James Wexler - RankMe

33 papers A* 2A 4Journal 20Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Choose Your Agent: Tradeoffs in Adopting AI Advisors, Coaches, and Delegates in Multi-Party Negotiation. CoRR Kehang Zhu, Nithum Thain, Vivian Tsai, James Wexler, Crystal Qian
2026	A	`conf`	Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargaining. IUI Crystal Qian, Kehang Zhu, John Joseph Horton, Benjamin S. Manning, Vivian Tsai, James Wexler, Nithum Thain
2025	—	`conf`	LLM Adoption in Data Curation Workflows: Industry Practices and Insights. CHI Extended Abstracts Crystal Qian, Michael Xieyang Liu, Emily Reif, Grady Simon, Nada Hussein, Nathan Clement, James Wexler, Carrie J. Cai, Michael Terry, Minsuk Kahng
2025	J	`jnl`	LLM Comparator: Interactive Analysis of Side-by-Side Evaluation of Large Language Models. IEEE Trans. Vis. Comput. Graph. Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, Lucas Dixon
2025	J	`jnl`	Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargaining. CoRR Crystal Qian, Kehang Zhu, John J. Horton, Benjamin S. Manning, Vivian Tsai, James Wexler, Nithum Thain
2024	—	`conf`	Automatic Histograms: Leveraging Language Models for Text Dataset Exploration. CHI Extended Abstracts Emily Reif, Crystal Qian, James Wexler, Minsuk Kahng
2024	J	`jnl`	Automatic Histograms: Leveraging Language Models for Text Dataset Exploration. CoRR Emily Reif, Crystal Qian, James Wexler, Minsuk Kahng
2024	A	`conf`	ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles. IUI Savvas Petridis, Benjamin D. Wedin, James Wexler, Mahima Pushkarna, Aaron Donsbach, Nitesh Goyal, Carrie J. Cai, Michael Terry
2024	—	`conf`	ConstitutionalExperts: Training a Mixture of Principle-based Prompts. ACL (Short Papers) Savvas Petridis, Ben Wedin, Ann Yuan, James Wexler, Nithum Thain
2024	J	`jnl`	ConstitutionalExperts: Training a Mixture of Principle-based Prompts. CoRR Savvas Petridis, Ben Wedin, Ann Yuan, James Wexler, Nithum Thain
2024	—	`conf`	LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models. CHI Extended Abstracts Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, Lucas Dixon
2024	J	`jnl`	LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models. CoRR Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, Lucas Dixon
2024	A	`conf`	Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI Collaboration. IUI Crystal Qian, James Wexler
2024	J	`jnl`	Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI Collaboration. CoRR Crystal Qian, James Wexler
2024	J	`jnl`	The Evolution of LLM Adoption in Industry Data Curation Practices. CoRR Crystal Qian, Michael Xieyang Liu, Emily Reif, Grady Simon, Nada Hussein, Nathan Clement, James Wexler, Carrie J. Cai, Michael Terry, Minsuk Kahng
2023	J	`jnl`	ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles. CoRR Savvas Petridis, Ben Wedin, James Wexler, Aaron Donsbach, Mahima Pushkarna, Nitesh Goyal, Carrie J. Cai, Michael Terry
2023	A	`conf`	From Discovery to Adoption: Understanding the ML Practitioners' Interpretability Journey. Conference on Designing Interactive Systems Narges Ashtari, Ryan Mullins, Crystal Qian, James Wexler, Ian Tenney, Mahima Pushkarna
2021	J	`jnl`	Analyzing a Caching Model. CoRR Leon Sixt, Evan Zheran Liu, Marie Pellat, James Wexler, Milad Hashemi, Been Kim, Martin Maas
2021	J	`jnl`	Best of both worlds: local and global explanations with human-understandable concepts. CoRR Jessica Schrouff, Sebastien Baur, Shaobo Hou, Diana Mincu, Eric Loreaux, Ralph Blanes, James Wexler, Alan Karthikesalingam, Been Kim
2020	—	`conf`	Probing ML models for fairness with the what-if tool and SHAP: hands-on tutorial. FAT* James Wexler, Mahima Pushkarna, Sara Robinson, Tolga Bolukbasi, Andrew Zaldivar
2020	—	`conf`	The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models. EMNLP (Demos) Ian Tenney, James Wexler, Jasmijn Bastings, Tolga Bolukbasi, Andy Coenen, Sebastian Gehrmann, Ellen Jiang, Mahima Pushkarna, Carey Radebaugh, Emily Reif, Ann Yuan
2020	J	`jnl`	The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models. CoRR Ian Tenney, James Wexler, Jasmijn Bastings, Tolga Bolukbasi, Andy Coenen, Sebastian Gehrmann, Ellen Jiang, Mahima Pushkarna, Carey Radebaugh, Emily Reif, Ann Yuan
2020	J	`jnl`	The What-If Tool: Interactive Probing of Machine Learning Models. IEEE Trans. Vis. Comput. Graph. James Wexler, Mahima Pushkarna, Tolga Bolukbasi, Martin Wattenberg, Fernanda B. Viégas, Jimbo Wilson
2019	—	`conf`	Approachable Music Composition with Machine Learning at Scale. ISMIR Cheng-Zhi Anna Huang, Curtis Hawthorne, Adam Roberts, Monica Dinculescu, James Wexler, Leon Hong, Jacob Howcroft
2019	J	`jnl`	Automating Interpretability: Discovering and Testing Visual Concepts Learned by Neural Networks. CoRR Amirata Ghorbani, James Wexler, Been Kim
2019	J	`jnl`	The Bach Doodle: Approachable music composition with machine learning at scale. CoRR Cheng-Zhi Anna Huang, Curtis Hawthorne, Adam Roberts, Monica Dinculescu, James Wexler, Leon Hong, Jacob Howcroft
2019	J	`jnl`	The What-If Tool: Interactive Probing of Machine Learning Models. CoRR James Wexler, Mahima Pushkarna, Tolga Bolukbasi, Martin Wattenberg, Fernanda B. Viégas, Jimbo Wilson
2019	A*	`conf`	Towards Automatic Concept-based Explanations. NeurIPS Amirata Ghorbani, James Wexler, James Y. Zou, Been Kim
2018	J	`jnl`	ClinicalVis: Supporting Clinical Task-Focused Design Evaluation. CoRR Marzyeh Ghassemi, Mahima Pushkarna, James Wexler, Jesse Johnson, Paul Varghese
2018	A*	`conf`	Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV). ICML Been Kim, Martin Wattenberg, Justin Gilmer, Carrie J. Cai, James Wexler, Fernanda B. Viégas, Rory Sayres
2018	J	`jnl`	Scalable and accurate deep learning for electronic health records. CoRR 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 D. Howell, Claire Cui, Greg Corrado, Jeff Dean
2018	J	`jnl`	Scalable and accurate deep learning with electronic health records. npj Digit. Medicine 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
2018	J	`jnl`	Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow. IEEE Trans. Vis. Comput. Graph. Kanit Wongsuphasawat, Daniel Smilkov, James Wexler, Jimbo Wilson, Dandelion Mané, Doug Fritz, Dilip Krishnan, Fernanda B. Viégas, Martin Wattenberg