| 2025 | Geometric Hyena Networks for Large-scale Equivariant Learning. | Artem Moskalev, Mangal Prakash, Junjie Xu, Tianyu Cui, Rui Liao, Tommaso Mansi |
| 2025 | SOLD: Slot Object-Centric Latent Dynamics Models for Relational Manipulation Learning from Pixels. | Malte Mosbach, Jan Niklas Ewertz, Angel Villar-Corrales, Sven Behnke |
| 2025 | Revisiting Non-Acyclic GFlowNets in Discrete Environments. | Nikita Morozov, Ian Maksimov, Daniil Tiapkin, Sergey Samsonov |
| 2025 | Dimensionality Reduction on Complex Vector Spaces for Euclidean Distance with Dynamic Weights. | Simone Moretti, Paolo Pellizzoni, Francesco Silvestri |
| 2025 | The Price of Linear Time: Error Analysis of Structured Kernel Interpolation. | Alexander Moreno, Justin Xiao, Jonathan Mei |
| 2025 | Online Episodic Convex Reinforcement Learning. | Bianca Marin Moreno, Khaled Eldowa, Pierre Gaillard, Margaux Brgre, Nadia Oudjane |
| 2025 | DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction. | Rudy Morel, Jiequn Han, Edouard Oyallon |
| 2025 | Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences. | Kirsten N. Morehouse, Siddharth Swaroop, Weiwei Pan |
| 2025 | A Two-Stage Learning-to-Defer Approach for Multi-Task Learning. | Yannis Montreuil, Yeo Shu Heng, Axel Carlier, Lai Xing Ng, Wei Tsang Ooi |
| 2025 | Adversarial Robustness in Two-Stage Learning-to-Defer: Algorithms and Guarantees. | Yannis Montreuil, Axel Carlier, Lai Xing Ng, Wei Tsang Ooi |
| 2025 | Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity. | Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli |
| 2025 | A Variational Information Theoretic Approach to Out-of-Distribution Detection. | Sudeepta Mondal, Zhuolin Jiang, Ganesh Sundaramoorthi |
| 2025 | Adversarial Inputs for Linear Algebra Backends. | Jonas Mller, Lukas Pirch, Felix Weissberg, Sebastian Baunsgaard, Thorsten Eisenhofer, Konrad Rieck |
| 2025 | Symmetry-Driven Discovery of Dynamical Variables in Molecular Simulations. | Jeet Mohapatra, Nima Dehmamy, Csaba Both, Subhro Das, Tommi S. Jaakkola |
| 2025 | Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning. | Mehrdad Moghimi, Hyejin Ku |
| 2025 | NoLiMa: Long-Context Evaluation Beyond Literal Matching. | Ali Modarressi, Hanieh Deilamsalehy, Franck Dernoncourt, Trung Bui, Ryan A. Rossi, Seunghyun Yoon, Hinrich Schtze |
| 2025 | Position: Probabilistic Modelling is Sufficient for Causal Inference. | Bruno Kacper Mlodozeniec, David Krueger, Richard E. Turner |
| 2025 | I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models. | Zhenxing Mi, Kuan-Chieh Wang, Guocheng Qian, Hanrong Ye, Runtao Liu, Sergey Tulyakov, Kfir Aberman, Dan Xu |
| 2025 | Does learning the right latent variables necessarily improve in-context learning? | Sarthak Mittal, Eric Elmoznino, Lo Gagnon, Sangnie Bhardwaj, Guillaume Lajoie, Dhanya Sridhar |
| 2025 | Equivariant Neural Tangent Kernels. | Philipp Misof, Pan Kessel, Jan E. Gerken |
| 2025 | SING: Spatial Context in Large Language Model for Next-Gen Wearables. | Ayushi Mishra, Yang Bai, Priyadarshan Narayanasamy, Nakul Garg, Nirupam Roy |
| 2025 | SWE-Lancer: Can Frontier LLMs Earn $1 Million from Real-World Freelance Software Engineering? | Samuel Miserendino, Michele Wang, Tejal Patwardhan, Johannes Heidecke |
| 2025 | Measuring Diversity: Axioms and Challenges. | Mikhail Mironov, Liudmila Prokhorenkova |
| 2025 | Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMs. | Hancheng Min, Ren Vidal |
| 2025 | CROW: Eliminating Backdoors from Large Language Models via Internal Consistency Regularization. | Nay Myat Min, Long H. Pham, Yige Li, Jun Sun |