Hashimoto, Tatsunori

Robust distortion-free watermarks for language models

Kuditipudi, R., Thickstun, J., Hashimoto, T., & Liang, P. (2023) · arXiv

Advanced Steganography and Watermarking TechniquesAdversarial Robustness in Machine Learning

Cited by 23

Identifying the Risks of LM Agents with an LM-Emulated Sandbox

Ruan, Y., Dong, H., Wang, A., Pitis, S., Zhou, Y., Ba, J., Dubois, Y., Maddison, C. J., & Hashimoto, T. (2023) · arXiv

Adversarial Robustness in Machine LearningSoftware Testing and Debugging Techniques

Cited by 19

Learning to (Learn at Test Time): RNNs with Expressive Hidden States

Sun, Y., Li, X., Dalal, K., Xu, J., Vikram, A., Zhang, G., Dubois, Y., Chen, X., Wang, X., Koyejo, S., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 18

Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Dubois, Y., Galambosi, B., Liang, P., & Hashimoto, T. B. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 17

Spurious Correlations in Reference-Free Evaluation of Text Generation

Durmus, E., Ladhak, F., & Hashimoto, T. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 16

s1: Simple test-time scaling

Muennighoff, N., Yang, Z., Shi, W., Li, X. L., Fei-Fei, L., Hajishirzi, H., Zettlemoyer, L., Liang, P., Candès, E., & Hashimoto, T. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 12

A Survey on Data Selection for Language Models

Albalak, A., Elazar, Y., Xie, S. M., Longpre, S., Lambert, N., Wang, X., Muennighoff, N., Hou, B., Pan, L., Jeong, H., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 12

Proving Test Set Contamination in Black Box Language Models

Oren, Y., Meister, N., Chatterji, N., Ladhak, F., & Hashimoto, T. B. (2023) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 11

Understanding Finetuning for Factual Knowledge Extraction

Ghosal, G., Hashimoto, T., & Raghunathan, A. (2024) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 3

Observational Scaling Laws and the Predictability of Language Model Performance

Ruan, Y., Maddison, C. J., & Hashimoto, T. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3

LongCodeBench: Evaluating Coding LLMs at 1M Context Windows

Rando, S., Romani, L., Sampieri, A., Franco, L., Yang, J., Kyuragi, Y., Galasso, F., & Hashimoto, T. (2025) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 2

Synthetic continued pretraining

Yang, Z., Band, N., Li, S., Candès, E., & Hashimoto, T. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

OpenThoughts: Data Recipes for Reasoning Models

Guha, E., Marten, R., Keh, S., Raoof, N., Smyrnis, G., Bansal, H., Nezhurina, M., Mercat, J., Vu, T., Sprague, Z., et al. (2025) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 1

The Extractive-Abstractive Spectrum: Uncovering Verifiability Trade-offs in LLM Generations

Worledge, T., Hashimoto, T., & Guestrin, C. (2024) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 1

Putting It All into Context: Simplifying Agents with LCLMs

Jiang, M., Ruan, Y., Lastras, L., Kapanipathi, P., & Hashimoto, T. (2025) · arXiv

Software Engineering ResearchAI-based Problem Solving and Planning

Cited by 0

End-to-End Test-Time Training for Long Context

Tandon, A., Dalal, K., Li, X., Koceja, D., Rød, M., Buchanan, S., Wang, X., Leskovec, J., Koyejo, S., Hashimoto, T., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Learning to (Learn at Test Time)

Sun, Y., Li, X., Dalal, K., Hsu, C., Koyejo, S., Guestrin, C., Wang, X., Hashimoto, T., & Chen, X. (2023) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 0