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cs.CL2025
Weak-to-Strong GraphRAG: Aligning Weak Retrievers with Large Language Models for Graph-based Retrieval Augmented Generation
Deyu Zou, Yongqiang Chen, Mufei Li +5
Graph-based retrieval-augmented generation (RAG) enables large language models (LLMs) to ground responses with structured external knowledge from up-to-date knowledge graphs (KGs)…
cs.CL2025
On the Thinking-Language Modeling Gap in Large Language Models
Chenxi Liu, Yongqiang Chen, Tongliang Liu +3
System 2 reasoning is one of the defining characteristics of intelligence, which requires slow and logical thinking. Human conducts System 2 reasoning via the language of thoughts…
cs.AI2025★ 1 cited
Can Large Language Models Help Experimental Design for Causal Discovery?
Junyi Li, Yongqiang Chen, Chenxi Liu +5
Designing proper experiments and selecting optimal intervention targets is a longstanding problem in scientific or causal discovery. Identifying the underlying causal structure fro…