most citedCan LLMs like GPT-4 outperform traditional AI tools in dementia diagnosis? Maybe, but not today

9 citations · 10 across the 5 of their papers we have counts for

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cs.CL2025

Negative Matters: Multi-Granularity Hard-Negative Synthesis and Anchor-Token-Aware Pooling for Enhanced Text Embeddings

Tengyu Pan, Zhichao Duan, Zhenyu Li +4

Text embedding models are essential for various natural language processing tasks, enabling the effective encoding of semantic information into dense vector representations. These…

cs.CL2025

COMM:Concentrated Margin Maximization for Robust Document-Level Relation Extraction

Zhichao Duan, Tengyu Pan, Zhenyu Li +2

Document-level relation extraction (DocRE) is the process of identifying and extracting relations between entities that span multiple sentences within a document. Due to its realis…

cs.CL2023

FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering

Zhenyu Li, Sunqi Fan, Yu Gu +5

Knowledge base question answering (KBQA) is a critical yet challenging task due to the vast number of entities within knowledge bases and the diversity of natural language question…

cs.CL20239 cited

Can LLMs like GPT-4 outperform traditional AI tools in dementia diagnosis? Maybe, but not today

Zhuo Wang, Rongzhen Li, Bowen Dong +8

Recent investigations show that large language models (LLMs), specifically GPT-4, not only have remarkable capabilities in common Natural Language Processing (NLP) tasks but also e…

cs.CL20231 cited

Bridging the Language Gap: Knowledge Injected Multilingual Question Answering

Zhichao Duan, Xiuxing Li, Zhengyan Zhang +3

Question Answering (QA) is the task of automatically answering questions posed by humans in natural languages. There are different settings to answer a question, such as abstractiv…