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| 2025 | FairPFN: A Tabular Foundation Model for Causal Fairness. | Jake Robertson, Noah Hollmann, Samuel Mller, Noor H. Awad, Frank Hutter |
| 2025 | On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention for Long-Context LLM Serving. | Yeonju Ro, Zhenyu Zhang, Souvik Kundu, Zhangyang Wang, Aditya Akella |
| 2025 | Resolving Lexical Bias in Model Editing. | Hammad Rizwan, Domenic Rosati, Ga Wu, Hassan Sajjad |
| 2025 | Progressive Tempering Sampler with Diffusion. | Severi Rissanen, Ruikang Ouyang, Jiajun He, Wenlin Chen, Markus Heinonen, Arno Solin, Jos Miguel Hernndez-Lobato |
| 2025 | Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting. | J. Rishi, GVS Mothish, Deepak Subramani |
| 2025 | Update Your Transformer to the Latest Release: Re-Basin of Task Vectors. | Filippo Rinaldi, Giacomo Capitani, Lorenzo Bonicelli, Donato Crisostomi, Federico Bolelli, Elisa Ficarra, Emanuele Rodol, Simone Calderara, Angelo Porrello |
| 2025 | Position: Theory of Mind Benchmarks are Broken for Large Language Models. | Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu, Justin D. Weisz, Murray Campbell |
| 2025 | General agents need world models. | Jonathan Richens, Tom Everitt, David Abel |
| 2025 | Feature learning from non-Gaussian inputs: the case of Independent Component Analysis in high dimensions. | Fabiola Ricci, Lorenzo Bardone, Sebastian Goldt |
| 2025 | Representative Ranking for Deliberation in the Public Sphere. | Manon Revel, Smitha Milli, Tyler Lu, Jamelle Watson-Daniels, Maximilian Nickel |
| 2025 | Can Transformers Learn Full Bayesian Inference in Context? | Arik Reuter, Tim G. J. Rudner, Vincent Fortuin, David Rgamer |
| 2025 | Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation. | Roie Reshef, Kfir Yehuda Levy |
| 2025 | FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching. | Sucheng Ren, Qihang Yu, Ju He, Xiaohui Shen, Alan L. Yuille, Liang-Chieh Chen |
| 2025 | ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks. | Zhiyao Ren, Siyuan Liang, Aishan Liu, Dacheng Tao |
| 2025 | A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization. | Kunjie Ren, Luo Luo |
| 2025 | Inverse Optimization via Learning Feasible Regions. | Ke Ren, Peyman Mohajerin Esfahani, Angelos Georghiou |
| 2025 | Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research. | Patrik Reizinger, Randall Balestriero, David A. Klindt, Wieland Brendel |
| 2025 | Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization. | Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh, Yingqian Zhang |
| 2025 | When to retrain a machine learning model. | Florence Regol, Leo Schwinn, Kyle Sprague, Mark Coates, Thomas Markovich |
| 2025 | RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals. | David Reber, Sean M. Richardson, Todd Nief, Cristina Garbacea, Victor Veitch |
| 2025 | Towards Memorization Estimation: Fast, Formal and Free. | Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi, Kaushik Roy |
| 2025 | Statistical Hypothesis Testing for Auditing Robustness in Language Models. | Paulius Rauba, Qiyao Wei, Mihaela van der Schaar |
| 2025 | Adversarial Inception Backdoor Attacks against Reinforcement Learning. | Ethan Rathbun, Alina Oprea, Christopher Amato |
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