Srinivasa, Jayanth

Middleware for LLMs: Tools Are Instrumental for Language Agents in Complex Environments

Gu, Y., Shu, Y., Yu, H., Liu, X., Dong, Y., Tang, J., Srinivasa, J., Latapie, H., & Su, Y. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 28

EXP-Bench: Can AI Conduct AI Research Experiments?

Kon, P. T. J., Liu, J., Zhu, X., Ding, Q., Peng, J., Xing, J., Huang, Y., Qiu, Y., Srinivasa, J., Lee, M., et al. (2025) · arXiv

Artificial Intelligence ApplicationsScientific Computing and Data Management

Cited by 1

The Hidden Risks of Large Reasoning Models: A Safety Assessment of R1

Zhou, K., Liu, C., Zhao, X., Jangam, S., Srinivasa, J., Liu, G., Song, D., & Wang, X. E. (2025) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 0

Survive or Collapse: The Asymmetric Roles of Data Gating and Reward Grounding in Self-Play RL

Pu, S. X., Weng, Z., Liu, C., Srinivasa, J., Liu, G., Wang, W. Y., & Wang, X. E. (2026) · arXiv

Reinforcement Learning in RoboticsTopic Modeling

Cited by 0

SkillWeaver: Web Agents can Self-Improve by Discovering and Honing Skills

Zheng, B., Fatemi, M. Y., Jin, X., Wang, Z. Z., Gandhi, A., Song, Y., Gu, Y., Srinivasa, J., Liu, G., Neubig, G., et al. (2025) · arXiv

Web Data Mining and AnalysisInformation Retrieval and Search Behavior

Cited by 0