Bartoldson, Brian R.

Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

Geiping, J., McLeish, S., Jain, N., Kirchenbauer, J., Singh, S., Bartoldson, B., Kailkhura, B., Bhatele, A., & Goldstein, T. (2025) · Advances in Neural Information Processing Systems 38

Topic ModelingExplainable Artificial Intelligence (XAI)

Cited by 10

Act Only When It Pays: Efficient Reinforcement Learning for LLM Reasoning via Selective Rollouts

Zheng, H., Zhou, Y., Bartoldson, B. R., Kailkhura, B., Lai, F., Zhao, J., & Chen, B. (2025) · arXiv

Reinforcement Learning in RoboticsTopic Modeling

Cited by 4

Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models

Venkatraman, S., Jain, V., Mittal, S., Shah, V., Obando-Ceron, J., Bengio, Y., Bartoldson, B. R., Kailkhura, B., Lajoie, G., Berseth, G., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

STAR-1: Safer Alignment of Reasoning LLMs with 1K Data

Wang, Z., Tu, H., Wang, Y., Wu, J., Liu, Y., Mei, J., Bartoldson, B. R., Kailkhura, B., & Xie, C. (2025) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 0