Yibo Jiang

I am a Computer Science PhD student at the University of Chicago, advised by Prof. Victor Veitch. I also work very closely with Prof. Bryon Aragam.

Previously, I received a MS in Computer Science from Columbia University, and graduated, as a Bronze Tablet recipient, from the University of Illinois Urbana-Champaign with double degrees in Electrical Engineering and Math.

Before starting my PhD, I was also a research fellow at Harvard, where I worked with Prof. Cengiz Pehlevan in the Theoretical Neuroscience Group. I have also interned at ByteDance (AML) and (a couple of times) at Nvidia (AI Dev Tech).

Research

I am broadly interested in robust/trustworthy machine learning, representation learning, causality, and more recently, the interpretability of large language models (LLMs). One speficic reseach goal of mine is to study the emergent structures and dynamics within representations, as well as complex networks arising from the training of modern machine learning models. My aim is to develop theories and methods for interpreting and ultimately utilizing these insights for alignment purposes.

I like collaborations; If you have a cool problem, don't hesitate to reach out – let's explore it together!

Publications

On the Origins of Linear Representations in Large Language Models

Yibo Jiang*, Goutham Rajendran*, Pradeep Ravikumar, Bryon Aragam, Victor Veitch
arxiv Preprint, 2024
arxiv

Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints

Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen
International Conference on Learning Representations (ICLR), 2024 (Spotlight, 5%)
arxiv / code

Uncovering Meanings of Embeddings via Partial Orthogonality

Yibo Jiang, Bryon Aragam, Victor Veitch
Advances in Neural Information Processing Systems (NeurIPS), 2023
arxiv

Learning Nonparametric Latent Causal Graphs with Unknown Interventions

Yibo Jiang, Bryon Aragam
Advances in Neural Information Processing Systems (NeurIPS), 2023
arxiv

Invariant and Transportable Representations for Anti-Causal Domain Shifts

Yibo Jiang, Victor Veitch
Advances in Neural Information Processing Systems (NeurIPS), 2022
arxiv / video / code

Associative Memory in Iterated Overparameterized Sigmoid Autoencoders

Yibo Jiang, Cengiz Pehlevan
International Conference on Machine Learning (ICML), 2020
arxiv / video / code

Meta-Learning to Cluster

Yibo Jiang, Nakul Verma
arxiv Preprint, 2019
arxiv

Model-Agnostic Meta-Learning using Runge-Kutta Methods

Daniel Jiwoong Im, Yibo Jiang, Nakul Verma
arxiv Preprint, 2019
arxiv

Academic Services

Conference Reviewer: NeurIPS (2023), ICML (2022, 2023), ICLR (2024), AISTATS (2022), KDD (2023)

Profile picture taken by Qian Sheng. Last updated March 2024.