2 papers
cs.IR2026
Beyond Chunks and Graphs: Retrieval-Augmented Generation through Triplet-Driven Thinking
Shengbo Gong, Xianfeng Tang, Qi He +2
Retrieval-augmented generation (RAG) is critical for reducing hallucinations and incorporating external knowledge into Large Language Models (LLMs). However, advanced RAG systems f…
cs.AI2026
Can Large Language Models Adequately Perform Symbolic Reasoning Over Time Series?
Zewen Liu, Juntong Ni, Xianfeng Tang +4
Uncovering hidden symbolic laws from time series data, as an aspiration dating back to Kepler's discovery of planetary motion, remains a core challenge in scientific discovery and…