28 citations · 43 across the 13 of their papers we have counts for
4 papers · 1 filter
Locality-Sensitive Hashing-Based Efficient Point Transformer for Charged Particle Reconstruction
Shitij Govil, Jack P. Rodgers, Yuan-Tang Chou +9
Charged particle track reconstruction is a foundational task in collider experiments and the main computational bottleneck in particle reconstruction. Graph neural networks (GNNs)…
Weak-to-Strong GraphRAG: Aligning Weak Retrievers with Large Language Models for Graph-based Retrieval Augmented Generation
Deyu Zou, Yongqiang Chen, Mufei Li +5
Graph-based retrieval-augmented generation (RAG) enables large language models (LLMs) to ground responses with structured external knowledge from up-to-date knowledge graphs (KGs)…
Graph-KV: Breaking Sequence via Injecting Structural Biases into Large Language Models
Haoyu Wang, Peihao Wang, Mufei Li +4
Modern large language models (LLMs) are inherently auto-regressive, requiring input to be serialized into flat sequences regardless of their structural dependencies. This serializa…
Towards A Universal Graph Structural Encoder
Jialin Chen, Haolan Zuo, Haoyu Peter Wang +3
Recent advancements in large-scale pre-training have shown the potential to learn generalizable representations for downstream tasks. In the graph domain, however, capturing and tr…