most citedA Survey on Retrieval And Structuring Augmented Generation with Large Language Models

15 citations · 16 across the 8 of their papers we have counts for

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cs.CL2026

MultiCube-RAG for Multi-hop Question Answering

Jimeng Shi, Wei Hu, Runchu Tian +8

Multi-hop question answering (QA) necessitates multi-step reasoning and retrieval across interconnected subjects, attributes, and relations. Existing retrieval-augmented generation…

cs.CL2025

Finish First, Perfect Later: Test-Time Token-Level Cross-Validation for Diffusion Large Language Models

Runchu Tian, Junxia Cui, Xueqiang Xu +2

Diffusion large language models (dLLMs) have recently emerged as a promising alternative to autoregressive (AR) models, offering advantages such as accelerated parallel decoding an…

cs.CL2025

Topic Coverage-based Demonstration Retrieval for In-Context Learning

Wonbin Kweon, SeongKu Kang, Runchu Tian +3

The effectiveness of in-context learning relies heavily on selecting demonstrations that provide all the necessary information for a given test input. To achieve this, it is crucia…

cs.CL2025★ 15 cited

A Survey on Retrieval And Structuring Augmented Generation with Large Language Models

Pengcheng Jiang, Siru Ouyang, Yizhu Jiao +3

Large Language Models (LLMs) have revolutionized natural language processing with their remarkable capabilities in text generation and reasoning. However, these models face critica…

cs.CL2025

Beyond True or False: Retrieval-Augmented Hierarchical Analysis of Nuanced Claims

Priyanka Kargupta, Runchu Tian, Jiawei Han

Claims made by individuals or entities are oftentimes nuanced and cannot be clearly labeled as entirely "true" or "false" -- as is frequently the case with scientific and political…