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Workshop
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Accumulating Data Avoids Model Collapse
Joshua Kazdan · Apratim Dey · Rylan Schaeffer · Matthias Gerstgrasser · Rafael Rafailov · David Donoho · Sanmi Koyejo
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Poster
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Thu 16:30
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Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach
Hao Zhang · Chenglin Li · Nuowen Kan · Ziyang Zheng · Wenrui Dai · Junni Zou · Hongkai Xiong
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Poster
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Fri 16:30
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Goal Reduction with Loop-Removal Accelerates RL and Models Human Brain Activity in Goal-Directed Learning
Huzi Cheng · Joshua Brown
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Workshop
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Loop-Diffusion: an equivariant diffusion model for designing and scoring protein loops
Kevin Borisiak · Gian Marco Visani · Armita Nourmohammad
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Workshop
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Interactive Navigation of Quadruped Robots in Challenging Environments using Large Language Models
Kangjie Zhou · Yao Mu · Pengying Wu · Han Gao · Chang Liu
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Workshop
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Auxiliary objectives improve generalization performance but reduce model specification for low-data neuroimaging-based brain age prediction
Donghyun Kim · Eloy Geenjaar · Vince Calhoun
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Workshop
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From Loops to Oops: Fallback Behaviors of Language Models Under Uncertainty
Maor Ivgi · Ori Yoran · Jonathan Berant · Mor Geva
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Poster
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Causal Inference in the Closed-Loop: Marginal Structural Models for Sequential Excursion Effects
Alexander Levis · Gabriel Loewinger · Francisco Pereira
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Workshop
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Sat 14:20
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Invited Talk 3 - Scaling LLMs with Synthetic Data Loops
Suchin Gururangan
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Workshop
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Sat 14:30
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Alan Yuille (Johns Hopkins University): Supervision of 3D-aware Models by Synthetic Data
Alan Yuille
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Poster
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Fri 11:00
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Diffusion Twigs with Loop Guidance for Conditional Graph Generation
Giangiacomo Mercatali · Yogesh Verma · Andre Freitas · Vikas Garg
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Workshop
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Preventing Conflicting Gradients in Neural Temporal Point Process Models for Irregular Time Series Data
Tanguy Bosser · Souhaib Ben Taieb
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