most citedCompressing Long Context for Enhancing RAG with AMR-based Concept Distillation

2 citations · 2 across the 3 of their papers we have counts for

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cs.CL2026

CoCR-RAG: Enhancing Retrieval-Augmented Generation in Web Q&A via Concept-oriented Context Reconstruction

Kaize Shi, Xueyao Sun, Qika Lin +4

Retrieval-augmented generation (RAG) has shown promising results in enhancing Q&A by incorporating information from the web and other external sources. However, the supporting docu…

cs.CL2026

Creative Convergence or Imitation? Genre-Specific Homogeneity in LLM-Generated Chinese Literature

Yuanchi Ma, Kaize Shi, Hui He +5

Large Language Models (LLMs) have demonstrated remarkable capabilities in narrative generation. However, they often produce structurally homogenized stories, frequently following r…

cs.CL2024★ 2 cited

Compressing Long Context for Enhancing RAG with AMR-based Concept Distillation

Kaize Shi, Xueyao Sun, Qing Li +1

Large Language Models (LLMs) have made significant strides in information acquisition. However, their overreliance on potentially flawed parametric knowledge leads to hallucination…