Radhakrishnan, Ansh
7 papers on CoChat
Most cited papers
- Verified
Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training
Hubinger, E., Denison, C., Mu, J., Lambert, M., Tong, M., MacDiarmid, M., Lanham, T., Ziegler, D. M., Maxwell, T., Cheng, N., et al. (2024) · arXiv
Adversarial Robustness in Machine LearningEthics and Social Impacts of AI
Cited by 46
- Verified
Measuring Faithfulness in Chain-of-Thought Reasoning
Lanham, T., Chen, A., Radhakrishnan, A., Steiner, B., Denison, C., Hernandez, D., Li, D., Durmus, E., Hubinger, E., Kernion, J., et al. (2023) · arXiv
Topic ModelingExplainable Artificial Intelligence (XAI)
Cited by 33
- Verified
Many-shot Jailbreaking
Anil, C., Durmus, E., Panickssery, N., Sharma, M., Benton, J., Kundu, S., Batson, J., Tong, M., Mu, J., Ford, D., et al. (2024) · Advances in Neural Information Processing Systems 37
Adversarial Robustness in Machine LearningSecurity and Verification in Computing
Cited by 25
- Verified
Reasoning Models Don't Always Say What They Think
Chen, Y., Benton, J., Radhakrishnan, A., Uesato, J., Denison, C., Schulman, J., Somani, A., Hase, P., Wagner, M., Roger, F., et al. (2025) · arXiv
Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI
Cited by 18
- Verified
Debating with More Persuasive LLMs Leads to More Truthful Answers
Khan, A., Hughes, J., Valentine, D., Ruis, L., Sachan, K., Radhakrishnan, A., Grefenstette, E., Bowman, S. R., Rocktäschel, T., & Perez, E. (2024) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 13
- Verified
Question Decomposition Improves the Faithfulness of Model-Generated Reasoning
Radhakrishnan, A., Nguyen, K., Chen, A., Chen, C., Denison, C., Hernandez, D., Durmus, E., Hubinger, E., Kernion, J., Lukošiūtė, K., et al. (2023) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 8
- Verified
Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats
Wen, J., Hebbar, V., Larson, C., Bhatt, A., Radhakrishnan, A., Sharma, M., Sleight, H., Feng, S., He, H., Perez, E., et al. (2024) · arXiv
Adversarial Robustness in Machine LearningSecurity and Verification in Computing
Cited by 1
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