10 papers
Is GraphRAG Needed? From Basic RAG to Graph-/Agentic Solutions with Context Optimization
Long Chen, Ryan Razkenari, Yuxuan Zhou +5
As advanced RAG variants like GraphRAG and Agentic RAG emerge, one leading question is when and how to use them. Here, we introduce a framework for different RAG scenarios evaluati…
TACO: Task-Aware Column Description Generation Using LLMs
Ting Cai, Rakesh R. Menon, Yiru Chen +8
Generating accurate and informative column descriptions (e.g. "membership status of customers" for the column name "cust_mem") is essential for a wide range of downstream NLP tasks…
Enhancing Multi-Agent Communication through Attention Steering with Context Relevance
Hongxiang Zhang, Yuan Tian, Tianyi Zhang
LLM-based multi-agent systems have demonstrated remarkable performance on complex tasks through collaborative reasoning. However, these systems tend to rapidly accumulate extremely…
ISEE: Interactive Semantic Enrichment for Database Fields
Yuan Tian, Yiru Chen, Rakesh R. Menon +8
LLM-based agents are increasingly being deployed for data-related tasks, including data sense-making, exploration, and retrieval. However, their performance heavily depends on the…
Attention-Aligned Reasoning for Large Language Models
Hongxiang Zhang, Yuan Tian, Tianyi Zhang
Large Language Models (LLMs) tend to generate a long reasoning chain when solving complex tasks. However, as the reasoning chain extends, critical intermediate steps and the origin…
EvoSchema: Towards Text-to-SQL Robustness Against Schema Evolution
Tianshu Zhang, Kun Qian, Siddhartha Sahai +4
Neural text-to-SQL models, which translate natural language questions (NLQs) into SQL queries given a database schema, have achieved remarkable performance. However, database schem…