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41 Results
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Poster
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Fri 16:30 |
Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data Alexander Havrilla · Wenjing Liao |
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Poster
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Thu 11:00 |
Dimension-free deterministic equivalents and scaling laws for random feature regression Leonardo Defilippis · Bruno Loureiro · Theodor Misiakiewicz |
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Poster
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Thu 11:00 |
Reranking Laws for Language Generation: A Communication-Theoretic Perspective António Farinhas · Haau-Sing Li · André Martins |
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Poster
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Wed 16:30 |
D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models Haoran Que · Jiaheng Liu · Ge Zhang · Chenchen Zhang · Xingwei Qu · Yinghao Ma · Feiyu Duan · ZhiqiBai zhiqi · JiakaiWang · Yuanxing Zhang · Xu Tan · Jie Fu · Jiamang Wang · Lin Qu · Wenbo Su · Bo Zheng |
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Workshop
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Principles of Animal Cognition for LLM Evaluations: A Case Study on Transitive Inference Sunayana Rane · Cyrus Kirkman · Amanda Royka · Graham Todd · Ryan Law · Jacob Foster · Erica Cartmill |
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Workshop
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Sun 11:20 |
Distributional Scaling Laws for Emergent Capabilities Rosie Zhao · Naomi Saphra · Sham Kakade |
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Workshop
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Loss-to-Loss Prediction: Language model scaling laws across datasets David Brandfonbrener · Nikhil Anand · Nikhil Vyas · Eran Malach · Sham Kakade |
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Workshop
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Scaling Generative Tabular Learning for Large Language Models Yiming Sun · Xumeng Wen · Shun Zheng · Xiaowei Jia · Jiang Bian |
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Workshop
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Information-Theoretic Foundations for Neural Scaling Laws Hong Jun Jeon · Benjamin Van Roy |
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Workshop
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Improving the Gaussian Approximation in Neural Networks: Para-Gaussians and Edgeworth Expansions Mihai Nica · Janosch Ortmann |
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Workshop
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Does equivariance matter at scale? Johann Brehmer · Sönke Behrends · Pim de Haan · Taco Cohen |
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Workshop
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A Multi-Power Law for Loss Curve Prediction Across Learning Rate Schedules Kairong Luo · Haodong Wen · Shengding Hu · Zhenbo Sun · Zhiyuan Liu · Maosong Sun · Kaifeng Lyu · Wenguang Chen |