Yixin Nie

Keep brewing and carry on...

🧑‍💻 ➕ 🧠 ➕ 📄🎨🎵🎥🗃️ 🔜 🤖💡🚀

I am a Research Scientist at Meta AI. I did my Ph.D. in Computer Science Department at University of North Carolina at Chapel Hill, advised by Mohit Bansal. Before that, I did my undergraduate degree at China University of Geosciences, and then my master's degree at The University of Chicago.
[show complete experience]


2022 -
Research Scientist at Meta AI.
2017 - 2022
Ph.D. in Computer Science Department at University of North Carolina at Chapel Hill, advised by Mohit Bansal.
I worked on data-driven approaches to language modeling, with an emphasis on benchmarking, fact-checking, and vision-language modeling.
2021
Research Intern at Microsoft in Cognitive Services Research team.
2020
Research Intern at Facebook AI Research (FAIR) with Jason Weston.
2019
Research Intern at Facebook AI Research (FAIR) with Douwe Kiela.
2015 - 2017
M.S in Computer Science Department at The University of Chicago.

2016
Research Assistant at Toyota Technological Institute at Chicago (TTIC).
  • Developed sentence encoder for NLI; achieved Top-1 (single model) at RepEval, EMNLP 2017.
2010 - 2014
B.Eng at China University of Geosciences in Computer Science.
selected publications (See all on Google Scholar)
Learning to Solve and Verify: A Self-Play Framework for Code and Test Generation
ArXiv 2025
Zi Lin, Sheng Shen, Jingbo Shang, Jason Weston, Yixin Nie
ROICtrl: Boosting Instance Control for Visual Generation
CVPR 2025
Yuchao Gu, Yipin Zhou, Yunfan Ye, Yixin Nie, Licheng Yu, Pingchuan Ma, Kevin Qinghong Lin, Mike Zheng Shou
Scene-LLM: Extending Language Model for 3D Visual Reasoning
WACV 2025
Rao Fu, Jingyu Liu, Xilun Chen, Yixin Nie, Wenhan Xiong
UNICORN: A Unified Causal Video-Oriented Language-Modeling Framework for Temporal Video-Language Tasks
EMNLP 2024
Yuanhao Xiong, Yixin Nie, Haotian Liu, Boxin Wang, Jun Chen, Rong Jin, Cho-Jui Hsieh, Lorenzo Torresani, Jie Lei
Jointly Training Large Autoregressive Multimodal Models
ICLR 2024
Emanuele Aiello, Lili Yu, Yixin Nie, Armen Aghajanyan, Barlas Oguz
The Role of Chain-of-Thought in Complex Vision-Language Reasoning Task
ArXiv 2024
Yifan Wu, Pengchuan Zhang, Wenhan Xiong, Barlas Oguz, James C. Gee, Yixin Nie
Llama 2: Open Foundation and Fine-Tuned Chat Models
ArXiv 2023
Llama 2 Team
Text-guided 3D Human Generation from 2D Collections
EMNLP 2023 Findings
Tsu-Jui Fu, Wenhan Xiong, Yixin Nie, Jingyu Liu, Barlas Oğuz, William Yang Wang
TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models
ArXiv 2023
Yuwei Yin, Jean Kaddour, Xiang Zhang, Yixin Nie, Zhenguang Liu, Lingpeng Kong, Qi Liu
CLIP-Layout: Style-Consistent Indoor Scene Synthesis with Semantic Furniture Embedding
ArXiv 2023
Jingyu Liu, Wenhan Xiong, Ian Jones, Yixin Nie, Anchit Gupta, Barlas Oğuz
3DGen: Triplane Latent Diffusion for Textured Mesh Generation
ArXiv 2023
Anchit Gupta*, Wenhan Xiong*, Yixin Nie*, Ian Jones*, Barlas Oğuz
Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning
Findings of ACL 2022
Xiang Zhou*, Yixin Nie*, Mohit Bansal
TVLT: Textless Vision-Language Transformer
NeurIPS 2022
Zineng Tang*, Jaemin Cho*, Yixin Nie*, Mohit Bansal
MLP Architectures for Vision-and-Language Modeling: An Empirical Study
ArXiv 2021
Yixin Nie*, Linjie Li*, Zhe Gan, Shuohang Wang, Chenguang Zhu, Michael Zeng, Zicheng Liu, Mohit Bansal, Lijuan Wang
Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference
Findings of ACL 2021
Hai Hu, He Zhou, Zuoyu Tian, Yiwen Zhang, Yina Ma, Yanting Li, Yixin Nie, Kyle Richardson
Dynabench: Rethinking Benchmarking in NLP
NAACL 2021
Dynabench Team
To What Extent Do Human Explanations of Model Behavior Align with Actual Model Behavior?
BlackboxNLP workshop, EMNLP 2021
Grusha Prasad, Yixin Nie, Mohit Bansal, Robin Jia, Douwe Kiela, Adina Williams
I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling
ACL 2021
Yixin Nie, Mary Williamson, Mohit Bansal, Douwe Kiela, Jason Weston
What Can We Learn from Collective Human Opinions on Natural Language Inference Data?
EMNLP 2020
Yixin Nie, Xiang Zhou, Mohit Bansal
ConjNLI: Natural Language Inference Over Conjunctive Sentences
EMNLP 2020
Swarnadeep Saha, Yixin Nie, Mohit Bansal
The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and Suggestions
EMNLP 2020
Xiang Zhou, Yixin Nie, Hao Tan, Mohit Bansal
Adversarial NLI: A New Benchmark for Natural Language Understanding
ACL 2020
Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, Douwe Kiela
Simple Compounded-Label Training for Fact Extraction and Verification
Fact Extraction and Verification (FEVER) workshop, ACL 2020
Yixin Nie*, Lisa Bauer*, and Mohit Bansal
Revealing the Importance of Semantic Retrieval for Machine Reading at Scale
EMNLP 2019
Yixin Nie, Songhe Wang, Mohit Bansal
Combining Fact Extraction and Verification with Neural Semantic Matching Networks
AAAI 2019
Yixin Nie, Haonan Chen, Mohit Bansal
Analyzing Compositionality-Sensitivity of NLI Models
AAAI 2019
Yixin Nie*, Yicheng Wang*, Mohit Bansal
Shortcut-Stacked Sentence Encoders for Multi-Domain Inference
RepEval Workshop, EMNLP 2017
Yixin Nie and Mohit Bansal
teaching
Teaching Assistant, Graduate Natural Language Processing, UNC Chapel Hill, Fall 2017.
Teaching Assistant, Algorithms and Analysis, UNC Chapel Hill, Fall 2017.
misc