Madaan, Aman

Self-Refine: Iterative Refinement with Self-Feedback

Madaan, A., Tandon, N., Gupta, P., Hallinan, S., Gao, L., Wiegreffe, S., Alon, U., Dziri, N., Prabhumoye, S., Yang, Y., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2,314

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Gehrmann, S., Adewumi, T., Aggarwal, K., Ammanamanchi, P. S., Aremu, A., Bosselut, A., Chandu, K. R., Clinciu, M.-A., Das, D., Dhole, K., et al. (2021) · Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021)

Natural Language Processing TechniquesTopic Modeling

Cited by 159

PAL: Program-aided Language Models

Gao, L., Madaan, A., Zhou, S., Alon, U., Liu, P., Yang, Y., Callan, J., & Neubig, G. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 155

Learning Performance-Improving Code Edits

Shypula, A., Madaan, A., Zeng, Y., Alon, U., Gardner, J., Hashemi, M., Neubig, G., Ranganathan, P., Bastani, O., & Yazdanbakhsh, A. (2023) · arXiv

Software Engineering ResearchParallel Computing and Optimization Techniques

Cited by 146

Memory-assisted prompt editing to improve GPT-3 after deployment

Madaan, A., Tandon, N., Clark, P., & Yang, Y. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 60

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Gehrmann, S., Adewumi, T., Aggarwal, K., Ammanamanchi, P. S., Anuoluwapo, A., Bosselut, A., Chandu, K. R., Clinciu, M., Das, D., Dhole, K. D., et al. (2021) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 49

Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation

Fernandes, P., Madaan, A., Liu, E., Farinhas, A., Martins, P. H., Bertsch, A., de Souza, J. G. C., Zhou, S., Wu, T., Neubig, G., et al. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 44

Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango

Madaan, A., & Yazdanbakhsh, A. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 24

Learning to Repair: Repairing model output errors after deployment using a dynamic memory of feedback

Tandon, N., Madaan, A., Clark, P., & Yang, Y. (2021) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 19

AutoMix: Automatically Mixing Language Models

Aggarwal, P., Madaan, A., Anand, A., Potharaju, S. P., Mishra, S., Zhou, P., Gupta, A., Rajagopal, D., Kappaganthu, K., Yang, Y., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 19

How FaR Are Large Language Models From Agents with Theory-of-Mind?

Zhou, P., Madaan, A., Potharaju, S. P., Gupta, A., McKee, K. R., Holtzman, A., Pujara, J., Ren, X., Mishra, S., Nematzadeh, A., et al. (2023) · arXiv

Topic ModelingChild and Animal Learning Development

Cited by 6

RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs

Akyürek, A. F., Akyürek, E., Madaan, A., Kalyan, A., Clark, P., Wijaya, D., & Tandon, N. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4