Papers
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts
Mikayel Samvelyan, Sharath Chandra Raparthy, Andrei Lupu et al.
RAMP: Boosting Adversarial Robustness Against Multiple $l_p$ Perturbations for Universal Robustness
Enyi Jiang, Gagandeep Singh
RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks
Guglielmo Gattiglio, Lyudmila Grigoryeva, Massimiliano Tamborrino
Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding
Daniel Severo, Ashish Khisti, Alireza Makhzani
Random Function Descent
Felix Benning, Leif Döring
Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces
Angeliki Kamoutsi, Peter Schmitt-Förster, Tobias Sutter et al.
Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation
Wooseong Cho, Taehyun Hwang, Joongkyu Lee et al.
Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning
Hao-Lun Hsu, Weixin Wang, Miroslav Pajic et al.
Randomized Sparse Matrix Compression for Large-Scale Constrained Optimization in Cancer Radiotherapy
Shima Adeli, Mojtaba Tefagh, Gourav Jhanwar et al.
Randomized Strategic Facility Location with Predictions
Eric Balkanski, Vasilis Gkatzelis, Golnoosh Shahkarami
Randomized Truthful Auctions with Learning Agents
Gagan Aggarwal, Anupam Gupta, Andres Perlroth et al.
RanDumb: Random Representations Outperform Online Continually Learned Representations
Ameya Prabhu, Shiven Sinha, Ponnurangam Kumaraguru et al.
RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs
Yue Yu, Wei Ping, Zihan Liu et al.
RankUp: Boosting Semi-Supervised Regression with an Auxiliary Ranking Classifier
Pin-Yen Huang, Szu-Wei Fu, Yu Tsao
RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning
Yujie Zhao, Jose Efraim Aguilar Escamill, Weyl Lu et al.
Rapid Plug-in Defenders
Kai Wu, Yujian Betterest Li, Jian Lou et al.
RashomonGB: Analyzing the Rashomon Effect and Mitigating Predictive Multiplicity in Gradient Boosting
Hsiang Hsu, Ivan Brugere, Shubham Sharma et al.
RaVL: Discovering and Mitigating Spurious Correlations in Fine-Tuned Vision-Language Models
Maya Varma, Jean-Benoit Delbrouck, Zhihong Chen et al.
RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees
Xun Xian, Ganghua Wang, Xuan Bi et al.
RCDN: Towards Robust Camera-Insensitivity Collaborative Perception via Dynamic Feature-based 3D Neural Modeling
Tianhang Wang, Fan Lu, Zehan Zheng et al.
RClicks: Realistic Click Simulation for Benchmarking Interactive Segmentation
Anton Antonov, Andrey Moskalenko, Denis Shepelev et al.
ReactZyme: A Benchmark for Enzyme-Reaction Prediction
Chenqing Hua, Bozitao Zhong, Sitao Luan et al.
RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models
Xinchen Zhang, Ling Yang, Yaqi Cai et al.
Realizable $H$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
Anqi Mao, Mehryar Mohri, Yutao Zhong
RealMAN: A Real-Recorded and Annotated Microphone Array Dataset for Dynamic Speech Enhancement and Localization
Bing Yang, Changsheng Quan, Yabo Wang et al.