Heng Wang  (王珩)

Hi there, thanks for visiting my website! I am a third-year undergraduate student at Xi'an Jiaotong University, majoring in Computer Science.

I am broadly interested in social network analysis, graph mining, and natural language processing, advised by Prof. Minnan Luo. My previous research includes Twitter bot detection, spoiler detection and graph representation learning. I'm a member of LUD lab, the premiere undergraduate research group @ XJTU.

Email  /  CV  /  Google Scholar  /  Twitter  /  Github

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Research Interest

I am broadly interested in natural language processing, social network analysis, and graph mining.

Publications (* indicates equal contribution)
3DSP Can Language Models Solve Graph Problems in Natural Language?
Heng Wang*, Shangbin Feng*, Tianxing He, Zhaoxuan Tan, Xiaochuang Han, Yulia Tsvetkov
Proceedings of NeurIPS, 2023 (spotlight)
code / poster

Are language models graph reasoners? We propose the NLGraph benchmark, a test bed for graph-based reasoning designed for language models in natural language. We find that LLMs are preliminary graph thinkers while the most advanced graph reasoning tasks remain an open research question.

3DSP Detecting Spoilers in Movie Reviews with External Movie Knowledge and User Networks
Heng Wang, Wenqian Zhang, Yuyang Bai, Zhaoxuan Tan, Shangbin Feng, Qinghua Zheng, Minnan Luo
Proceedings of EMNLP, 2023

We curate a large-scale network-based spoiler detection dataset (LCS), a movie knowledge base (UKM), and propose MVSD, a Multi-View Spoiler Detection framework that takes into account external knowledge and user interaction networks.

3DSP Resolving Knowledge Conflicts in Large Language Models
Yike Wang*, Shangbin Feng*, Heng Wang, Weijia Shi, Vidhisha Balachandran , Tianxing He, Yulia Tsvetkov
arXiv preprint, 2023.

We introduce KNOWLEDGE CONFLICT, an evaluation framework for simulating contextual knowledge conflicts and quantitatively evaluating LLMs' abilities to handle knowledge conflicts.

3DSP BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts
Yuhan Liu, Zhaoxuan Tan, Heng Wang, Shangbin Feng, Qinghua Zheng, Minnan Luo
Proceedings of SIGIR 2023.

We propose community-aware mixture-of-experts to address two challenges in detecting advanced Twitter bots: manipulated features and diverse communities.

3DSP TwiBot-22: Towards Graph-Based Twitter Bot Detection
Shangbin Feng*, Zhaoxuan Tan*, Herun Wan*, Ningnan Wang*, Zilong Chen*, Binchi Zhang*, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo
Proceedings of NeurIPS, Datasets and Benchmarks Track, 2022.
website / GitHub / bibtex / poster

We present TwiBot-22, the largest graph-based Twitter bot detection benchmark to date, which provides diversified entities and relations in Twittersphere and has considerably better annotation quality.

Xi'an Jiaotong University
2021.09 - 2025.07 (Expected)

B.E. in Computer Science
GPA: 94.96 / 100.0 (4.17 / 4.3)
Advisor: Prof. Minnan Luo
Academic Experiences
Luo lab Undergraduate Division (LUD) @ XJTU

Member         2021.08 - present
Conducted research on various topics including social network analysis, graph neural networks pre-training.
Advisor: Prof. Minnan Luo
Honors & Awards
  • Golden Award (team 3rd place), ACM ICPC Shaanxi Provincial Programming Contest, 2023
  • Silver Award (ranking 26/115), ACM ICPC Asia Hong Kong Regional, 2023
  • National Scholarship, 2022
  • NeurIPS Scholar Award, 2023
  • Academic Research Award, Xi'an Jiaotong University, 2022
  • Silver Award, CCF Collegiate Computer System and Programming Contest, 2022
  • Silver Award (ranking 61/697), ACM ICPC Asia Kunming Regional, 2022
  • Outstanding Student Leaders, Xi'an Jiaotong University, 2022
  • Dean's List, Xi'an Jiaotong University, 2022
  • Reviewer: EMNLP 2023, TOIS 2023, NeurIPS dataset and benchmark track 2022, 2023
  • I enjoy playing the piano 🎹 and go.
  • I am a big fan of Animenz.

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