Zihao He

Zihao He

I'm a Research Scientist on the Monetization GenAI team at Meta. I obtained my PhD in CS from USC, advised by Prof. Kristina Lerman. I was part of the SEA Lab. My research interests include NLP, LLM alignment & evaluation, and reinforcement learning from human feedback (RLHF).

Previously, I received my undergraduate degree in Communication Engineering from Beijing University of Posts and Telecommunications. I've spent time at Tsinghua University working with Shutao Xia. During my PhD, I interned at TikTok, Amazon, and DiDi Global.

Recent News

Industrial Experience

Education

Aug 2019 – Feb 2025 Ph.D. in Computer Science, University of Southern California, Los Angeles, CA, United States
Sep 2018 – Jun 2019 (Transferred) M.S. in Computer Engineering, Tsinghua University, Beijing, China
Sep 2014 – Jun 2018 B.E. in Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China

Selected Publications & Preprints

Multi-Task Reinforcement Learning for Enhanced Multimodal LLM-as-a-Judge
Junjie Wu, Xuan Kan, Zihao He, Shunwen Tan, Bo Pan, Kaitai Zhang
ACL Industry Track, 2026
BigTokDetect: A Clinically-Informed Vision-Language Modeling Framework for Detecting Pro-Bigorexia Videos on TikTok
Minh Duc Chu, Kshitij Pawar, Zihao He, Roxanna Sharifi, Ross Sonnenblick, Magdalayna Curry, Laura D'Adamo, Lindsay Young, Stuart B Murray, Kristina Lerman
EACL, 2026
STEER-BENCH: A Benchmark for Evaluating the Steerability of Large Language Models
Kai Chen, Zihao He, Taiwei Shi, Kristina Lerman
EMNLP, 2025
Smoothing Out Hallucinations: Mitigating LLM Hallucination with Smoothed Knowledge Distillation
Hieu Nguyen, Zihao He, Shoumik Atul Gandre, Ujjwal Pasupulety, Sharanya Kumari Shivakumar, Kristina Lerman
Preprint, 2025
Improving and Assessing the Fidelity of Large Language Models Alignment to Online Communities
Minh Duc Chu, Zihao He, Rebecca Dorn, Kristina Lerman
NAACL, 2025
How Susceptible are Large Language Models to Ideological Manipulation?
Kai Chen, Zihao He, Jun Yan, Taiwei Shi, Kristina Lerman
EMNLP, 2024
Whose Emotions and Moral Sentiments Do Language Models Reflect?
Zihao He, Siyi Guo, Ashwin Rao, Kristina Lerman
ACL-Findings, 2024
IsamasRed: A Public Dataset Tracking Reddit Discussions on Israel-Hamas Conflict
Kai Chen, Zihao He, Keith Burghardt, Jingxin Zhang, Kristina Lerman
ICWSM, 2024
Don't Blame the Data, Blame the Model: Understanding Noise and Bias When Learning from Subjective Annotations
Abhishek Anand, Negar Mokhberian, Prathyusha Kumar, Anweasha Saha, Zihao He, Ashwin Rao, Fred Morstatter, Kristina Lerman
Proceedings of the 1st Workshop on Uncertainty-Aware NLP (UncertaiNLP), 2024
Reading Between the Tweets: Deciphering Ideological Stances of Interconnected Mixed-ideology Communities
Zihao He, Ashwin Rao, Siyi Guo, Negar Mokhberian, Kristina Lerman
EACL-Findings, 2024
Measuring Online Emotional Reactions to Events
Siyi Guo, Zihao He, Ashwin Rao, Eugene Jang, Yuanfeixue Nan, Fred Morstatter, Jeffrey Brantingham, Kristina Lerman
ASONAM, 2023
Anger Breeds Controversy: Analyzing Controversy and Emotions on Reddit
Kai Chen, Zihao He, Rong-Ching Chang, Jonathan May, Kristina Lerman
SBP-BRiMS, 2023
ALCAP: Alignment-Augmented Music Captioner
Zihao He, Weituo Hao, Wei-Tsung Lu, Changyou Chen, Kristina Lerman, Xuchen Song
EMNLP, 2023
Infusing Knowledge from Wikipedia to Enhance Stance Detection
Zihao He, Negar Mokhberian, Kristina Lerman
Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, 2022
Detecting Polarized Topics Using Partisanship-aware Contextualized Topic Embeddings
Zihao He, Negar Mokhberian, António Câmara, Andres Abeliuk, Kristina Lerman
EMNLP-Findings, 2021
Speaker Turn Modeling for Dialogue Act Classification
Zihao He, Leili Tavabi, Kristina Lerman, Mohammad Soleymani
EMNLP-Findings, 2021
Graph Embedding with Personalized Context Distribution
Zihao He, Di Huang, Yuzhong Huang, Kexuan Sun, Sami Abu-El-Haija, Bryan Perozzi, Kristina Lerman, Fred Morstatter, Aram Galstyan
Companion Proceedings of the Web Conference, 2020
Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters
Haoyu Liang, Zhihao Ouyang, Yuyuan Zeng, Hang Su, Zihao He, Shu-Tao Xia, Jun Zhu, Bo Zhang
ECCV, 2020
Neural Style Transfer with Content Discrimination
Xiyu Yan, Yeli Xing, Zihao He, Tao Dai, Yong Jiang, Shu-Tao Xia
ICMEW, 2019
AttentionDrop for Convolutional Neural Networks
Zhihao Ouyang, Yan Feng, Zihao He, Tianbo Hao, Tao Dai, Shu-Tao Xia
ICME, 2019
Automatic Grassland Degradation Estimation Using Deep Learning
Xiyu Yan, Yong Jiang, Shuai Chen, Zihao He, Chunmei Li, Shu-Tao Xia, Tao Dai, Shuo Dong, Feng Zheng
IJCAI, 2019

Miscellany