Shieber, Stuart

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

Challenges in Data-to-Document Generation

Wiseman, S., Shieber, S., & Rush, A. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Topic ModelingMultimodal Machine Learning Applications

Cited by 524

Accountability of AI Under the Law: The Role of Explanation

Doshi-Velez, F., Kortz, M., Budish, R., Bavitz, C., Gershman, S. J., O'Brien, D., Scott, K., Shieber, S., Waldo, J., Weinberger, D., et al. (2017) · SSRN Electronic Journal

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 457

Lessons from a Restricted Turing Test

Shieber, S. M. (1994) · arXiv

Artificial Intelligence ApplicationsCybernetics and Technology in Society

Cited by 222

Don’t Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference

Belinkov, Y., Poliak, A., Shieber, S., Van Durme, B., & Rush, A. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 73

From Explicit CoT to Implicit CoT: Learning to Internalize CoT Step by Step

Deng, Y., Choi, Y., & Shieber, S. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3

Implicit Chain of Thought Reasoning via Knowledge Distillation

Deng, Y., Prasad, K., Fernandez, R., Smolensky, P., Chaudhary, V., & Shieber, S. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1