most citedRAKG:Document-level Retrieval Augmented Knowledge Graph Construction

2 citations · 2 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL2025

DeepWriter: A Fact-Grounded Multimodal Writing Assistant Based On Offline Knowledge Base

Song Mao, Lejun Cheng, Pinlong Cai +3

Large Language Models (LLMs) have demonstrated remarkable capabilities in various applications. However, their use as writing assistants in specialized domains like finance, medici…

cs.CL2025

From Ranking to Selection: A Simple but Efficient Dynamic Passage Selector for Retrieval Augmented Generation

Siyuan Meng, Junming Liu, Yirong Chen +5

Retrieval-augmented generation (RAG) systems are often bottlenecked by their reranking modules, which typically score passages independently and select a fixed Top-K size. This app…

cs.CV2025

Learning Only with Images: Visual Reinforcement Learning with Reasoning, Rendering, and Visual Feedback

Yang Chen, Yufan Shen, Wenxuan Huang +7

Multimodal Large Language Models (MLLMs) exhibit impressive performance across various visual tasks. Subsequent investigations into enhancing their visual reasoning abilities have…

cs.AI2025

LeanRAG: Knowledge-Graph-Based Generation with Semantic Aggregation and Hierarchical Retrieval

Yaoze Zhang, Rong Wu, Pinlong Cai +5

Retrieval-Augmented Generation (RAG) plays a crucial role in grounding Large Language Models by leveraging external knowledge, whereas the effectiveness is often compromised by the…

cs.IR20252 cited

RAKG:Document-level Retrieval Augmented Knowledge Graph Construction

Hairong Zhang, Jiaheng Si, Guohang Yan +5

With the rise of knowledge graph based retrieval-augmented generation (RAG) techniques such as GraphRAG and Pike-RAG, the role of knowledge graphs in enhancing the reasoning capabi…

cs.CV2025

Aligning Vision to Language: Annotation-Free Multimodal Knowledge Graph Construction for Enhanced LLMs Reasoning

Junming Liu, Siyuan Meng, Yanting Gao +7

Multimodal reasoning in Large Language Models (LLMs) struggles with incomplete knowledge and hallucination artifacts, challenges that textual Knowledge Graphs (KGs) only partially…