Papers
Relating Misfit to Gain in Weak-to-Strong Generalization Beyond the Squared Loss
Abhijeet Mulgund, Chirag Pabbaraju
Premise-Augmented Reasoning Chains Improve Error Identification in Math reasoning with LLMs
Sagnik Mukherjee, Abhinav Chinta, Takyoung Kim et al.
MIB: A Mechanistic Interpretability Benchmark
Aaron Mueller, Atticus Geiger, Sarah Wiegreffe et al.
CLARIFY: Contrastive Preference Reinforcement Learning for Untangling Ambiguous Queries
Ni Mu, Hao Hu, Xiao Hu et al.
SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression
Mohammad Mozaffari, Amir Yazdanbakhsh, Maryam Mehri Dehnavi
Sparse Autoencoders for Hypothesis Generation
Rajiv Movva, Kenny Peng, Nikhil Garg et al.
GRADEO: Towards Human-Like Evaluation for Text-to-Video Generation via Multi-Step Reasoning
Zhun Mou, Bin Xia, Zhengchao Huang et al.
Return of the Latent Space COWBOYS: Re-thinking the use of VAEs for Bayesian Optimisation of Structured Spaces
Henry Moss, Sebastian W. Ober, Tom Diethe
Geometric Hyena Networks for Large-scale Equivariant Learning
Artem Moskalev, Mangal Prakash, Junjie Xu et al.
SOLD: Slot Object-Centric Latent Dynamics Models for Relational Manipulation Learning from Pixels
Malte Mosbach, Jan Niklas Ewertz, Angel Villar-Corrales et al.
Revisiting Non-Acyclic GFlowNets in Discrete Environments
Nikita Morozov, Ian Maksimov, Daniil Tiapkin et al.
Causal-PIK: Causality-based Physical Reasoning with a Physics-Informed Kernel
Carlota Parés Morlans, Michelle Yi, Claire Chen et al.
Dimensionality Reduction on Complex Vector Spaces for Euclidean Distance with Dynamic Weights
Simone Moretti, Paolo Pellizzoni, Francesco Silvestri
The Price of Linear Time: Error Analysis of Structured Kernel Interpolation
Alexander Moreno, Justin Xiao, Jonathan Mei
Online Episodic Convex Reinforcement Learning
Bianca Marin Moreno, Khaled Eldowa, Pierre Gaillard et al.
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction
Rudy Morel, Jiequn Han, Edouard Oyallon
A Two-Stage Learning-to-Defer Approach for Multi-Task Learning
Yannis Montreuil, Yeo Shu Heng, Axel Carlier et al.
Adversarial Robustness in Two-Stage Learning-to-Defer: Algorithms and Guarantees
Yannis Montreuil, Axel Carlier, Lai Xing Ng et al.
Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity
Alessandro Montenegro, Marco Mussi, Matteo Papini et al.
A Variational Information Theoretic Approach to Out-of-Distribution Detection
Sudeepta Mondal, Zhuolin Jiang, Ganesh Sundaramoorthi
Adversarial Inputs for Linear Algebra Backends
Jonas Möller, Lukas Pirch, Felix Weissberg et al.
Symmetry-Driven Discovery of Dynamical Variables in Molecular Simulations
Jeet Mohapatra, Nima Dehmamy, Csaba Both et al.
NoLiMa: Long-Context Evaluation Beyond Literal Matching
Ali Modarressi, Hanieh Deilamsalehy, Franck Dernoncourt et al.
GMAIL: Generative Modality Alignment for generated Image Learning
Shentong Mo, Sukmin Yun