Summary of Test-time Adaptation For Regression by Subspace Alignment, By Kazuki Adachi et al.
Test-time Adaptation for Regression by Subspace Alignmentby Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai, Tomoki HamagamiFirst…
Summary of Formation Of Representations in Neural Networks, by Liu Ziyin et al.
Formation of Representations in Neural Networksby Liu Ziyin, Isaac Chuang, Tomer Galanti, Tomaso PoggioFirst submitted…
Summary of Revisit Large-scale Image-caption Data in Pre-training Multimodal Foundation Models, by Zhengfeng Lai et al.
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Modelsby Zhengfeng Lai, Vasileios Saveris, Chen Chen,…
Summary of Dynamic Gradient Alignment For Online Data Mixing, by Simin Fan et al.
Dynamic Gradient Alignment for Online Data Mixingby Simin Fan, David Grangier, Pierre AblinFirst submitted to…
Summary of Dual Active Learning For Reinforcement Learning From Human Feedback, by Pangpang Liu et al.
Dual Active Learning for Reinforcement Learning from Human Feedbackby Pangpang Liu, Chengchun Shi, Will Wei…
Summary of Simplicity Bias and Optimization Threshold in Two-layer Relu Networks, by Etienne Boursier and Nicolas Flammarion
Simplicity bias and optimization threshold in two-layer ReLU networksby Etienne Boursier, Nicolas FlammarionFirst submitted to…
Summary of Beyond Bradley-terry Models: a General Preference Model For Language Model Alignment, by Yifan Zhang et al.
Beyond Bradley-Terry Models: A General Preference Model for Language Model Alignmentby Yifan Zhang, Ge Zhang,…
Summary of Anchors Aweigh! Sail For Optimal Unified Multi-modal Representations, by Minoh Jeong et al.
Anchors Aweigh! Sail for Optimal Unified Multi-Modal Representationsby Minoh Jeong, Min Namgung, Zae Myung Kim,…
Summary of Ec-dit: Scaling Diffusion Transformers with Adaptive Expert-choice Routing, by Haotian Sun et al.
EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routingby Haotian Sun, Tao Lei, Bowen Zhang, Yanghao…
Summary of Meta-ttt: a Meta-learning Minimax Framework For Test-time Training, by Chen Tao et al.
Meta-TTT: A Meta-learning Minimax Framework For Test-Time Trainingby Chen Tao, Li Shen, Soumik MondalFirst submitted…