On Evaluating the Generalization of LSTM Models in Formal Languages. - Mirac Suzgun; Yonatan Belinkov; Stuart M. Shieber (CoRR, 2018)

LSTM Networks Can Perform Dynamic Counting. - Mirac Suzgun; Sebastian Gehrmann; Yonatan Belinkov; Stuart M. Shieber (CoRR, 2019)

Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages. - Mirac Suzgun; Sebastian Gehrmann; Yonatan Belinkov; Stuart M. Shieber (CoRR, 2019)

Prompt-and-Rerank: A Method for Zero-Shot and Few-Shot Arbitrary Textual Style Transfer with Small Language Models. - Mirac Suzgun; Luke Melas-Kyriazi; Dan Jurafsky (EMNLP, 2022)

Monte Carlo Tree Search for Interpreting Stress in Natural Language. - Kyle Swanson; Joy Hsu; Mirac Suzgun (LT-EDI, 2022)

Scaling Instruction-Finetuned Language Models. - Hyung Won Chung; Le Hou; Shayne Longpre; Barret Zoph; Yi Tay; William Fedus; Eric Li; Xuezhi Wang 002; Mostafa Dehghani 001; Siddhartha Brahma; Albert Webson; Shixiang Shane Gu; et al. (CoRR, 2022)

Follow the Wisdom of the Crowd: Effective Text Generation via Minimum Bayes Risk Decoding. - Mirac Suzgun; Luke Melas-Kyriazi; Dan Jurafsky (ACL (Findings), 2023)

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. - Mirac Suzgun; Nathan Scales; Nathanael Schärli; Sebastian Gehrmann; Yi Tay; Hyung Won Chung; Aakanksha Chowdhery; Quoc V. Le; Ed H. Chi; Denny Zhou; Jason Wei (ACL (Findings), 2023)

When Do Pre-Training Biases Propagate to Downstream Tasks? A Case Study in Text Summarization. - Faisal Ladhak; Esin Durmus; Mirac Suzgun; Tianyi Zhang; Dan Jurafsky; Kathleen R. McKeown; Tatsunori Hashimoto (EACL, 2023)

Language models are multilingual chain-of-thought reasoners. - Freda Shi; Mirac Suzgun; Markus Freitag; Xuezhi Wang 002; Suraj Srivats; Soroush Vosoughi; Hyung Won Chung; Yi Tay; Sebastian Ruder; Denny Zhou; Dipanjan Das 001; Jason Wei (ICLR, 2023)

The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications. - Mirac Suzgun; Luke Melas-Kyriazi; Suproteem K. Sarkar; Scott Duke Kominers; Stuart M. Shieber (NeurIPS, 2023)

string2string: A Modern Python Library for String-to-String Algorithms. - Mirac Suzgun; Stuart M. Shieber; Dan Jurafsky (CoRR, 2023)

Holistic Evaluation of Language Models. - Percy Liang; Rishi Bommasani; Tony Lee; Dimitris Tsipras; Dilara Soylu; Michihiro Yasunaga; Yian Zhang; Deepak Narayanan; Yuhuai Wu; Ananya Kumar; Benjamin Newman; Binhang Yuan; et al. (Trans. Mach. Learn. Res., 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Do Language Models Know When They're Hallucinating References? - Ayush Agrawal; Mirac Suzgun; Lester Mackey; Adam Kalai (EACL (Findings), 2024)

Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions. - Federico Bianchi 001; Mirac Suzgun; Giuseppe Attanasio; Paul Röttger; Dan Jurafsky; Tatsunori Hashimoto; James Zou 001 (ICLR, 2024)

A Benchmark for Learning to Translate a New Language from One Grammar Book. - Garrett Tanzer; Mirac Suzgun; Eline Visser; Dan Jurafsky; Luke Melas-Kyriazi (ICLR, 2024)

Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models. - Matthew Dahl; Varun Magesh; Mirac Suzgun; Daniel E. Ho (CoRR, 2024)

Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding. - Mirac Suzgun; Adam Tauman Kalai (CoRR, 2024)

Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools. - Varun Magesh; Faiz Surani; Matthew Dahl; Mirac Suzgun; Christopher D. Manning; Daniel E. Ho (CoRR, 2024)

Belief in the Machine: Investigating Epistemological Blind Spots of Language Models. - Mirac Suzgun; Tayfun Gur; Federico Bianchi 001; Daniel E. Ho; Thomas Icard; Dan Jurafsky; James Zou 001 (CoRR, 2024)

Scaling Instruction-Finetuned Language Models. - Hyung Won Chung; Le Hou; Shayne Longpre; Barret Zoph; Yi Tay; William Fedus; Yunxuan Li; Xuezhi Wang 002; Mostafa Dehghani 001; Siddhartha Brahma; Albert Webson; Shixiang Shane Gu; et al. (J. Mach. Learn. Res., 2024)

AI for Scaling Legal Reform: Mapping and Redacting Racial Covenants in Santa Clara County. - Faiz Surani; Mirac Suzgun; Vyoma Raman; Christopher D. Manning; Peter Henderson 002; Daniel E. Ho (CoRR, 2025)

Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory. - Mirac Suzgun; Mert Yüksekgönül; Federico Bianchi 001; Dan Jurafsky; James Zou 001 (CoRR, 2025)

Cost-of-Pass: An Economic Framework for Evaluating Language Models. - Mehmet Hamza Erol; Batu El; Mirac Suzgun; Mert Yüksekgönül; James Zou 001 (CoRR, 2025)