Spotlight Papers
1,421 papers found • Page 29 of 29
Conference
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks
Hao Chen, Jindong Wang, Ankit Parag Shah et al.
Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression
Runtian Zhai, Bingbin Liu, Andrej Risteski et al.
Uni3D: Exploring Unified 3D Representation at Scale
Junsheng Zhou, Jinsheng Wang, Baorui Ma et al.
Unified Human-Scene Interaction via Prompted Chain-of-Contacts
Zeqi Xiao, Tai Wang, Jingbo Wang et al.
Universal Humanoid Motion Representations for Physics-Based Control
Zhengyi Luo, Jinkun Cao, Josh Merel et al.
Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND
Qiyu Kang, Kai Zhao, Qinxu Ding et al.
Unlocking the Power of Representations in Long-term Novelty-based Exploration
Alaa Saade, Steven Kapturowski, Daniele Calandriello et al.
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings
Kevin Frans, Seohong Park, Pieter Abbeel et al.
Variational Bayesian Last Layers
James Harrison, John Willes, Jasper Snoek
Variational Inference for SDEs Driven by Fractional Noise
Rembert Daems, Manfred Opper, Guillaume Crevecoeur et al.
Variational Learning is Effective for Large Deep Networks
Yuesong Shen, Nico Daheim, Bai Cong et al.
Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation
Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan et al.
Vision-Language Foundation Models as Effective Robot Imitators
Xinghang Li, Minghuan Liu, Hanbo Zhang et al.
Vocabulary for Universal Approximation: A Linguistic Perspective of Mapping Compositions
Yongqiang Cai
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
Xing Han Lù, Zdeněk Kasner, Siva Reddy
What does automatic differentiation compute for neural networks?
Sejun Park, Sanghyuk Chun, Wonyeol Lee
What does the Knowledge Neuron Thesis Have to do with Knowledge?
Jingcheng Niu, Andrew Liu, Zining Zhu et al.
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Aaditya Singh, Ted Moskovitz, Feilx Hill et al.
What's In My Big Data?
Yanai Elazar, Akshita Bhagia, Ian Magnusson et al.
What Will My Model Forget? Forecasting Forgotten Examples in Language Model Refinement
Xisen Jin, Xiang Ren
Whole-Song Hierarchical Generation of Symbolic Music Using Cascaded Diffusion Models
Ziyu Wang, Lejun Min, Gus Xia