activity
20232026
most citedLarge Language Models for Generative Information Extraction: A Survey

24 citations · 54 across the 34 of their papers we have counts for

collaborators
Showing 2025Show all

8 papers · 1 filter

cs.AI2025

Look as You Think: Unifying Reasoning and Visual Evidence Attribution for Verifiable Document RAG via Reinforcement Learning

Shuochen Liu, Pengfei Luo, Chao Zhang +6

Aiming to identify precise evidence sources from visual documents, visual evidence attribution for visual document retrieval-augmented generation (VD-RAG) ensures reliable and veri…

cs.IR2025

TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework

Chao Zhang, Yuhao Wang, Derong Xu +9

Retrieval-Augmented Generation (RAG) utilizes external knowledge to augment Large Language Models' (LLMs) reliability. For flexibility, agentic RAG employs autonomous, multi-round…

cs.CL2025

A Survey on Parallel Reasoning

Ziqi Wang, Boye Niu, Zipeng Gao +10

With the increasing capabilities of Large Language Models (LLMs), parallel reasoning has emerged as a new inference paradigm that enhances reasoning robustness by concurrently expl…

cs.AI2025

A2R: An Asymmetric Two-Stage Reasoning Framework for Parallel Reasoning

Ziqi Wang, Boye Niu, Zhongli Li +7

Recent Large Reasoning Models have achieved significant improvements in complex task-solving capabilities by allocating more computation at the inference stage with a "thinking lon…

cs.CL2025★ 1 cited

From Single to Multi-Granularity: Toward Long-Term Memory Association and Selection of Conversational Agents

Derong Xu, Yi Wen, Pengyue Jia +8

Large Language Models (LLMs) have recently been widely adopted in conversational agents. However, the increasingly long interactions between users and agents accumulate extensive d…

cs.CL2025

Align-GRAG: Anchor and Rationale Guided Dual Alignment for Graph Retrieval-Augmented Generation

Derong Xu, Pengyue Jia, Xiaopeng Li +9

Despite the strong abilities, large language models (LLMs) still suffer from hallucinations and reliance on outdated knowledge, raising concerns in knowledge-intensive tasks. Graph…

cs.IR2025

ImageScope: Unifying Language-Guided Image Retrieval via Large Multimodal Model Collective Reasoning

Pengfei Luo, Jingbo Zhou, Tong Xu +3

With the proliferation of images in online content, language-guided image retrieval (LGIR) has emerged as a research hotspot over the past decade, encompassing a variety of subtask…

cs.CL2025★ 3 cited

Harnessing Large Language Models for Knowledge Graph Question Answering via Adaptive Multi-Aspect Retrieval-Augmentation

Derong Xu, Xinhang Li, Ziheng Zhang +7

Large Language Models (LLMs) demonstrate remarkable capabilities, yet struggle with hallucination and outdated knowledge when tasked with complex knowledge reasoning, resulting in…