Zhang, Michael

On the Opportunities and Risks of Foundation Models

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 2,676

Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence

Chen, H.-T., Zhang, M., & Choi, E. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Topic ModelingInformation Retrieval and Search Behavior

Cited by 31

Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence

Chen, H.-T., Zhang, M. J. Q., & Choi, E. (2022) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 31

Selectively Answering Ambiguous Questions

Cole, J., Zhang, M., Gillick, D., Eisenschlos, J., Dhingra, B., & Eisenstein, J. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 19

Selectively Answering Ambiguous Questions

Cole, J. R., Zhang, M. J. Q., Gillick, D., Eisenschlos, J. M., Dhingra, B., & Eisenstein, J. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 19

Simple linear attention language models balance the recall-throughput tradeoff

Arora, S., Eyuboglu, S., Zhang, M., Timalsina, A., Alberti, S., Zinsley, D., Zou, J., Rudra, A., & Ré, C. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 5