Decoder-only large language model (LLM)-based embedding m...
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Strong Model Collapse
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"Published as a conference paper at ICLR 2025\n\nSTRONG MODEL COLLAPSE\n\nElvis Dohmatob1,2,3, Yunzh(...TRUNCATED)
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"From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning o(...TRUNCATED)
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"Published as a conference paper at ICLR 2025\n\nFROM ARTIFICIAL NEEDLES TO REAL HAYSTACKS: IM-\nPRO(...TRUNCATED)
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Large Language Models are Interpretable Learners
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"Published as a conference paper at ICLR 2025\n\nLARGE LANGUAGE MODELS ARE INTERPRETABLE\nLEARNERS\n(...TRUNCATED)
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Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents
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"Published as a conference paper at ICLR 2025\n\nNavigating the Digital World as Humans Do:\nUNIVERS(...TRUNCATED)
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Measuring Non-Adversarial Reproduction of Training Data in Large Language Models
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"Published as a conference paper at ICLR 2025\n\nMEASURING NON-ADVERSARIAL REPRODUCTION\nOF TRAINING(...TRUNCATED)
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More RLHF, More Trust? On The Impact of Preference Alignment On Trustworthiness
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"Published as a conference paper at ICLR 2025\n\nMORE RLHF, MORE TRUST? ON THE IMPACT OF PREF-\nEREN(...TRUNCATED)
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Training Language Models on Synthetic Edit Sequences Improves Code Synthesis
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"Published as a conference paper at ICLR 2025\n\nTRAINING LANGUAGE MODELS ON SYNTHETIC\nEDIT SEQUENC(...TRUNCATED)
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SWEb: A Large Web Dataset for the Scandinavian Languages
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"Published as a conference paper at ICLR 2025\n\nSWEB: A LARGE WEB DATASET FOR THE\nSCANDINAVIAN LAN(...TRUNCATED)
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