James Zou

This page is a disambiguation page, it actually contains mutiple papers from persons of the same or a similar name.

Known people with the same name:

Bibliography

2024
New Evaluation Metrics Capture Quality Degradation due to LLM Watermarking.
Trans. Mach. Learn. Res., 2024

Author Correction: Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach.
npj Digit. Medicine, 2024

Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach.
npj Digit. Medicine, 2024

Mixture-of-Agents Enhances Large Language Model Capabilities.
CoRR, 2024

Dragonfly: Multi-Resolution Zoom Supercharges Large Visual-Language Model.
CoRR, 2024

Enhancing Large Vision Language Models with Self-Training on Image Comprehension.
CoRR, 2024

SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals.
CoRR, 2024

Talking Nonsense: Probing Large Language Models' Understanding of Adversarial Gibberish Inputs.
CoRR, 2024

Optimizing Calibration by Gaining Aware of Prediction Correctness.
CoRR, 2024

The complementary contributions of academia and industry to AI research.
CoRR, 2024

2023
TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter.
CoRR, 2023

2022
Improving genetic risk prediction across diverse population by disentangling ancestry representations.
CoRR, 2022

Ensembling improves stability and power of feature selection for deep learning models.
Proceedings of the Machine Learning in Computational Biology, 21-22 November 2022, Online, 2022

2021
CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq.
CoRR, 2021

2020
Explaining the Trump Gap in Social Distancing Using COVID Discourse.
Proceedings of the 1st Workshop on NLP for COVID-19@ EMNLP 2020, Online, December 2020, 2020

2019
A Knowledge Graph-based Approach for Exploring the U.S. Opioid Epidemic.
CoRR, 2019

2018
Minimizing Close-k Aggregate Loss Improves Classification.
CoRR, 2018

CoVeR: Learning Covariate-Specific Vector Representations with Tensor Decompositions.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Quantifying the accuracy of approximate diffusions and Markov chains.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Signal to noise in matching markets.
CoRR, 2016

Controlling Bias in Adaptive Data Analysis Using Information Theory.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016


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