Papers
Strategic Planning: A Top-Down Approach to Option Generation
Max Ruiz Luyten, Antonin Berthon, Mihaela Van Der Schaar
From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning
Noa Rubin, Kirsten Fischer, Javed Lindner et al.
No Free Lunch from Random Feature Ensembles: Scaling Laws and Near-Optimality Conditions
Benjamin Samuel Ruben, William Lingxiao Tong, Hamza Tahir Chaudhry et al.
G-Adaptivity: optimised graph-based mesh relocation for finite element methods
James Rowbottom, Georg Maierhofer, Teo Deveney et al.
Implicit Riemannian Optimism with Applications to Min-Max Problems
Christophe Roux, David Martı́nez-Rubio, Sebastian Pokutta
Loss Functions and Operators Generated by f-Divergences
Vincent Roulet, Tianlin Liu, Nino Vieillard et al.
Differential Privacy Under Class Imbalance: Methods and Empirical Insights
Lucas Rosenblatt, Yuliia Lut, Ethan Turok et al.
Fragments to Facts: Partial-Information Fragment Inference from LLMs
Lucas Rosenblatt, Bin Han, Robert Wolfe et al.
CAN: Leveraging Clients As Navigators for Generative Replay in Federated Continual Learning
Xuankun Rong, Jianshu Zhang, Kun He et al.
MITIGATING OVER-EXPLORATION IN LATENT SPACE OPTIMIZATION USING LES
Omer Ronen, Ahmed Imtiaz Humayun, Richard Baraniuk et al.
Provably Efficient RL for Linear MDPs under Instantaneous Safety Constraints in Non-Convex Feature Spaces
Amirhossein Roknilamouki, Arnob Ghosh, Ming Shi et al.
Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces
Kevin Rojas, Yuchen Zhu, Sichen Zhu et al.
Towards characterizing the value of edge embeddings in Graph Neural Networks
Dhruv Rohatgi, Tanya Marwah, Zachary Chase Lipton et al.
Separating Knowledge and Perception with Procedural Data
Adrian Rodriguez-Munoz, Manel Baradad, Phillip Isola et al.
Concept Reachability in Diffusion Models: Beyond Dataset Constraints
Marta Aparicio Rodriguez, Xenia Miscouridou, Anastasia Borovykh
Discrete Neural Algorithmic Reasoning
Gleb Rodionov, Liudmila Prokhorenkova
A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
Zachary Andrew Roch, George K. Atia, Yue Wang
FairPFN: A Tabular Foundation Model for Causal Fairness
Jake Robertson, Noah Hollmann, Samuel Müller et al.
On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention for Long-Context LLM Serving
Yeonju Ro, Zhenyu Zhang, Souvik Kundu et al.
Resolving Lexical Bias in Model Editing
Hammad Rizwan, Domenic Rosati, Ga Wu et al.
Progressive Tempering Sampler with Diffusion
Severi Rissanen, Ruikang Ouyang, Jiajun He et al.
Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting
J Rishi, Gvs Mothish, Deepak Subramani
Update Your Transformer to the Latest Release: Re-Basin of Task Vectors
Filippo Rinaldi, Giacomo Capitani, Lorenzo Bonicelli et al.
General agents need world models
Jonathan Richens, Tom Everitt, David Abel
Understanding the Logic of Direct Preference Alignment through Logic
Kyle Richardson, Vivek Srikumar, Ashish Sabharwal