3 citations · 10 across the 9 of their papers we have counts for
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cs.CL2024★ 1 cited
Potential and Limitations of LLMs in Capturing Structured Semantics: A Case Study on SRL
Ning Cheng, Zhaohui Yan, Ziming Wang +6
Large Language Models (LLMs) play a crucial role in capturing structured semantics to enhance language understanding, improve interpretability, and reduce bias. Nevertheless, an on…
cs.CL2024★ 2 cited
TransportationGames: Benchmarking Transportation Knowledge of (Multimodal) Large Language Models
Xue Zhang, Xiangyu Shi, Xinyue Lou +4
Large language models (LLMs) and multimodal large language models (MLLMs) have shown excellent general capabilities, even exhibiting adaptability in many professional domains such…
cs.CL2023
A Quality-based Syntactic Template Retriever for Syntactically-controlled Paraphrase Generation
Xue Zhang, Songming Zhang, Yunlong Liang +4
Existing syntactically-controlled paraphrase generation (SPG) models perform promisingly with human-annotated or well-chosen syntactic templates. However, the difficulty of obtaini…