Research
LLM+Graph@VLDB'2025 Workshop Summary
arXiv:2604.02861v2 Announce Type: replace-cross Abstract: The integration of large language models (LLMs) with graph-structured data has become a pivotal and fast evolving research frontier, drawing s
arXiv:2604.02861v2 Announce Type: replace-cross Abstract: The integration of large language models (LLMs) with graph-structured data has become a pivotal and fast evolving research frontier, drawing strong interest from both academia and industry. The 2nd LLM+Graph Workshop, co-located with the 51st International Conference on Very Large Data Bases (VLDB 2025) in London, focused on advancing algorithms and systems that bridge LLMs, graph data management, and graph machine learning for practical applications. This report highlights the key research directions, challenges, and innovative solutions presented by the workshop's speakers.
Related
- LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification
- Stabilizing Unsupervised Self-Evolution of MLLMs via Continuous Softened Retracing reSampling
- Analytical FFN-to-MoE Restructuring via Activation Pattern Analysis
- A Survey of Inductive Reasoning for Large Language Models
Source: arXiv cs.AI | 2026-04-27