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Yibo Jiang
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Twitter /
Email
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).
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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!
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Publications
The Geometry of Categorical and Hierarchical Concepts in Large Language Models
Kiho Park, Yo Joong Choe, Yibo Jiang, Victor Veitch
ICML Mechanistic Interpretability Workshop, 2024
(Best Paper Award)
arxiv
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Do LLMs Dream of Elephants (When Told Not to)? Latent Concept Association and Associative Memory in Transformers
Yibo Jiang, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam
Advances in Neural Information Processing Systems (NeurIPS), 2024
arxiv
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On the Origins of Linear Representations in Large Language Models
Yibo Jiang*, Goutham Rajendran*, Pradeep Ravikumar, Bryon Aragam, Victor Veitch
International Conference on Machine Learning (ICML), 2024
arxiv
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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
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Uncovering Meanings of Embeddings via Partial Orthogonality
Yibo Jiang, Bryon Aragam, Victor Veitch
Advances in Neural Information Processing Systems (NeurIPS), 2023
arxiv
/ video
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Learning Nonparametric Latent Causal Graphs with Unknown Interventions
Yibo Jiang, Bryon Aragam
Advances in Neural Information Processing Systems (NeurIPS), 2023
arxiv
/ video
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Invariant and Transportable Representations for Anti-Causal Domain Shifts
Yibo Jiang, Victor Veitch
Advances in Neural Information Processing Systems (NeurIPS), 2022
arxiv
/ video
/ code
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Associative Memory in Iterated Overparameterized Sigmoid Autoencoders
Yibo Jiang, Cengiz Pehlevan
International Conference on Machine Learning (ICML), 2020
arxiv
/ video
/ code
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Meta-Learning to Cluster
Yibo Jiang, Nakul Verma
arxiv Preprint, 2019
arxiv
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Model-Agnostic Meta-Learning using Runge-Kutta Methods
Daniel Jiwoong Im, Yibo Jiang, Nakul Verma
arxiv Preprint, 2019
arxiv
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Academic Services
Conference Reviewer: NeurIPS, ICML, ICLR, AISTATS, KDD, AAAI
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Profile picture taken by Qian Sheng. Last updated Sept. 2024.
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