Papers
11,951 papers found
Aligning AI With Shared Human Values
Dan Hendrycks, Collin Burns, Steven Basart et al.
A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
Nikunj Saunshi, Sadhika Malladi, Sanjeev Arora
An Adaptive News-Driven Method for CVaR-sensitive Online Portfolio Selection in Non-Stationary Financial Markets
Qianqiao Liang, Mengying Zhu, Xiaolin Zheng et al.
Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective
Muhammet Balcilar, Guillaume Renton, Pierre Héroux et al.
Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics
Vinay Venkatesh Ramasesh, Ethan Dyer, Maithra Raghu
Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies
Paul Pu Liang, Manzil Zaheer, Yuan Wang et al.
A New Vowel Normalization for Sociophonetics
Wilbert Heeringa, Hans Van de Velde
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov et al.
ANOCE: Analysis of Causal Effects with Multiple Mediators via Constrained Structural Learning
Hengrui Cai, Rui Song, Wenbin Lu
A Non-commutative Extension of Lee-Seung's Algorithm for Positive Semidefinite Factorizations
Yong Sheng Soh, Antonios Varvitsiotis
Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval
Wenhan Xiong, Xiang Li, Srini Iyer et al.
An Unsupervised Deep Learning Approach for Real-World Image Denoising
Dihan Zheng, Sia Huat Tan, Xiaowen Zhang et al.
Anytime Sampling for Autoregressive Models via Ordered Autoencoding
Yilun Xu, Yang Song, Sahaj Garg et al.
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks
Renjie Liao, Raquel Urtasun, Richard Zemel
A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
Sanghyun Hong, Yigitcan Kaya, Ionuț-Vlad Modoranu et al.
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
Lee Xiong, Chenyan Xiong, Ye Li et al.
Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
Róbert Csordás, Sjoerd van Steenkiste, Jürgen Schmidhuber
Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
Zhen Qin, Le Yan, Honglei Zhuang et al.
Are wider nets better given the same number of parameters?
Anna Golubeva, Guy Gur-Ari, Behnam Neyshabur
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity
Kangkang Lu, Cuong Manh Nguyen, Xun Xu et al.
Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning
Valerie Chen, Abhinav Gupta, Kenneth Marino
A statistical theory of cold posteriors in deep neural networks
Laurence Aitchison
Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors
Yu Sun, Jiaming Liu, Yiran Sun et al.
A teacher-student framework to distill future trajectories
Alexander Neitz, Giambattista Parascandolo, Bernhard Schölkopf
A Temporal Kernel Approach for Deep Learning with Continuous-time Information
Da Xu, Chuanwei Ruan, Evren Korpeoglu et al.