Ian Tenney
6 papers in the PaperMetrix corpus
Papers by this author
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What Happens To BERT Embeddings During Fine-tuning?
2020
While much recent work has examined how linguistic information is encoded in pretrained sentence representations, comparatively little is understood about how these models change when adapted to solve downstream tasks.
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The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models
2020 · arXiv (Cornell University)
We present the Language Interpretability Tool (LIT), an open-source platform for visualization and understanding of NLP models. We focus on core questions about model behavior: Why did my model make this prediction? When does it …
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Probing What Different NLP Tasks Teach Machines about Function Word Comprehension
2019
Najoung Kim, Roma Patel, Adam Poliak, Patrick Xia, Alex Wang, Tom McCoy, Ian Tenney, Alexis Ross, Tal Linzen, Benjamin Van Durme, Samuel R. Bowman, Ellie Pavlick. Proceedings of the Eighth Joint Conference on Lexical and …
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BERT Rediscovers the Classical NLP Pipeline
2019
Pre-trained text encoders have rapidly advanced the state of the art on many NLP tasks. We focus on one such model, BERT, and aim to quantify where linguistic information is captured within the network. We …
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Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling
2019
Alex Wang, Jan Hula, Patrick Xia, Raghavendra Pappagari, R. Thomas McCoy, Roma Patel, Najoung Kim, Ian Tenney, Yinghui Huang, Katherin Yu, Shuning Jin, Berlin Chen, Benjamin Van Durme, Edouard Grave, Ellie Pavlick, Samuel R. Bowman. …
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What do you learn from context? Probing for sentence structure in\n contextualized word representations
2019 · arXiv (Cornell University)
Contextualized representation models such as ELMo (Peters et al., 2018a) and\nBERT (Devlin et al., 2018) have recently achieved state-of-the-art results on a\ndiverse array of downstream NLP tasks. Building on recent token-level probing\nwork, we introduce a …