Welcome to Xingyue Huang’s Personal Website
Welcome! 👋
I’m Xingyue Huang (黄星越), a DPhil student in Computer Science at the University of Oxford, supervised by Prof. Michael M. Bronstein and Dr. İsmail İlkan Ceylan.
Previously, I earned my MMathCompSci (Mathematics and Computer Science) from Oxford with Distinction.
🧑💻 About Me
- Passionate about Graph Representation Learning, Knowledge Graphs/Hypergraphs, and Geometric Deep Learning
- Also interested in Large Language Models (LLMs), Multi-Agent Systems (MAS), and Mathematical Reasoning
- Early work in Evolutionary Algorithms and Genetic Programming with Dr. Yu Zhou at Shenzhen University
📰 News
Workshop Proposal Accepted at ICML 2026
Published:
Our workshop proposal, “Graph Foundation Models: A New Era for Graph Machine Learning,” has been accepted for ICML 2026!
TDA Accepted to ACL 2026
Published:
Our paper “Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling” has been accepted to ACL 2026.
HTP Accepted to ACL 2026 (Oral)
Published:
Our paper “Hierarchical Token Prepending: Enhancing Information Flow in Decoder-based LLM Embeddings” has been accepted to ACL 2026 (Oral).
Selected as Top Reviewer for NeurIPS 2025
Published:
Honored to be recognized as a Top Reviewer at NeurIPS 2025.
Organizing the SEA Workshop @ NeurIPS 2025
Published:
Co-organizing the Scaling Environments for Agents (SEA) Workshop at NeurIPS 2025.
Research Intern at Snap Inc. (User Modelling & Personalization)
Published:
Research intern at Snap Inc., User Modelling and Personalization teams.
Research Internships at Eigent-AI & CAMEL-AI
Published:
Worked on multi-agent systems and data generation for verifiable RL.
How Expressive are Knowledge Graph Foundation Models? Permalink
Published:
Our paper ‘How Expressive are Knowledge Graph Foundation Models?’ is now available on arXiv. Check it out for a detailed analysis of the expressive power of KGFMs.
🛠️ Service
- Reviewer: NeurIPS 2025, ICLR 2026