2 citations · 2 across the 4 of their papers we have counts for
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LLM+Graph@VLDB'2025 Workshop Summary
Yixiang Fang, Arijit Khan, Tianxing Wu +2
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…
Cost-Efficient RAG for Entity Matching with LLMs: A Blocking-based Exploration
Chuangtao Ma, Zeyu Zhang, Arijit Khan +2
Retrieval-augmented generation (RAG) enhances LLM reasoning in knowledge-intensive tasks, but existing RAG pipelines incur substantial retrieval and generation overhead when applie…
SQL-to-Text Generation with Weighted-AST Few-Shot Prompting
Sriom Chakrabarti, Chuangtao Ma, Arijit Khan +1
SQL-to-Text generation aims at translating structured SQL queries into natural language descriptions, thereby facilitating comprehension of complex database operations for non-tech…
Knowledge Graph-based Retrieval-Augmented Generation for Schema Matching
Chuangtao Ma, Sriom Chakrabarti, Arijit Khan +1
Traditional similarity-based schema matching methods are incapable of resolving semantic ambiguities and conflicts in domain-specific complex mapping scenarios due to missing commo…
LLM+KG@VLDB'24 Workshop Summary
Arijit Khan, Tianxing Wu, Xi Chen
The unification of large language models (LLMs) and knowledge graphs (KGs) has emerged as a hot topic. At the LLM+KG'24 workshop, held in conjunction with VLDB 2024 in Guangzhou, C…