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cs.CL2026
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…
cs.CL2026
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…
cs.CL2025
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…