Salakhutdinov, Ruslan

AgentDAM: Privacy Leakage Evaluation for Autonomous Web Agents

Zharmagambetov, A., Guo, C., Evtimov, I., Pavlova, M., Salakhutdinov, R., & Chaudhuri, K. (2025) · arXiv

Privacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Cited by 6

Don’t Copy the Teacher: Data and Model Challenges in Embodied Dialogue

Min, S. Y., Zhu, H., Salakhutdinov, R., & Bisk, Y. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Speech and dialogue systemsSocial Robot Interaction and HRI

Cited by 5

MultiViz: Towards User-Centric Visualizations and Interpretations of Multimodal Models

Liang, P. P., Lyu, Y., Chhablani, G., Jain, N., Deng, Z., Wang, X., Morency, L.-P., & Salakhutdinov, R. (2023) · Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Data Visualization and Analytics

Cited by 4

Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model Control

Fan, X., Lyu, Y., Liang, P. P., Salakhutdinov, R., & Morency, L.-P. (2023) · Findings of the Association for Computational Linguistics: ACL 2023

Topic ModelingNatural Language Processing Techniques

Cited by 3

Tree Search for Language Model Agents

Koh, J. Y., McAleer, S., Fried, D., & Salakhutdinov, R. (2024) · arXiv

AI-based Problem Solving and PlanningInformation Retrieval and Search Behavior

Cited by 2

Dissecting Adversarial Robustness of Multimodal LM Agents

Wu, C. H., Shah, R., Koh, J. Y., Salakhutdinov, R., Fried, D., & Raghunathan, A. (2024) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 1

Contrastive Difference Predictive Coding

Zheng, C., Salakhutdinov, R., & Eysenbach, B. (2023) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 1

VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks

Koh, J. Y., Lo, R., Jang, L., Duvvur, V., Lim, M. C., Huang, P.-Y., Neubig, G., Zhou, S., Salakhutdinov, R., & Fried, D. (2024) · arXiv

Multimodal Machine Learning ApplicationsWeb Data Mining and Analysis

Cited by 1

Rethinking Thinking Tokens: LLMs as Improvement Operators

Madaan, L., Didolkar, A., Gururangan, S., Quan, J., Silva, R., Salakhutdinov, R., Zaheer, M., Arora, S., & Goyal, A. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Can Large Reasoning Models Self-Train?

Shafayat, S., Tajwar, F., Salakhutdinov, R., Schneider, J., & Zanette, A. (2025) · arXiv

Reinforcement Learning in RoboticsMachine Learning and Algorithms

Cited by 0

Training a Generally Curious Agent

Tajwar, F., Jiang, Y., Thankaraj, A., Rahman, S. S., Kolter, J. Z., Schneider, J., & Salakhutdinov, R. (2025) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 0

GitSwarm: Decentralized Compounding Inference

Shah, V., Samanta, A., Dahal, P., Plekhanov, M., Wu, C.-J., Yih, S., Munos, R., Fergus, R., Foerster, J., Salakhutdinov, R., et al. (2026) · arXiv

Scientific Computing and Data ManagementAI-based Problem Solving and Planning

Cited by 0

Scaling Test-Time Compute for Agentic Coding

Kim, J., Yang, W., Niu, K., Zhang, H., Zhu, Y., Helenowski, E., Silva, R., Chen, Z., Iyer, S., Zaheer, M., et al. (2026) · arXiv

Software Engineering ResearchAI-based Problem Solving and Planning

Cited by 0

Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning

Qu, Y., Yang, M. Y. R., Setlur, A., Tunstall, L., Beeching, E. E., Salakhutdinov, R., & Kumar, A. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0