James Wexler

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 26

Top Topics

Interactive Visualizations

Top Venues

IEEE Trans. Vis. Comput. Graph.

CHI Extended Abstracts

Publications

Crystal Qian, James Wexler
Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI Collaboration. IUI (2024)
Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, Lucas Dixon
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models. CoRR (2024)
Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, Lucas Dixon
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models. CHI Extended Abstracts (2024)
Emily Reif, Crystal Qian, James Wexler, Minsuk Kahng
Automatic Histograms: Leveraging Language Models for Text Dataset Exploration. CHI Extended Abstracts (2024)
Crystal Qian, James Wexler
Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI Collaboration. CoRR (2024)
Savvas Petridis, Ben Wedin, Ann Yuan, James Wexler, Nithum Thain
ConstitutionalExperts: Training a Mixture of Principle-based Prompts. CoRR (2024)
Emily Reif, Crystal Qian, James Wexler, Minsuk Kahng
Automatic Histograms: Leveraging Language Models for Text Dataset Exploration. CoRR (2024)
Savvas Petridis, Benjamin D. Wedin, James Wexler, Mahima Pushkarna, Aaron Donsbach, Nitesh Goyal, Carrie J. Cai, Michael Terry
ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles. IUI (2024)
Narges Ashtari, Ryan Mullins, Crystal Qian, James Wexler, Ian Tenney, Mahima Pushkarna
From Discovery to Adoption: Understanding the ML Practitioners' Interpretability Journey. Conference on Designing Interactive Systems (2023)
Savvas Petridis, Ben Wedin, James Wexler, Aaron Donsbach, Mahima Pushkarna, Nitesh Goyal, Carrie J. Cai, Michael Terry
ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles. CoRR (2023)
Leon Sixt, Evan Zheran Liu, Marie Pellat, James Wexler, Milad Hashemi, Been Kim, Martin Maas
Analyzing a Caching Model. CoRR (2021)
Jessica Schrouff, Sebastien Baur, Shaobo Hou, Diana Mincu, Eric Loreaux, Ralph Blanes, James Wexler, Alan Karthikesalingam, Been Kim
Best of both worlds: local and global explanations with human-understandable concepts. CoRR (2021)
James Wexler, Mahima Pushkarna, Sara Robinson, Tolga Bolukbasi, Andrew Zaldivar
Probing ML models for fairness with the what-if tool and SHAP: hands-on tutorial. FAT* (2020)
James Wexler, Mahima Pushkarna, Tolga Bolukbasi, Martin Wattenberg, Fernanda B. Viégas, Jimbo Wilson
The What-If Tool: Interactive Probing of Machine Learning Models. IEEE Trans. Vis. Comput. Graph. 26 (1) (2020)
Ian Tenney, James Wexler, Jasmijn Bastings, Tolga Bolukbasi, Andy Coenen, Sebastian Gehrmann, Ellen Jiang, Mahima Pushkarna, Carey Radebaugh, Emily Reif, Ann Yuan
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models. EMNLP (Demos) (2020)
Ian Tenney, James Wexler, Jasmijn Bastings, Tolga Bolukbasi, Andy Coenen, Sebastian Gehrmann, Ellen Jiang, Mahima Pushkarna, Carey Radebaugh, Emily Reif, Ann Yuan
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models. CoRR (2020)
James Wexler, Mahima Pushkarna, Tolga Bolukbasi, Martin Wattenberg, Fernanda B. Viégas, Jimbo Wilson
The What-If Tool: Interactive Probing of Machine Learning Models. CoRR (2019)
Amirata Ghorbani, James Wexler, James Y. Zou, Been Kim
Towards Automatic Concept-based Explanations. NeurIPS (2019)
Cheng-Zhi Anna Huang, Curtis Hawthorne, Adam Roberts, Monica Dinculescu, James Wexler, Leon Hong, Jacob Howcroft
The Bach Doodle: Approachable music composition with machine learning at scale. CoRR (2019)
Cheng-Zhi Anna Huang, Curtis Hawthorne, Adam Roberts, Monica Dinculescu, James Wexler, Leon Hong, Jacob Howcroft
Approachable Music Composition with Machine Learning at Scale. ISMIR (2019)
Amirata Ghorbani, James Wexler, Been Kim
Automating Interpretability: Discovering and Testing Visual Concepts Learned by Neural Networks. CoRR (2019)
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Michaela Hardt, Peter J. Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Yi Zhang, Gerardo Flores, Gavin E. Duggan, Jamie Irvine, Quoc Le, Kurt Litsch, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Gregory S. Corrado, Jeffrey Dean
Scalable and accurate deep learning with electronic health records. npj Digit. Medicine 1 (2018)
Been Kim, Martin Wattenberg, Justin Gilmer, Carrie J. Cai, James Wexler, Fernanda B. Viégas, Rory Sayres
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV). ICML (2018)
Marzyeh Ghassemi, Mahima Pushkarna, James Wexler, Jesse Johnson, Paul Varghese
ClinicalVis: Supporting Clinical Task-Focused Design Evaluation. CoRR (2018)
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Peter J. Liu, Xiaobing Liu, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Gavin E. Duggan, Gerardo Flores, Michaela Hardt, Jamie Irvine, Quoc V. Le, Kurt Litsch, Jake Marcus, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael Howell, Claire Cui, Greg Corrado, Jeff Dean
Scalable and accurate deep learning for electronic health records. CoRR (2018)
Kanit Wongsuphasawat, Daniel Smilkov, James Wexler, Jimbo Wilson, Dandelion Mané, Doug Fritz, Dilip Krishnan, Fernanda B. Viégas, Martin Wattenberg
Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow. IEEE Trans. Vis. Comput. Graph. 24 (1) (2018)