Papers
11,015 papers found
Language models are multilingual chain-of-thought reasoners
Freda Shi, Mirac Suzgun, Markus Freitag et al.
Language Models are Realistic Tabular Data Generators
Vadim Borisov, Kathrin Sessler, Tobias Leemann et al.
Language Models Can Teach Themselves to Program Better
Patrick Haluptzok, Matthew Bowers, Adam Tauman Kalai
Large Language Models are Human-Level Prompt Engineers
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han et al.
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson
Latent Bottlenecked Attentive Neural Processes
Leo Feng, Hossein Hajimirsadeghi, Yoshua Bengio et al.
Latent Graph Inference using Product Manifolds
Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero et al.
Latent Neural ODEs with Sparse Bayesian Multiple Shooting
Valerii Iakovlev, Cagatay Yildiz, Markus Heinonen et al.
Latent State Marginalization as a Low-cost Approach for Improving Exploration
Dinghuai Zhang, Aaron Courville, Yoshua Bengio et al.
Latent Variable Representation for Reinforcement Learning
Tongzheng Ren, Chenjun Xiao, Tianjun Zhang et al.
LAVA: Data Valuation without Pre-Specified Learning Algorithms
Hoang Anh Just, Feiyang Kang, Tianhao Wang et al.
Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations
Ziyu Jiang, Yinpeng Chen, Mengchen Liu et al.
LDMIC: Learning-based Distributed Multi-view Image Coding
Xinjie Zhang, Jiawei Shao, Jun Zhang
Learnable Behavior Control: Breaking Atari Human World Records via Sample-Efficient Behavior Selection
Jiajun Fan, Yuzheng Zhuang, Yuecheng Liu et al.
Learnable Graph Convolutional Attention Networks
Adrián Javaloy, Pablo Sanchez Martin, Amit Levi et al.
Learned Index with Dynamic $\epsilon$
Daoyuan Chen, Wuchao Li, Yaliang Li et al.
Learning About Progress From Experts
Jake Bruce, Ankit Anand, Bogdan Mazoure et al.
Learning Achievement Structure for Structured Exploration in Domains with Sparse Reward
Zihan Zhou, Animesh Garg
Learning a Data-Driven Policy Network for Pre-Training Automated Feature Engineering
Liyao Li, Haobo Wang, Liangyu Zha et al.
Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition
Canzhe Zhao, Ruofeng Yang, Baoxiang Wang et al.
Learning Continuous Normalizing Flows For Faster Convergence To Target Distribution via Ascent Regularizations
Shuangshuang Chen, Sihao Ding, Yiannis Karayiannidis et al.
Learning Controllable Adaptive Simulation for Multi-resolution Physics
Tailin Wu, Takashi Maruyama, Qingqing Zhao et al.
Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model
Zhihai Wang, Xijun Li, Jie Wang et al.
Learning differentiable solvers for systems with hard constraints
Geoffrey Négiar, Michael W. Mahoney, Aditi Krishnapriyan