Mitchell, Tom

Machine learning: Trends, perspectives, and prospects

Jordan, M. I., & Mitchell, T. M. (2015) · Science

Machine Learning and AlgorithmsArtificial Intelligence Applications

Cited by 9,955

Text classification from labeled and unlabeled documents using EM

Nigam, K., Mccallum, A. K., Thrun, S., & Mitchell, T. (2000) · Machine Learning

Text and Document Classification TechnologiesMachine Learning and Algorithms

Cited by 2,736

Toward an architecture for never-ending language learning

Carlson, A., Betteridge, J., Kisiel, B., Settles, B., Hruschka, E., & Mitchell, T. (2010) · Proceedings of the AAAI Conference on Artificial Intelligence

Web Data Mining and AnalysisAI-based Problem Solving and Planning

Cited by 2,000

Machine learning classifiers and fMRI: A tutorial overview

Pereira, F., Mitchell, T., & Botvinick, M. (2009) · NeuroImage

Functional Brain Connectivity StudiesEEG and Brain-Computer Interfaces

Cited by 1,624

Explanation-Based Generalization: A Unifying View

Mitchell, T. M., Keller, R. M., & Kedar-Cabelli, S. T. (1986) · Machine Learning

AI-based Problem Solving and PlanningMachine Learning and Algorithms

Cited by 1,382

Predicting Human Brain Activity Associated with the Meanings of Nouns

Mitchell, T. M., Shinkareva, S. V., Carlson, A., Chang, K.-M., Malave, V. L., Mason, R. A., & Just, M. A. (2008) · Science

Neurobiology of Language and BilingualismCategorization, perception, and language

Cited by 1,180

What can machine learning do? Workforce implications

Brynjolfsson, E., & Mitchell, T. (2017) · Science

Ethics and Social Impacts of AILabor market dynamics and wage inequality

Cited by 1,131

What Can Machines Learn and What Does It Mean for Occupations and the Economy?

Brynjolfsson, E., Mitchell, T., & Rock, D. (2018) · AEA Papers and Proceedings

Labor market dynamics and wage inequalityDigital Economy and Work Transformation

Cited by 695

Leveraging Knowledge Bases in LSTMs for Improving Machine Reading

Yang, B., & Mitchell, T. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 261

Incorporating Vector Space Similarity in Random Walk Inference over Knowledge Bases

Gardner, M., Talukdar, P., Krishnamurthy, J., & Mitchell, T. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingAdvanced Graph Neural Networks

Cited by 189

The Internal State of an LLM Knows When It's Lying

Azaria, A., & Mitchell, T. (2023) · arXiv

Misinformation and Its ImpactsTopic Modeling

Cited by 179

The Internal State of an LLM Knows When It’s Lying

Azaria, A., & Mitchell, T. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023

Misinformation and Its ImpactsTopic Modeling

Cited by 175

Protecting scientific integrity in an age of generative AI

Blau, W., Cerf, V. G., Enriquez, J., Francisco, J. S., Gasser, U., Gray, M. L., Greaves, M., Grosz, B. J., Jamieson, K. H., Haug, G. H., et al. (2024) · Proceedings of the National Academy of Sciences

Academic integrity and plagiarismEthics and Social Impacts of AI

Cited by 118

Aligning context-based statistical models of language with brain activity during reading

Wehbe, L., Vaswani, A., Knight, K., & Mitchell, T. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Neurobiology of Language and BilingualismReading and Literacy Development

Cited by 95

Instructable Intelligent Personal Agent

Azaria, A., Krishnamurthy, J., & Mitchell, T. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 70

Plan, Eliminate, and Track - Language Models are Good Teachers for Embodied Agents

Wu, Y., Min, S. Y., Bisk, Y., Salakhutdinov, R., Azaria, A., Li, Y., Mitchell, T., & Prabhumoye, S. (2023) · arXiv

AI-based Problem Solving and PlanningReinforcement Learning in Robotics

Cited by 7

SmartPlay: A Benchmark for LLMs as Intelligent Agents

Wu, Y., Tang, X., Mitchell, T. M., & Li, Y. (2023) · arXiv

Artificial Intelligence in GamesAI-based Problem Solving and Planning

Cited by 6