DisSent: Sentence Representation Learning from Explicit Discourse Relations. - Allen Nie; Erin D. Bennett; Noah D. Goodman (CoRR, 2017)

DeepTag: inferring all-cause diagnoses from clinical notes in under-resourced medical domain. - Allen Nie; Ashley Zehnder; Rodney López Page; Arturo L. Pineda; Manuel A. Rivas; Carlos D. Bustamante; James Zou 001 (CoRR, 2018)

Large-scale Generative Modeling to Improve Automated Veterinary Disease Coding. - Yuhui Zhang; Allen Nie; James Zou 001 (CoRR, 2018)

DeepTag: inferring diagnoses from veterinary clinical notes. - Allen Nie; Ashley Zehnder; Rodney López Page; Yuhui Zhang; Arturo López Pineda; Manuel A. Rivas; Carlos D. Bustamante; James Zou 001 (npj Digit. Medicine, 2018)

DisSent: Learning Sentence Representations from Explicit Discourse Relations. - Allen Nie; Erin Bennett; Noah D. Goodman (ACL (1), 2019)

Learning to Explain: Answering Why-Questions via Rephrasing. - Allen Nie; Erin D. Bennett; Noah D. Goodman (CoRR, 2019)

VetTag: improving automated veterinary diagnosis coding via large-scale language modeling. - Yuhui Zhang; Allen Nie; Ashley Zehnder; Rodney López Page; James Zou 001 (npj Digit. Medicine, 2019)

Inducing Grammar from Long Short-Term Memory Networks by Shapley Decomposition. - Yuhui Zhang; Allen Nie (ACL (student), 2020)

Pragmatic Issue-Sensitive Image Captioning. - Allen Nie; Reuben Cohn-Gordon; Christopher Potts (EMNLP (Findings), 2020)

LitGen: Genetic Literature Recommendation Guided by Human Explanations. - Allen Nie; Arturo L. Pineda; Matt W. Wright; Hannah Wand; Bryan Wulf; Helio A. Costa; Ronak Y. Patel; Carlos D. Bustamante; James Zou 001 (PSB, 2020)

Play to Grade: Testing Coding Games as Classifying Markov Decision Process. - Allen Nie; Emma Brunskill; Chris Piech (NeurIPS, 2021)

Giving Feedback on Interactive Student Programs with Meta-Exploration. - Evan Zheran Liu; Moritz Stephan; Allen Nie; Chris Piech; Emma Brunskill; Chelsea Finn (NeurIPS, 2022)

Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data. - Allen Nie; Yannis Flet-Berliac; Deon R. Jordan; William Steenbergen; Emma Brunskill (NeurIPS, 2022)

Model-Based Offline Reinforcement Learning with Local Misspecification. - Kefan Dong; Yannis Flet-Berliac; Allen Nie; Emma Brunskill (AAAI, 2023)

Understanding the Impact of Reinforcement Learning Personalization on Subgroups of Students in Math Tutoring. - Allen Nie; Ann-Katrin Reuel; Emma Brunskill (AIED (Posters/Late Breaking Results/...), 2023)

Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets. - Anirudhan Badrinath; Yannis Flet-Berliac; Allen Nie; Emma Brunskill (NeurIPS, 2023)

MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks. - Allen Nie; Yuhui Zhang; Atharva Amdekar; Chris Piech; Tatsunori B. Hashimoto; Tobias Gerstenberg (NeurIPS, 2023)

Reinforcement Learning Tutor Better Supported Lower Performers in a Math Task. - Sherry Ruan; Allen Nie; William Steenbergen; Jiayu He; JQ Zhang; Meng Guo 006; Yao Liu 009; Kyle Dang Nguyen; Catherine Y. Wang; Rui Ying; James A. Landay; Emma Brunskill (CoRR, 2023)

LLF-Bench: Benchmark for Interactive Learning from Language Feedback. - Ching-An Cheng; Andrey Kolobov; Dipendra Misra; Allen Nie; Adith Swaminathan (CoRR, 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)

Estimating the Causal Treatment Effect of Unproductive Persistence. - Amelia Leon; Allen Nie; Yash Chandak; Emma Brunskill (LAK, 2024)

Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs. - Ching-An Cheng; Allen Nie; Adith Swaminathan (NeurIPS, 2024)

OPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple Estimators. - Allen Nie; Yash Chandak; Christina J. Yuan; Anirudhan Badrinath; Yannis Flet-Berliac; Emma Brunskill (NeurIPS, 2024)

A Fast and Accurate Machine Learning Autograder for the Breakout Assignment. - Evan Zheran Liu; David Yuan 001; Ahmed Ahmed; Elyse Cornwall; Juliette Woodrow; Kaylee Burns; Allen Nie; Emma Brunskill; Chris Piech; Chelsea Finn (SIGCSE (1), 2024)

The Importance of Directional Feedback for LLM-based Optimizers. - Allen Nie; Ching-An Cheng; Andrey Kolobov; Adith Swaminathan (CoRR, 2024)

Trace is the New AutoDiff - Unlocking Efficient Optimization of Computational Workflows. - Ching-An Cheng; Allen Nie; Adith Swaminathan (CoRR, 2024)

The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters Exam Performances. - Allen Nie; Yash Chandak; Miroslav Suzara; Ali Malik; Juliette Woodrow; Matt Peng; Mehran Sahami; Emma Brunskill; Chris Piech (CoRR, 2024)

EVOLvE: Evaluating and Optimizing LLMs For Exploration. - Allen Nie; Yi Su 008; Bo Chang 002; Jonathan N. Lee; Ed H. Chi; Quoc V. Le; Minmin Chen (CoRR, 2024)

Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers. - Anjiang Wei; Allen Nie; Thiago S. F. X. Teixeira; Rohan Yadav; Wonchan Lee; Ke Wang; Alex Aiken (CoRR, 2024)

Predicting Long Term Sequential Policy Value Using Softer Surrogates. - Hyunji Nam; Allen Nie; Ge Gao; Vasilis Syrgkanis; Emma Brunskill (CoRR, 2024)

On the Promising Path of Making Education Effective for Every Student. - Allen Nie (XRDS, 2024)

Reinforcement learning tutor better supported lower performers in a math task. - Sherry Ruan; Allen Nie; William Steenbergen; Jiayu He; J. Q. Zhang; Meng Guo 006; Yao Liu 009; Kyle Dang Nguyen; Catherine Y. Wang; Rui Ying; James A. Landay; Emma Brunskill (Mach. Learn., 2024)

Exploring the Benefit of Customizing Feedback Interventions For Educators and Students With Offline Contextual Multi-Armed Bandits. - Joy Yun; Allen Nie; Emma Brunskill; Dorottya Demszky (LAK, 2025)

Teaching Large Language Models to Reason through Learning and Forgetting. - Tianwei Ni; Allen Nie; Sapana Chaudhary; Yao Liu 009; Huzefa Rangwala; Rasool Fakoor (CoRR, 2025)

Provably Learning from Language Feedback. - Wanqiao Xu; Allen Nie; Ruijie Zheng; Aditya Modi 002; Adith Swaminathan; Ching-An Cheng (CoRR, 2025)

Assessing the Quality of AI-Generated Exams: A Large-Scale Field Study. - Calvin Isley; Joshua Gilbert; Evangelos Kassos; Michaela Kocher; Allen Nie; Emma Brunskill; Benjamin W. Domingue; Jake Hofman; Joscha Legewie; Teddy Svoronos; Charlotte Tuminelli; Sharad Goel (CoRR, 2025)