Xiaoxin He

PhD student at National University of Singapore @NUSingapore | Graphs and LLMs | Google PhD Fellowship 2024

[Xingyue Huang @hxyscott]

We are happy to announce that "Graph Foundation Models: A New Era for Graph Machine Learning" workshop has been accepted at #ICML2026!

Call for papers on topics: Graph Foundation Models, LLMs/TFMs+Graphs, theory of GFMs, etc.

📷 Submit by May 3rd! 📷 #GraphML #GFM

[Xavier Bresson @xbresson]

Boosting Q&A Accuracy with GraphRAG powered by our G-Retriever architecture.
@he_xiaoxin

https://t.co/mSlrNyiwiM

[Xiaoxin He @he_xiaoxin]

Check out the paper here: https://t.co/AQmZNrklFN

[Yu Wang @__YuWang__]

(1/4) Excited to share that our position paper "Towards LifeSpan Cognitive Systems" has been accepted to TMLR! As "agents" dominate the AI landscape in 2025, we push the boundaries by envisioning LSCS — AI systems that go beyond personal assistants to lifespan cognitive systems.

[Xiaoxin He @he_xiaoxin]

I will be presenting G-Retriever tomorrow, Thu 12 Dec 4:30 p.m. PST — 7:30 p.m. PST, at East Exhibit Hall A-C #4607.
https://t.co/rTNKG9Q10q

[Xiaoxin He @he_xiaoxin]

𝑪𝒉𝒂𝒕 𝒘𝒊𝒕𝒉 𝒀𝒐𝒖𝒓 𝑮𝒓𝒂𝒑𝒉 🗣️

G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering

ArXiv: https://t.co/NdcIKy2urF
GitHub: https://t.co/J9yEdE5y14
BlogPost: https://t.co/JvddZq9xxo

[Xavier Bresson @xbresson]

I will give a talk at the @LogConference on "Integrating Graph Neural Networks and Large Language Models".

The conference is virtual, free to attend, live-streamed, and recorded.
https://t.co/PwtgTz0Z4a

Hope to see you there!

[Xiaoxin He @he_xiaoxin]

@guanzhi_wang Thank you, guanzhi!

[Xiaoxin He @he_xiaoxin]

Thrilled to announce that I've been awarded the 𝗚𝗼𝗼𝗴𝗹𝗲 𝗣𝗵𝗗 𝗙𝗲𝗹𝗹𝗼𝘄𝘀𝗵𝗶𝗽! Huge thanks to my advisors, @BryanHooi1 and @xbresson, for their incredible support and guidance! Grateful to @GoogleAI for this valuable honor! 🎉🎉

https://t.co/ry77GmFf6R

[Xiaoxin He @he_xiaoxin]

@frankkklee @BryanHooi1 @xbresson @GoogleAI Thank you, shenggui!

[Xiaoxin He @he_xiaoxin]

@lovrovrcek @BryanHooi1 @xbresson @GoogleAI Thank you, Lovro!

[Xiaoxin He @he_xiaoxin]

@michael_galkin @BryanHooi1 @xbresson @GoogleAI Thank you, Michael!

[Xiaoxin He @he_xiaoxin]

Awesome to see that PyG now supports G-Retriever!🎉
https://t.co/0Ik4HoRvBn
Excited to try out the new features in PyG 2.6!

[Jure Leskovec @jure]

🚀 PyG 2.6 is here: GNNs + LLMs, PyTorch 2.4 and more! 🎉
We’re excited to announce the release of PyG 2.6.0, packed with incredible updates for graph learning!
Here’s a quick rundown of what’s new:
✨ Key Highlights:
-- GNNs + LLMs: New models like GRetriever that co-train LLaMA2 with GNNs for enhanced knowledge graph tasks.
-- PyTorch 2.4 Compatibility: Full support for PyTorch 2.4 across platforms!
-- Efficient Index Tensor Representation: Simplifying 1D indices with the new Index class for seamless interactions in GNN message passing.
-- Plus, there are new tutorials, multi-GPU examples, and various improvements to elevate your GNN workflows! 🚀

Check out the full changelog and get started with PyG 2.6 today!

https://t.co/Lx4ORkr7RC

[Learning on Graphs Conference 2026 @LogConference]

We have seen great success in LoG 2023 local meetups in Stanford, NY, Munich, Amsterdam, Shanghai, Lausanne, Paris, Tromso, Madrid, Trento, Oxford, and Montreal. With over 700 attendees in total, the memories from LoG 2023 have been incredible!

[Xavier Bresson @xbresson]

Join the online LoGG presentation by @he_xiaoxin, hosted by @HannesStaerk @dom_beaini, on integrating LLMs and GNNs w/ G-Retriever.

When: Mon Jul 15 11am ET
Zoom: https://t.co/Se7SzV0KtF
Blog: https://t.co/BSDZxKwdLP
ArXiv: https://t.co/pn8f7nVdTY
GitHub: https://t.co/uWWLMRQb6O

[Learning on Graphs Conference 2026 @LogConference]

Our new call for #LoG2024 local meetups is out! This "network" of local mini-conferences aims to bring together attendees belonging to the same geographic area, fostering discussions and collaborations.If you are interested in hosting one, please read this https://t.co/bYWUSQROON

[Xavier Bresson @xbresson]

Two exciting updates for the Learning on Graphs Conference!

1) Virtual conference from Nov 26th 2024
https://t.co/y0rQKN9pCB

2) Join the first in-person conference from Sept 28-30 2025
https://t.co/J5Mb7b7pr8

Don't miss out on the opportunity to receive high-quality reviews!

[Xiaoxin He @he_xiaoxin]

The Graph Foundation Models Workshop @TheWebConf was a great success! We would like to extend a big thank you to our speakers, panelists, advisory board, organizers, and audience for making this event amazing!

[Xiaoxin He @he_xiaoxin]

Please visit our poster today (May 9), from 4:30 to 6:30 PM at Hall B, #89. See you there!

[Xavier Bresson @xbresson]

New paper w/ @he_xiaoxin, T. Laurent, @BryanHooi1 "Explanations as Features: LLM-Based Features for Text-Attributed Graphs"
ArXiv: https://t.co/TerY447HYJ
GitHub: https://t.co/eQNnP8BTso

[Xiaoxin He @he_xiaoxin]

(6/n) If you are interested in related topics such as Graph RAG and Graph Prompt Tuning, please check out the 'Related Work and Discussion' section in our blog post: https://t.co/EPKc6htfkH

[Xiaoxin He @he_xiaoxin]

𝑪𝒉𝒂𝒕 𝒘𝒊𝒕𝒉 𝒀𝒐𝒖𝒓 𝑮𝒓𝒂𝒑𝒉 🗣️

G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering

ArXiv: https://t.co/NdcIKy2urF
GitHub: https://t.co/J9yEdE5y14
BlogPost: https://t.co/JvddZq9xxo

[Xiaoxin He @he_xiaoxin]

(5/n) We evaluate 𝑮-𝑹𝒆𝒕𝒓𝒊𝒆𝒗𝒆𝒓 on our GraphQA benchmark, and consider three model configurations: 1) Inference-Only; 2) Frozen LLM + Prompt Tuning; and 3) Tuned LLM.