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20242026
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cs.CL2026

A Systematic Survey of Semantic Role Labeling in the Era of Pretrained Language Models

Huiyao Chen, Meishan Zhang, Jing Li +4

Semantic role labeling (SRL) is a central natural language processing task for understanding predicate-argument structures within texts and enabling downstream applications. Despit…

cs.CL2025

Event Extraction in Large Language Model

Bobo Li, Xudong Han, Jiang Liu +11

Large language models (LLMs) and multimodal LLMs are changing event extraction (EE): prompting and generation can often produce structured outputs in zero shot or few shot settings…

cs.CL2025

LLMs Can Also Do Well! Breaking Barriers in Semantic Role Labeling via Large Language Models

Xinxin Li, Huiyao Chen, Chengjun Liu +4

Semantic role labeling (SRL) is a crucial task of natural language processing (NLP). Although generative decoder-based large language models (LLMs) have achieved remarkable success…

cs.CL2025

Contrastive Learning on LLM Back Generation Treebank for Cross-domain Constituency Parsing

Peiming Guo, Meishan Zhang, Jianling Li +2

Cross-domain constituency parsing is still an unsolved challenge in computational linguistics since the available multi-domain constituency treebank is limited. We investigate auto…

cs.CL2025

Language Models are Universal Embedders

Xin Zhang, Zehan Li, Yanzhao Zhang +4

In the large language model (LLM) revolution, embedding is a key component of various systems, such as retrieving knowledge or memories for LLMs or building content moderation filt…

cs.CL2025

GME: Improving Universal Multimodal Retrieval by Multimodal LLMs

Xin Zhang, Yanzhao Zhang, Wen Xie +7

Universal Multimodal Retrieval (UMR) aims to enable search across various modalities using a unified model, where queries and candidates can consist of pure text, images, or a comb…