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20182026
most citedA Survey of Knowledge-Enhanced Text Generation

252 citations · 554 across the 32 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.DL2025

CiteGuard: Faithful Citation Attribution for LLMs via Retrieval-Augmented Validation

Yee Man Choi, Xuehang Guo, Yi R. Fung +1

Large Language Models (LLMs) have emerged as powerful assistants for scientific writing. However, concerns remain about the quality and reliability of the generated text, including…

cs.CL2025

Atomic Reasoning for Scientific Table Claim Verification

Yuji Zhang, Qingyun Wang, Cheng Qian +7

Scientific texts often convey authority due to their technical language and complex data. However, this complexity can sometimes lead to the spread of misinformation. Non-experts a…

cs.CV2025

MedEBench: Diagnosing Reliability in Text-Guided Medical Image Editing

Minghao Liu, Zhitao He, Zhiyuan Fan +2

Text-guided image editing has seen significant progress in natural image domains, but its application in medical imaging remains limited and lacks standardized evaluation framework…

cs.CL2025

Explain Less, Understand More: Data-Efficient Personalization of Reader-Dependent Jargons

Bohao Wu, Qingyun Wang, Yue Guo

Personalizing jargon detection and explanation is essential for making technical documents accessible to readers with diverse disciplinary backgrounds. However, tailoring models to…

cs.CL2025

MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness

Junsheng Huang, Zhitao He, Yucheng Huang +3

The hallucination of non-existent facts by LLMs is an important problem given its widespread adoption across various applications. Previous research addresses this problem by analy…

cs.CL2025

CALM: Unleashing the Cross-Lingual Self-Aligning Ability of Language Model Question Answering

Yumeng Wang, Zhiyuan Fan, Qingyun Wang +2

Large Language Models (LLMs) are pretrained on extensive multilingual corpora to acquire both language-specific cultural knowledge and general knowledge. Ideally, while LLMs should…