Trenton Chang

According to our database1, Trenton Chang authored at least 17 papers between 2022 and 2026.

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Bibliography

2026
Causal Machine Learning Is Not a Panacea: A Roadmap for Observational Causal Inference in Health.
CoRR, May, 2026

A Course Correction in Steerability Evaluation: Revealing Miscalibration and Side Effects in LLMs.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025
Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025.
CoRR, October, 2025

Estimating Misreporting in the Presence of Genuine Modification: A Causal Perspective.
CoRR, May, 2025

Conditional Front-door Adjustment for Heterogeneous Treatment Assignment Effect Estimation Under Non-adherence.
CoRR, May, 2025

Evaluation Framework for AI Systems in "the Wild".
CoRR, April, 2025

Machine Learning for Health symposium 2024 - Findings track.
CoRR, March, 2025

Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium.
CoRR, February, 2025

Disentangling misreporting from genuine adaptation in strategic settings: a causal approach.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Conditional Front-door Adjustment for Heterogeneous Treatment Assignment Effect Estimation Under Non-compliance.
Proceedings of the Conference on Health, 2025

2024
Who's Gaming the System? A Causally-Motivated Approach for Detecting Strategic Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024


From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.
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Trans. Mach. Learn. Res., 2023

2022
Lost in Transmission: On the Impact of Networking Corruptions on Video Machine Learning Models.
CoRR, 2022

Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agent.
Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue, 2022

Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning.
Proceedings of the Machine Learning for Healthcare Conference, 2022


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