Papers
11,951 papers found
LoRA: Low-Rank Adaptation of Large Language Models
Edward J Hu, yelong shen, Phillip Wallis et al.
LORD: Lower-Dimensional Embedding of Log-Signature in Neural Rough Differential Equations
JAEHOON LEE, Jinsung Jeon, Sheo yon Jhin et al.
Lossless Compression with Probabilistic Circuits
Anji Liu, Stephan Mandt, Guy Van den Broeck
LOSSY COMPRESSION WITH DISTRIBUTION SHIFT AS ENTROPY CONSTRAINED OPTIMAL TRANSPORT
Huan Liu, George Zhang, Jun Chen et al.
Low-Budget Active Learning via Wasserstein Distance: An Integer Programming Approach
Rafid Mahmood, Sanja Fidler, Marc T Law
Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality
Yiping Lu, Haoxuan Chen, Jianfeng Lu et al.
MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining
Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk
MAML is a Noisy Contrastive Learner in Classification
Chia Hsiang Kao, Wei-Chen Chiu, Pin-Yu Chen
Mandarin Lombard Grid: a Lombard-grid-like corpus of Standard Chinese
Yuhong Yang, Xufeng Chen, Qingmu Liu et al.
Map Induction: Compositional spatial submap learning for efficient exploration in novel environments
Sugandha Sharma, Aidan Curtis, Marta Kryven et al.
Mapping conditional distributions for domain adaptation under generalized target shift
Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bezenac et al.
Mapping Language Models to Grounded Conceptual Spaces
Roma Patel, Ellie Pavlick
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
Denis Yarats, Rob Fergus, Alessandro Lazaric et al.
Matrix Completion with Covariate Information and Informative Missingness
Huaqing Jin, Yanyuan Ma, Fei Jiang
Maximizing Ensemble Diversity in Deep Reinforcement Learning
Hassam Sheikh, Mariano Phielipp, Ladislau Boloni
Maximum Entropy RL (Provably) Solves Some Robust RL Problems
Benjamin Eysenbach, Sergey Levine
Maximum n-times Coverage for Vaccine Design
Ge Liu, Alexander Dimitrakakis, Brandon Carter et al.
MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC
Erik Nijkamp, Ruiqi Gao, Pavel Sountsov et al.
Measuring CLEVRness: Black-box Testing of Visual Reasoning Models
Spyridon Mouselinos, Henryk Michalewski, Mateusz Malinowski
Measuring the Interpretability of Unsupervised Representations via Quantized Reversed Probing
Iro Laina, Yuki M Asano, Andrea Vedaldi
Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models
Kushal Tirumala, Aram Markosyan, Luke Zettlemoyer et al.
Memorizing Transformers
Yuhuai Wu, Markus Norman Rabe, DeLesley Hutchins et al.
Memory Augmented Optimizers for Deep Learning
Paul-Aymeric Martin McRae, Prasanna Parthasarathi, Mido Assran et al.
Memory Replay with Data Compression for Continual Learning
Liyuan Wang, Xingxing Zhang, Kuo Yang et al.
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention
Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald et al.