Yuankai Li

I am a junior year undergraduate majoring in Artificial Intelligence in the School of Data Science, Fudan University.

I am privileged to be a research intern at Shanghai AI Laboratory under the guidance of Prof. Dequan Wang and Prof. Zhijie Deng, where I have worked with their esteemed group to study the capability boundaries of Large Language Models(LLMs).

My research interests lie broadly in machine learning and natural language processing. Currently, I have an intense interest in LLMs, with a specific focus on:

• Exploring and expanding the capability of LLMs to reason reliably via training, alignment and in-context learning

• Building helpful and reliable AI agents and exploring the use of LLMs in embodied AI

• Building intelligence systems that communicate through natural language and continuously improve through interaction

Email  /  CV  /  GitHub  / 

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Research

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LLMs as NPCs: Toward Human-Like and Interpretable Multi-Agent Driving Simulation


Second author, with additional authors omitted for anonymity.
Submitted to CoRL 2024

We develope an autonomous driving simulation system using LLMs in the decision-making stage and devised a method to translate a series of LLM decisions into simulation trajectories.

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Dissecting Dissonance: Benchmarking Large Multimodal Models Against Self-contradictory Instructions


Jin Gao, Lei Gan*, Yuankai Li*, Yixin Ye, Dequan Wang
ECCV 2024
paper / huggingface /

We introduce the idea of self-contradictory instructions in Large Multimodal Models(LMMs), emphasized its potential harm, and sought to benchmark and address this problem.




Other Projects

These include coursework and side projects.

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Exploration on Supervised-Finetuning on Small Language Models


Pattern Recognition & Machine Learning, Fudan University
2024-01-03
report /

I finetune GPT2-small over the MOSS-002 SFT dataset and conducted various capability tests with the BigBench dataset.

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Simple Machine Learning Framework


Artificial Intelligence(Honor), Fudan University
2023-12-15
code /

I redevelope a simple machine learning framework in Python that implements a backpropagation algorithm, various neural network architectures (like MLP and CNN), manifold statistical learning models (like HMM and CRF), etc.

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Implicit QR Algorithm for Eigen Value Problems


Numerical Linear Algebra, Fudan University
2022-12-22
code /

I implement the implicit QR algorithm proposed by John G. F. Francis(1962) in Matlab. The algorithm can find the eigenvalue of any given matrix in a reasonable amount of time.

Miscellanea

Things you can't find on my CV.

I enjoy playing Minesweeper. My average 3BV/s is 1.2 in Flag mode and 0.7 in NF mode. I'm still improving my skills.

I once learnt the basics of Sindarin from this.

I favour Star Trek DS9, VOY and TNG.

I am interested in speedrunning in most roguelike games.




Design and source code from Jon Barron's website