Jiaxin Zhang
Staff Research Scientst
Intuit AI Research
Office: 2535 Garcia Ave Mountain View, CA, 94043
Research: As an AI researcher, I am passionate about building AGI capability and assisting humans in solving complex real-world tasks ranging from Computer Vision (CV) and Natural Language Processing (NLP). My interest span multiple areas, including reliabile and robust AI, generative models (LLMs and diffusion models), uncertainty quantification, and AI for Science.
Previously: I was a Research Staff in Computer Science and Mathematics Dvision at Oak Ridge National Laboratory, US Department of Energy (DOE). I received my Ph.D. from Johns Hopkins University in 2018.
Publications: 50+ peer-review journal/conference papers, and 35+ first-author papers, including several top-tier AI conferences, e.g., NeurIPS, CVPR, EMNLP, etc, and high-impact journals, such as Nature series.
Service: Invited Reviewer or PC member in NeurIPS 2020-2023, ICML 2021-2023, ICLR 2021-2024, AISTATS 2021-2023, CVPR 2022, ECCV 2022, KDD 2023, ICASSP 2024, SIAM SDM 2024, WACV 2024, etc.
I’m always looking for highly motivated Ph.D. students to work with me for research internship positions. Please feel free to email me with your CV if interested. .
news
Nov 10, 2023 | I created two Github Repos to share resources and papers on LLM Prompt Optimization and LLM RAG. Welcome to contribute and work together! |
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Oct 24, 2023 | Two papers on “DECDM: Document Enhancement using Cycle-Consistent Diffusion Models” and “On the Quantification of Image Reconstruction Uncertainty without Training Data” are accpeted by WACV 2024! |
Oct 22, 2023 | Our paper on “A Divide-Conquer-Reasoning Approach to Consistency Evaluation and Improvement in Blackbox Large Language Models” is accepted by NeurIPS 2023 Workshop on Socially Responsible Language Modelling Research. |
Oct 7, 2023 | Our paper on SAC^3: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency is accepted by EMNLP 2023! The code is coming soon! |
Sep 28, 2023 | One patent on “Model based document image enhancement” is issued and published. |
Sep 21, 2023 | Our paper on “Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision” is accepted by NeurIPS 2023! Cheers! |
Mar 27, 2023 | I was invited to be a Reviewer/PC member for NeurIPS 2023, ICLR 2024, ICASSP 2024, WACV 2024, SIAM SDM 2024. |
Mar 21, 2023 | I built a Github Repo that contains a collection of resources and papers on Reliability, Robustness and Safety in Large Language Models (LLMs). |
Feb 21, 2023 | Our paper titled “Speech Privacy Leakage from Shared Gradients in Distributed Learning” is accepted by ICASSP 2023! |
Dec 12, 2022 | Two papers on “Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling” and “AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution” are accpeted by AAAI 2023! |
selected publications
- WACVDECDM: Document Enhancement using Cycle-Consistent Diffusion ModelsIn IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024
- WACVOn the Quantification of Image Reconstruction Uncertainty without Training DataIn IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024