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Li "Harry" Zhang  张力


About Me

I am an assistant professor at Drexel University focusing on Natural Language Processing and Artificial Intelligence. I'm interested in planning and reasoning using Large Language Models. I earned my PhD from the University of Pennsylvania, having the honor to be mentored by Prof. Chris Callison-Burch, with a thesis committee chaired by Prof. Dan Roth. I earned my BS from the University of Michigan in 2018, mentored by Prof. Rada Mihalcea and Prof. Dragomir Radev.

Potential PhD students should email me with [PhD 2025] in the subject line and apply online. It is necessary to demonstrate past experience in NLP/AI/ML research. I am also hiring paid research assistants/interns and looking for unpaid visiting students/collaborators with potential conversion to a PhD student starting in Jan 2026. Those interested should fill out this form; please do not email separately on this matter.

CV

Harry.Zhang@drexel.edu


Affiliations

Drexel Universitydrexel logo
Assistant Professor;
Dec 2024 to Present

University of Pennsylvaniaupenn logo
Ph.D.; Aug 2019 to Aug 2024

Allen Institute for Artifical IntelligenceAI2
Research Intern;
April 2023 to Dec 2023

IBM ResearchIBM Research
Research Intern; May 2021 to Aug 2021,
April 2019 to June 2019

University of Michiganumich logo
B.S.E.; Aug 2015 to Dec 2018

Goldman SachsGoldman Sachs
Summer Analyst;
May 2017 to Aug 2017

Shenzhen Middle SchoolSMS logo
High School Diploma;
Sept 2012 to Jun 2015

Mentorship and Teaching

PhD Students
Cassie Huang
Research Assistants & Interns
Krystal Gong
Past Mentored Students
Tianyi Zhang
Hainiu Xu, King's College London
Zhaoyi Hou, University of Pittsburg
Young-Min Cho, University of Pennsylvania
Manni Arora, Apple
Teaching Assistant
2020Penn

CIS 530: Computational Linguistics (Winter, Fall 2020)

2016 - 2018UM-Penn

EECS 595: Natural Language Processing (Fall 2018) and EECS 280: Programming and Introductory Data Structures (Winter, Fall 2016)


Service

I have reviewed more than 50 papers of and chaired for many NLP conferences and workshops.

Area Chair of COLING 2025, ARR Aug 2024, ARR Jun 2024 / EMNLP 2024, ARR Feb 2024 / ACL 2024
Session Chair of ACL 2024, AACL-IJCNLP 2020
Reviewer of LREC-COLING 2024, EMNLP 2023, ACL 2023, ARR Mar 2022, DaSH Workshop @ EMNLP 2022, COLING 2022, LREC 2022, ARR Nov 2021, COLING 2020, Computer Speech and Language 2018
Program Chair of MASC-SLL 2023, MASC-SLL 2021
Co-organizer of CLUNCH 2020


Research

Primary Work: Structured Reasoning of Events using LLMs

Events and procedures play a major role in human language. Therefore, reasoning about them is crucial for AI and NLP. My work combines data-driven methods like large language models (LLM) and symbolic, structured representations of events to advance state-of-the-art on many downstream tasks, such as question answering, dialog, story generation, planning, etc. [PhD thesis] Roughly, I have looked into three types of methods:


1. (ongoing) Use LLMs to predict a fully structured and symbolic representation of an environment and problem (e.g., in PDDL or Python) that are processed by solvers (e.g., planners or interpreters), leading to an executable, verifiable, and interpretable reasoning process.

[29] PDDLEGO: Iterative Planning in Textual Environments; Li Zhang, Peter Jansen, Peter Clark, Chris Callison-Burch and Niket Tandon; in *SEM 2024.Paper BibTeX Repo

[28] PROC2PDDL: Open-Domain Planning Representations from Texts; Tianyi Zhang*Equal contribution^Mentored student, Li Zhang*Equal contribution, Zhaoyi Hou^Mentored student, Ziyu Wang^Mentored student, Yuling Gu, Peter Clark, Chris Callison-Burch and Niket Tandon; in ACL 2024 2st Workshop on Natural Language Reasoning and Structured Explanations.Paper BibTeX Repo

[20] Faithful Chain of Thought Reasoning; Qing Lyu*Equal contribution, Shreya Havaldar*Equal contribution, Adam Stein*Equal contribution, Li Zhang, Delip Rao, Eric Wong, Marianna Apidianaki and Chris Callison-Burch; in IJCNLP-AACL 2023.Paper BibTeX Repo


2. Use LLMs to predict a semi structured and symbolic representation of events (specifically, entities), which helps their decision making and reasoning via in-context learning.

[23] OpenPI2.0: An Improved Dataset for Entity Tracking in Texts; Li Zhang, Hainiu Xu^Mentored student, Abhinav Kommula, Chris Callison-Burch and Niket Tandon; in EACL 2024.Paper BibTeX Repo

[19] Causal Reasoning of Entities and Events in Procedural Texts; Li Zhang*Equal contribution, Hainiu Xu*Equal contribution^Mentored student, Yue Yang, Shuyan Zhou, Weiqiu You, Manni Arora and Chris Callison-Burch; in Findings of EACL 2023.Paper BibTeX Repo


3. Finetune LLMs with language-based data (specifically, event relations) to improve performance on various downstream tasks.

[6] Reasoning about Goals, Steps, and Temporal Ordering with WikiHow; Li Zhang*Equal contribution, Qing Lyu*Equal contribution and Chris Callison-Burch; in EMNLP 2020.Paper BibTeX Repo

[15] Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models; ... Li Zhang*Equal contribution, Qing Lyu*Equal contribution and Chris Callison-Burch; in TMLR.Paper

[10] Show Me More Details: Discovering Hierarchies of Procedures from Semi-structured Web Data; Shuyan Zhou*Equal contribution, Li Zhang*Equal contribution, Yue Yang, Qing Lyu, Pengcheng Yin, Chris Callison-Burch and Graham Neubig; in ACL 2022.Paper BibTeX Demo Repo

[8] Goal-Oriented Script Construction; Qing Lyu*Equal contribution, Li Zhang*Equal contribution and Chris Callison-Burch; in INLG 2021.Paper BibTeX Repo

[7] Intent Detection with WikiHow; Li Zhang, Qing Lyu, Chris Callison-Burch; in AACL-IJCNLP 2020.Paper BibTeX Repo

[9] Visual Goal-Step Inference using wikiHow; Yue Yang, Artemis Panagopoulou, Qing Lyu, Li Zhang, Mark Yatskar and Chris Callison-Burch; In EMNLP 2021.Paper BibTeX


Activities


Music

I am a drummer, producer and video content creator. I run a video channel with over 50,000 subscribers on Bilibili and YouTube, primarily making cover songs from video game and anime soundtracks, in a variety of styles ranging from metal to jazz. I am proudly sponsored by Vater, Tama, Mackie, Alesis, NUX, Xvive and have collaborated with manufacturers of major video games such as Genshin Impact and Azur Lane.
bilibili        

My videos are primarily either collaboration-work music videos or solo-work drum covers.

 

My new album, Megidalon, a collection of reimagined Persona soundracks, is available for streaming on all platforms! My two previous albums Dazzling Tales (reimagined Genshin Impact soundtracks) and A Doll's Lament (reimagined NieR soundtracks) are also available for listening on all major streaming platforms.

Megidalon   Dazzling Tales   A Doll's Lament


I also engage in research of AI music generation, having published a paper on automatic drum composition in an AAAI 2023 workshop.

[18] Language Models are Drummers: Drum Composition with Natural Language Pre-Training; Li Zhang and Chris Callison-Burch; in AAAI 2023 Workshop on Creative AI Across Modalities.Paper Repo BibTeX