Manning, Christopher D.

DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature

Mitchell, E., Lee, Y., Khazatsky, A., Manning, C. D., & Finn, C. (2023) · arXiv

Authorship Attribution and ProfilingDigital Media Forensic Detection

Cited by 151

Do Massively Pretrained Language Models Make Better Storytellers?

See, A., Pappu, A., Saxena, R., Yerukola, A., & Manning, C. D. (2019) · Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)

Topic ModelingNatural Language Processing Techniques

Cited by 139

Learning Language Games through Interaction

Wang, S. I., Liang, P., & Manning, C. D. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 132

Learning to Summarize Radiology Findings

Zhang, Y., Ding, D. Y., Qian, T., Manning, C. D., & Langlotz, C. P. (2018) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 126

Learning to Summarize Radiology Findings

Zhang, Y., Ding, D. Y., Qian, T., Manning, C. D., & Langlotz, C. P. (2018) · Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 126

Just ask for calibration: Strategies for eliciting calibrated confidence scores from language models fine-tuned with human feedback

Tian, K., Mitchell, E., Zhou, A., Sharma, A., Rafailov, R., Yao, H., Finn, C., & Manning, C. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 123

Biomedical and clinical English model packages for the Stanza Python NLP library

Zhang, Y., Zhang, Y., Qi, P., Manning, C. D., & Langlotz, C. P. (2021) · Journal of the American Medical Informatics Association

Biomedical Text Mining and OntologiesNatural Language Processing Techniques

Cited by 112

HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Yang, Z., Qi, P., Zhang, S., Bengio, Y., Cohen, W. W., Salakhutdinov, R., & Manning, C. D. (2018) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 97

Fast Model Editing at Scale

Mitchell, E., Lin, C., Bosselut, A., Finn, C., & Manning, C. D. (2021) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 95

Quantifying large language model usage in scientific papers

Liang, W., Zhang, Y., Wu, Z., Lepp, H., Ji, W., Zhao, X., Cao, H., Liu, S., He, S., Huang, Z., et al. (2025) · Nature Human Behaviour

scientometrics and bibliometrics researchAcademic Writing and Publishing

Cited by 80

Human Effort and Machine Learnability in Computer Aided Translation

Green, S., Wang, S. I., Chuang, J., Heer, J., Schuster, S., & Manning, C. D. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Natural Language Processing TechniquesTranslation Studies and Practices

Cited by 68

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Henderson, P., Krass, M., Zheng, L., Guha, N., Manning, C. D., Jurafsky, D., & Ho, D. (2022) · Advances in Neural Information Processing Systems 35

Artificial Intelligence in LawEthics and Social Impacts of AI

Cited by 62

Naturalizing a Programming Language via Interactive Learning

Wang, S. I., Ginn, S., Liang, P., & Manning, C. D. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesSpeech and dialogue systems

Cited by 59

MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions

Zhong, Z., Wu, Z., Manning, C. D., Potts, C., & Chen, D. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 55

Mapping the Increasing Use of LLMs in Scientific Papers

Liang, W., Zhang, Y., Wu, Z., Lepp, H., Ji, W., Zhao, X., Cao, H., Liu, S., He, S., Huang, Z., et al. (2024) · arXiv

scientometrics and bibliometrics researchAcademic Writing and Publishing

Cited by 55

Memory-Based Model Editing at Scale

Mitchell, E., Lin, C., Bosselut, A., Manning, C. D., & Finn, C. (2022) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 51

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Henderson, P., Krass, M. S., Zheng, L., Guha, N., Manning, C. D., Jurafsky, D., & Ho, D. E. (2022) · arXiv

Artificial Intelligence in LawEthics and Social Impacts of AI

Cited by 49

Measuring machine translation quality as semantic equivalence: A metric based on entailment features

Padó, S., Cer, D., Galley, M., Jurafsky, D., & Manning, C. D. (2009) · Machine Translation

Natural Language Processing TechniquesTopic Modeling

Cited by 47

Sceneseer:3d scene design with natural language.

Chang, A. X., Eric, M., Savva, M., & Manning, C. D. (2017) · arXiv

3D Shape Modeling and AnalysisComputer Graphics and Visualization Techniques

Cited by 38

Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Magesh, V., Surani, F., Dahl, M., Suzgun, M., Manning, C. D., & Ho, D. E. (2024) · arXiv

Artificial Intelligence in LawTopic Modeling

Cited by 37

RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

Sarthi, P., Abdullah, S., Tuli, A., Khanna, S., Goldie, A., & Manning, C. D. (2024) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 36

Stay Hungry, Stay Focused: Generating Informative and Specific Questions in Information-Seeking Conversations

Qi, P., Zhang, Y., & Manning, C. D. (2020) · Findings of the Association for Computational Linguistics: EMNLP 2020

Speech and dialogue systemsTopic Modeling

Cited by 23

The EOS Decision and Length Extrapolation

Newman, B., Hewitt, J., Liang, P., & Manning, C. D. (2020) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 22

Fine-tuning Language Models for Factuality

Tian, K., Mitchell, E., Yao, H., Manning, C. D., & Finn, C. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 14