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20192026
most citedInformation Extraction from Clinical Notes: Are We Ready to Switch to Large Language Models?

9 citations · 10 across the 6 of their papers we have counts for

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cs.CL2025

When Agents Trade: Live Multi-Market Trading Benchmark for LLM Agents

Lingfei Qian, Xueqing Peng, Yan Wang +14

Although Large Language Model (LLM)-based agents are increasingly used in financial trading, it remains unclear whether they can reason and adapt in live markets, as most studies t…

cs.CL2025

MultiFinBen: Benchmarking Large Language Models for Multilingual and Multimodal Financial Application

Xueqing Peng, Lingfei Qian, Yan Wang +44

Real-world financial analysis involves information across multiple languages and modalities, from reports and news to scanned filings and meeting recordings. Yet most existing eval…

cs.CL20249 cited

Information Extraction from Clinical Notes: Are We Ready to Switch to Large Language Models?

Yan Hu, Xu Zuo, Yujia Zhou +9

Backgrounds: Information extraction (IE) is critical in clinical natural language processing (NLP). While large language models (LLMs) excel on generative tasks, their performance…

cs.CL2019

CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases

Tao Yu, Rui Zhang, He Yang Er +21

We present CoSQL, a corpus for building cross-domain, general-purpose database (DB) querying dialogue systems. It consists of 30k+ turns plus 10k+ annotated SQL queries, obtained f…

cs.CL2019

SParC: Cross-Domain Semantic Parsing in Context

Tao Yu, Rui Zhang, Michihiro Yasunaga +16

We present SParC, a dataset for cross-domainSemanticParsing inContext that consists of 4,298 coherent question sequences (12k+ individual questions annotated with SQL queries). It…