Lang Yu / 余浪
Meta
Email: langyu at meta dot com
I am a Research Scientist at Meta. I am building privacy-preserving ML systems for Facebook Ads. I got my Phd in Computer Science at the University of Chicago. I do research on NLP and machine learning. I was very fortunate to be advised by Prof. Allyson Ettinger. My research focus on composition and interpretability in neural language models.Latest CV
Education
Ph.D. in Computer Science, June 2021
Advisor: Prof. Allyson Ettinger
Committee: Prof. Allyson Ettinger, Prof. Yuxin Chen and Prof. Rebecca Willett
M.S. in Computer Science, June, 2019
Advisor: Prof. John Goldsmith
News
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September 2023 Joined Ads Core ML Content Understanding team.
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July 2023 New paper “Counterfactual reasoning: Testing language models’ understanding of hypothetical scenarios” presented at ACL 2023.
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December 2022. “Counterfactual reasoning: Do language models need world knowledge for causal understanding?” presented at nCSI workshop at NeurIPS 2022.
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October 2022. New paper ““No, They Did Not”: Dialogue Response Dynamics in Pre-trained Language Models” presented at COLING 2022.
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September 2021. Begun my position as Research Scientist at Meta Seattle.
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August 2021. Presented at Rep4NLP workshop about my ACL Findings paper “On the Interplay Between Fine-tuning and Composition in Transformers”.
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June 2021. Officially got my Ph.D.!
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April 2021. Defended my Phd dissertation “Analyzing and Improving Compositionality in Neural Language Models”!
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November 2020. Presented at EMNLP 2020 about my paper “Assessing Phrasal Representation and Composition in Transformers”.
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October 2020. I have accepted a position as Research Scientist at Facebook.
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June 2020. Started a machine learning internship at Facebook Seattle. I was on Public Connections team, working on “Public Figures to Follow” (PFTF).
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June 2019. Started a machine learning internship at Facebook Seattle. I was on Page Connections team, working on “People You May Follow” (PYML).
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January 2019. Passed my MS thesis defense! MS thesis: “Unsupervised Vocabulary Expansion With Hierarchical Signature Structure”