Key-Value Memory Networks for Directly Reading Documents. - Alexander H. Miller; Adam Fisch; Jesse Dodge; Amir-Hossein Karimi; Antoine Bordes; Jason Weston (EMNLP, 2016)

Reading Wikipedia to Answer Open-Domain Questions. - Danqi Chen 001; Adam Fisch; Jason Weston; Antoine Bordes (ACL (1), 2017)

ParlAI: A Dialog Research Software Platform. - Alexander H. Miller; Will Feng; Dhruv Batra; Antoine Bordes; Adam Fisch; Jiasen Lu; Devi Parikh; Jason Weston (EMNLP (System Demonstrations), 2017)

StarSpace: Embed All The Things! - Ledell Yu Wu; Adam Fisch; Sumit Chopra; Keith Adams; Antoine Bordes; Jason Weston (AAAI, 2018)

MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension. - Adam Fisch; Alon Talmor; Robin Jia; Minjoon Seo; Eunsol Choi; Danqi Chen 001 (MRQA@EMNLP, 2019)

Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers. - Adam Fisch; Jiang Guo; Regina Barzilay (EMNLP/IJCNLP (1), 2019)

CapWAP: Image Captioning with a Purpose. - Adam Fisch; Kenton Lee; Ming-Wei Chang; Jonathan H. Clark; Regina Barzilay (EMNLP (1), 2020)

Relaxed Conformal Prediction Cascades for Efficient Inference Over Many Labels. - Adam Fisch; Tal Schuster; Tommi S. Jaakkola; Regina Barzilay (CoRR, 2020)

CapWAP: Captioning with a Purpose. - Adam Fisch; Kenton Lee; Ming-Wei Chang; Jonathan H. Clark; Regina Barzilay (CoRR, 2020)

Making Pre-trained Language Models Better Few-shot Learners. - Tianyu Gao 001; Adam Fisch; Danqi Chen 001 (ACL/IJCNLP (1), 2021)

Consistent Accelerated Inference via Confident Adaptive Transformers. - Tal Schuster; Adam Fisch; Tommi S. Jaakkola; Regina Barzilay (EMNLP (1), 2021)

Efficient Conformal Prediction via Cascaded Inference with Expanded Admission. - Adam Fisch; Tal Schuster; Tommi S. Jaakkola; Regina Barzilay (ICLR, 2021)

Few-Shot Conformal Prediction with Auxiliary Tasks. - Adam Fisch; Tal Schuster; Tommi S. Jaakkola; Regina Barzilay (ICML, 2021)

Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence. - Tal Schuster; Adam Fisch; Regina Barzilay (NAACL-HLT, 2021)

Conformal Prediction Sets with Limited False Positives. - Adam Fisch; Tal Schuster; Tommi S. Jaakkola; Regina Barzilay (ICML, 2022)

Confident Adaptive Language Modeling. - Tal Schuster; Adam Fisch; Jai Gupta 001; Mostafa Dehghani 001; Dara Bahri; Vinh Tran 002; Yi Tay; Donald Metzler (NeurIPS, 2022)

Calibrated Selective Classification. - Adam Fisch; Tommi S. Jaakkola; Regina Barzilay (Trans. Mach. Learn. Res., 2022)

Efficiently Controlling Multiple Risks with Pareto Testing. - Bracha Laufer-Goldshtein; Adam Fisch; Regina Barzilay; Tommi S. Jaakkola (ICLR, 2023)

Towards Robust and Efficient Continual Language Learning. - Adam Fisch; Amal Rannen-Triki; Razvan Pascanu; Jörg Bornschein; Angeliki Lazaridou; Elena Gribovskaya; Marc'Aurelio Ranzato (CoRR, 2023)

Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking. - Jacob Eisenstein; Chirag Nagpal; Alekh Agarwal; Ahmad Beirami; Alex D'Amour; Dj Dvijotham; Adam Fisch; Katherine A. Heller; Stephen Pfohl; Deepak Ramachandran; Peter Shaw 004; Jonathan Berant (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)

Conformal Methods for Efficient and Reliable Deep Learning - Adam Fisch (2023)

Conformal Risk Control. - Anastasios Nikolas Angelopoulos; Stephen Bates; Adam Fisch; Lihua Lei; Tal Schuster (ICLR, 2024)

Conformal Language Modeling. - Victor Quach; Adam Fisch; Tal Schuster; Adam Yala; Jae Ho Sohn; Tommi S. Jaakkola; Regina Barzilay (ICLR, 2024)

Stratified Prediction-Powered Inference for Effective Hybrid Evaluation of Language Models. - Adam Fisch; Joshua Maynez; R. Alex Hofer; Bhuwan Dhingra; Amir Globerson; William W. Cohen (NeurIPS, 2024)

Block Transformer: Global-to-Local Language Modeling for Fast Inference. - Namgyu Ho; Sangmin Bae; Taehyeon Kim 001; Hyunjik Jo; Yireun Kim; Tal Schuster; Adam Fisch; James Thorne; Se-Young Yun (NeurIPS, 2024)

Mitigating LLM Hallucinations via Conformal Abstention. - Yasin Abbasi-Yadkori; Ilja Kuzborskij; David Stutz; András György 001; Adam Fisch; Arnaud Doucet; Iuliya Beloshapka; Wei-Hung Weng; Yao-Yuan Yang; Csaba Szepesvári; Ali Taylan Cemgil; Nenad Tomasev (CoRR, 2024)

Bayesian Prediction-Powered Inference. - R. Alex Hofer; Joshua Maynez; Bhuwan Dhingra; Adam Fisch; Amir Globerson; William W. Cohen (CoRR, 2024)

Robust Preference Optimization through Reward Model Distillation. - Adam Fisch; Jacob Eisenstein; Vicky Zayats; Alekh Agarwal; Ahmad Beirami; Chirag Nagpal; Petet Shaw; Jonathan Berant (CoRR, 2024)

Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation. - Adam Fisch; Joshua Maynez; R. Alex Hofer; Bhuwan Dhingra; Amir Globerson; William W. Cohen (CoRR, 2024)

Risk-Controlling Model Selection via Guided Bayesian Optimization. - Bracha Laufer-Goldshtein; Adam Fisch; Regina Barzilay; Tommi S. Jaakkola (Trans. Mach. Learn. Res., 2024)

Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA. - Sangmin Bae; Adam Fisch; Hrayr Harutyunyan; Ziwei Ji; Seungyeon Kim 001; Tal Schuster (ICLR, 2025)

Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning. - Amrith Setlur; Chirag Nagpal; Adam Fisch; Xinyang Geng; Jacob Eisenstein; Rishabh Agarwal; Alekh Agarwal; Jonathan Berant; Aviral Kumar (ICLR, 2025)

Robust Preference Optimization through Reward Model Distillation. - Adam Fisch; Jacob Eisenstein; Vicky Zayats; Alekh Agarwal; Ahmad Beirami; Chirag Nagpal; Peter Shaw 004; Jonathan Berant (Trans. Mach. Learn. Res., 2025)

Mitigating Preference Hacking in Policy Optimization with Pessimism. - Dhawal Gupta; Adam Fisch; Christoph Dann; Alekh Agarwal (CoRR, 2025)

Don't lie to your friends: Learning what you know from collaborative self-play. - Jacob Eisenstein; Reza Aghajani; Adam Fisch; Dheeru Dua; Fantine Huot; Mirella Lapata; Vicky Zayats; Jonathan Berant (CoRR, 2025)

Cost-Optimal Active AI Model Evaluation. - Anastasios N. Angelopoulos; Jacob Eisenstein; Jonathan Berant; Alekh Agarwal; Adam Fisch (CoRR, 2025)

Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation. - Sangmin Bae; Yujin Kim; Reza Bayat; Sungnyun Kim; Jiyoun Ha; Tal Schuster; Adam Fisch; Hrayr Harutyunyan; Ziwei Ji; Aaron Courville; Se-Young Yun (CoRR, 2025)