779 citations
- Massachusetts Institute of TechnologyUS13 papers
- Harvard UniversityUS10 papers
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- Technical University of MunichDE9 papers
- Beijing Academy of Artificial IntelligenceCN8 papers
- Monash UniversityAU8 papers
- Shanghai Jiao Tong UniversityCN8 papers
- University of Hong KongHK8 papers
- Harvard University PressUS7 papers
- University of Southern CaliforniaUS7 papers
- Hong Kong University of Science and TechnologyHK6 papers
- Imperial College LondonGB6 papers
56 papers · 1 filter
Residual-SwinCA-Net: A Channel-Aware Integrated Residual CNN-Swin Transformer for Malignant Lesion Segmentation in BUSI
Saeeda Naz, Saddam Hussain Khan
A novel deep hybrid Residual-SwinCA-Net segmentation framework is proposed in the study for addressing such challenges by extracting locally correlated and robust features, incorpo…
Mitigating hallucinations in healthcare LLMs with granular fact-checking and domain-specific adaptation
Musarrat Zeba, Abdullah Al Mamun, Kishoar Jahan Tithee +8
In healthcare, it is essential for any Large Language Model (LLM)-generated output to be reliable and accurate, particularly in cases involving decision-making and patient safety.…
Skeletons Matter: Dynamic Data Augmentation for Text-to-Query
Yuchen Ji, Bo Xu, Jie Shi +5
The task of translating natural language questions into query languages has long been a central focus in semantic parsing. Recent advancements in Large Language Models (LLMs) have…
A Multifaceted Analysis of Negative Bias in Large Language Models through the Lens of Parametric Knowledge
Jongyoon Song, Sangwon Yu, Sungroh Yoon
Negative bias refers to the tendency of large language models (LLMs) to excessively generate negative responses in binary decision tasks (e.g., yes-no question answering). Previous…
LM-Fix: Lightweight Bit-Flip Detection and Rapid Recovery Framework for Language Models
Ahmad Tahmasivand, Noureldin Zahran, Saba Al-Sayouri +2
This paper presents LM-Fix, a lightweight detection and rapid recovery framework for faults in large language models (LLMs). Existing integrity approaches are often heavy or slow f…
Generative Artificial Intelligence in Bioinformatics: A Systematic Review of Models, Applications, and Methodological Advances
Wasimul Karim, Riasad Alvi, Sayeem Been Zaman +7
Generative artificial intelligence (GenAI) is transforming bioinformatics by advancing genomics, proteomics, transcriptomics, structural biology, and drug discovery. Following the…