Delighted to announce that our work has been accepted for presentation at the ICLR 2024 LLM Agents Workshop@ICLR2024 workshop in Vienna. Received exceptionally positive feedback from the reviewers and looking forward to sharing our insights and contributions with the community.

𝑪𝒉𝒂𝒕 𝒘𝒊𝒕𝒉 𝒀𝒐𝒖𝒓 𝑮𝒓𝒂𝒑𝒉 🗣️

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

ArXiv: arxiv.org/abs/2402.07630
GitHub: github.com/XiaoxinHe/G-Re…
BlogPost: medium.com/@xxhe/graph-re…

One of my favourite letters, insightful & humane, from Richard Feynman to a former student who was having a rough time

I was reflecting on it as an argument in favour of scope insensitivity, or even in favour of smaller problems:

🚀 Excited to introduce MultiModal Graph Learning (MMGL) - exploring beyond the typical one-to-one data modality pairs🔗 to uncover more complex and multifaceted relationships among data modalities! 🌐

📄 Paper: arxiv.org/abs/2310.07478
🧵 Thread continues...

Thrilled to share paper on LLMs' calibration capability! 'Can LLMs Express Their Uncertainty?'

We explore confidence elicitation in LLM,revealing mitigation of LLMs' overconfidence. However,improvements are needed.

Arxiv: arxiv.org/abs/2306.13063

#LLM #Calibration #Uncertainty

New paper w/ Xiaoxin He, T. Laurent, Bryan Hooi 'Explanations as Features: LLM-Based Features for Text-Attributed Graphs'
ArXiv: arxiv.org/pdf/2305.19523…
GitHub: github.com/XiaoxinHe/TAPE

🚀Awesome-Graph-LLM

Check out this GitHub repo for a collection of AWESOME things about Graph-Related Large Language Models (LLMs): github.com/XiaoxinHe/Awes…