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20222026
most citedLasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model

69 citations · 174 across the 31 of their papers we have counts for

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Showing 2024 · cs.CLShow all

6 papers · 2 filters

cs.CL2024

MD: A Multimodal, Multilingual and Multitask Dataset for Grounded Document-level Information Extraction

Jiang Liu, Bobo Li, Xinran Yang +5

Multimodal information extraction (IE) tasks have attracted increasing attention because many studies have shown that multimodal information benefits text information extraction. H…

cs.CL2024

PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysis

Meng Luo, Hao Fei, Bobo Li +6

While existing Aspect-based Sentiment Analysis (ABSA) has received extensive effort and advancement, there are still gaps in defining a more holistic research target seamlessly int…

cs.CL2024

Revisiting Structured Sentiment Analysis as Latent Dependency Graph Parsing

Chengjie Zhou, Bobo Li, Hao Fei +3

Structured Sentiment Analysis (SSA) was cast as a problem of bi-lexical dependency graph parsing by prior studies. Multiple formulations have been proposed to construct the graph,…

cs.CL2024

Harvesting Events from Multiple Sources: Towards a Cross-Document Event Extraction Paradigm

Qiang Gao, Zixiang Meng, Bobo Li +4

Document-level event extraction aims to extract structured event information from unstructured text. However, a single document often contains limited event information and the rol…

cs.CL2024

Enhancing Cross-Document Event Coreference Resolution by Discourse Structure and Semantic Information

Qiang Gao, Bobo Li, Zixiang Meng +5

Existing cross-document event coreference resolution models, which either compute mention similarity directly or enhance mention representation by extracting event arguments (such…

cs.CL2024★ 1 cited

CMNER: A Chinese Multimodal NER Dataset based on Social Media

Yuanze Ji, Bobo Li, Jun Zhou +3

Multimodal Named Entity Recognition (MNER) is a pivotal task designed to extract named entities from text with the support of pertinent images. Nonetheless, a notable paucity of da…