Aman Madaan

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Yiming YangProfessor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Niket TandonSenior Research Scientist, Allen Institute for AIVerified email at allenai.org
Graham NeubigCarnegie Mellon UniversityVerified email at cs.cmu.edu
Peter ClarkAllen Institute for Artificial Intelligence (AI2)Verified email at allenai.org
Uri AlonResearch Scientist, Google DeepMindVerified email at cs.cmu.edu
Shrimai PrabhumoyeSenior Research Scientist @NVIDIA and Adjunct Assistant Professor @Boston UniversityVerified email at nvidia.com
Amir YazdanbakhshResearch Scientist at Google DeepMindVerified email at google.com
Shuyan ZhouCarnegie Mellon UniversityVerified email at cs.cmu.edu
Luyu GaoCarnegie Mellon UniversityVerified email at cs.cmu.edu
Dheeraj RajagopalResearch ScientistVerified email at google.com
Alan W BlackProfessor, Language Technologies Institute, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Amrith SetlurMachine Learning Department, CMUVerified email at cs.cmu.edu
Tanmay ParekhStudent, University of California Los AngelesVerified email at ucla.edu
Eduard HovyUniversity of Melbourne, CMUVerified email at andrew.cmu.edu
Pengfei LiuAssociate professor at Shanghai Jiaotong UniversityVerified email at andrew.cmu.edu
Nouha DziriResearch Scientist at AI2Verified email at allenai.org
Prakhar GuptaCarnegie Mellon University, Language Technologies InstituteVerified email at cmu.edu
Skyler HallinanUndergraduate StudentVerified email at uw.edu
Sean J WelleckPostdoctoral scholar, University of WashingtonVerified email at uw.edu
Bodhisattwa Prasad MajumderResearcher, Allen Institute for AIVerified email at allenai.org

Aman Madaan

Carnegie Mellon University

Verified email at cs.cmu.edu - Homepage

Large Language Models Machine Learning Natural Language Processing Code Generation Commonsense Reasoning


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PAL: Program-aided Language Models L Gao, A Madaan, S Zhou*, U Alon, P Liu, Y Yang, J Callan, G Neubig ICML 2023, 2022	199	2022
Self-refine: Iterative refinement with self-feedback A Madaan, N Tandon, P Gupta, S Hallinan, L Gao, S Wiegreffe, U Alon, ... arXiv preprint arXiv:2303.17651, 2023	177	2023
Politeness transfer: A tag and generate approach A Madaan, A Setlur, T Parekh, B Poczos, G Neubig, Y Yang, ... ACL 2020, 2020	146	2020
The gem benchmark: Natural language generation, its evaluation and metrics S Gehrmann, T Adewumi, K Aggarwal, PS Ammanamanchi, ... arXiv preprint arXiv:2102.01672, 2021	118	2021
Language models of code are few-shot commonsense learners A Madaan, S Zhou, U Alon, Y Yang, G Neubig Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022	67	2022
Numerical Relation Extraction with Minimal Supervision A Madaan, A Mittal, G Ramakrishnan, S Sarawagi Thirtieth AAAI Conference on Artificial Intelligence, 2016	64	2016
Memory-assisted prompt editing to improve GPT-3 after deployment A Madaan, N Tandon, P Clark, Y Yang Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022	44	2022
Text and patterns: For effective chain of thought, it takes two to tango A Madaan, A Yazdanbakhsh EMNLP 2023 (Findings), 2022	36	2022
RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs AF Akyürek, E Akyürek, A Madaan, A Kalyan, P Clark, D Wijaya, ... arXiv preprint arXiv:2305.08844, 2023	20	2023
Learning to repair: Repairing model output errors after deployment using a dynamic memory of feedback N Tandon, A Madaan, P Clark, Y Yang Findings of the Association for Computational Linguistics: NAACL 2022, 339--352, 2022	20*	2022
Learning performance-improving code edits A Madaan, A Shypula, U Alon, M Hashemi, P Ranganathan, Y Yang, ... Deep Learning For Code, ICLR 2023, 2023	19	2023
Bridging the gap: A survey on integrating (human) feedback for natural language generation P Fernandes, A Madaan, E Liu, A Farinhas, PH Martins, A Bertsch, ... TACL, 2023	18	2023
Eigen: Event influence generation using pre-trained language models A Madaan, D Rajagopal, Y Yang, A Ravichander, E Hovy, S Prabhumoye Commonsense Representation and Reasoning Workshop (CSRR), ACL 2022, 2020	18*	2020
Think about it! Improving defeasible reasoning by first modeling the question scenario A Madaan, N Tandon, D Rajagopal, P Clark, Y Yang, E Hovy EMNLP 2021, 2021	14	2021
Neural language modeling for contextualized temporal graph generation A Madaan, Y Yang NAACL 2021, 2020	11	2020
Gemv2: Multilingual nlg benchmarking in a single line of code S Gehrmann, A Bhattacharjee, A Mahendiran, A Wang, A Papangelis, ... arXiv preprint arXiv:2206.11249, 2022	7	2022
Could you give me a hint? Generating inference graphs for defeasible reasoning A Madaan, D Rajagopal, N Tandon, Y Yang, E Hovy ACL 2021 (Findings), 2021	7	2021
Improving neural model performance through natural language feedback on their explanations A Madaan, N Tandon, D Rajagopal, Y Yang, P Clark, K Sakaguchi, ... arXiv preprint arXiv:2104.08765, 2021	6	2021
Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning with LLMs P Aggarwal, A Madaan, Y Yang EMNLP 2023, 2023	3	2023
System and method for automatic generation of extract, transform, load (etl) asserts K Ramanathan, G Ronanki, A Madaan US Patent App. 16/851,869, 2020	3	2020

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