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Gagan Bansal
Gagan Bansal
Microsoft Research
Verified email at microsoft.com - Homepage
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Does the whole exceed its parts? The effect of AI explanations on complementary team performance
G Bansal, T Wu, J Zhou, R Fok, B Nushi, E Kamar, MT Ribeiro, D Weld
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021
3982021
Beyond accuracy: The role of mental models in human-AI team performance
G Bansal, B Nushi, E Kamar, WS Lasecki, DS Weld, E Horvitz
Proceedings of the AAAI conference on human computation and crowdsourcing 7 …, 2019
3402019
The challenge of crafting intelligible intelligence
DS Weld, G Bansal
Communications of the ACM 62 (6), 70-79, 2019
298*2019
Updates in human-AI teams: Understanding and addressing the performance/compatibility tradeoff
G Bansal, B Nushi, E Kamar, DS Weld, WS Lasecki, E Horvitz
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 2429-2437, 2019
2642019
Is the most accurate AI the best teammate? Optimizing AI for teamwork
G Bansal, B Nushi, E Kamar, E Horvitz, DS Weld
Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11405 …, 2021
1192021
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
Q Wu, G Bansal, J Zhang, Y Wu, S Zhang, E Zhu, B Li, L Jiang, X Zhang, ...
arXiv preprint arXiv:2308.08155, 2023
1002023
Hierarchical summarization: Scaling up multi-document summarization
J Christensen, S Soderland, G Bansal
Proceedings of the 52nd annual meeting of the association for computational …, 2014
742014
Reading between the lines: Modeling user behavior and costs in AI-assisted programming
H Mozannar, G Bansal, A Fourney, E Horvitz
CHI 2024, 2022
422022
A coverage-based utility model for identifying unknown unknowns
G Bansal, D Weld
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
422018
Do explanations help users detect errors in open-domain QA? An evaluation of spoken vs. visual explanations
AV González, G Bansal, A Fan, Y Mehdad, R Jia, S Iyer
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 …, 2021
33*2021
Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations
V Chen, QV Liao, JW Vaughan, G Bansal
Proceedings of CSCW, 2023
242023
Generation probabilities are not enough: Exploring the effectiveness of uncertainty highlighting in AI-powered code completions
H Vasconcelos, G Bansal, A Fourney, QV Liao, JW Vaughan
arXiv preprint arXiv:2302.07248, 2023
20*2023
Emerging perspectives in human-centered machine learning
G Ramos, J Suh, S Ghorashi, C Meek, R Banks, S Amershi, R Fiebrink, ...
Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing …, 2019
202019
Technology-enabled disinformation: Summary, lessons, and recommendations
J Akers, G Bansal, G Cadamuro, C Chen, Q Chen, L Lin, P Mulcaire, ...
arXiv preprint arXiv:1812.09383, 2018
202018
Data staining: A method for comparing faithfulness of explainers
J Sippy, G Bansal, DS Weld
Proceedings of ICML Workshop on Human Interpretability in Machine Learning, 2020
132020
Aligning Offline Metrics and Human Judgments of Value for Code Generation Models
V Dibia, A Fourney, G Bansal, F Poursabzi-Sangdeh, H Liu, S Amershi
Findings of the Association for Computational Linguistics: ACL 2023, 8516-8528, 2023
7*2023
Explanatory dialogs: Towards actionable, interactive explanations
G Bansal
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 356-357, 2018
72018
When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming
H Mozannar, G Bansal, A Fourney, E Horvitz
Proceedings of AAAI, 2023
22023
Workshop on Trust and Reliance in AI-Human Teams (TRAIT)
G Bansal, Z Buçinca, K Holstein, J Hullman, AM Smith-Renner, S Stumpf, ...
Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing …, 2023
2023
Three Maxims for Developing Human-Centered AI for DecisionMaking
G Bansal
2022
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