Abstract: Given the overwhelming and rapidly increasing volumes of the published biomedical literature, automatic biomedical text summarization has long been a highly important task. Recently, great ...

Abstract: In the field of abstract text summarization, architectures based on encoder-decoder frameworks are widely applied to sequence-to-sequence generation tasks and can effectively handle ...

An interactive Natural Language Processing (NLP) application for abstractive document summarization using state-of-the-art Transformer models from Hugging Face. An interactive Natural Language ...

Background and Context of the Topic On r/LocalLLaMA, selecting models for agent use has become a major concern in practical operations. As Qwen3.6-122B has established itself as the de facto standard ...

Systems that can create summaries from conversations are in high demand in customer service, newsrooms and virtual assistants ...

In an increasingly competitive job market, some applicants are quietly trying to outsmart AI hiring tools. Now, new research ...

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...

aDepartment of Biomedical Informatics, Medical School, Harvard University, Boston, MA, United States of America bDepartment of Internal Medicine, University of Texas at Southwestern, Dallas, TX, ...

The KwaiKAT Team at Kuaishou has published the KAT-Coder-V2.5 technical report, arguing that agentic coding capability is bottlenecked by training infrastructure rather than model scale. AutoBuilder ...

'RW': Use the routing weights (RW) from the Mixture of Experts (MoE) model as the embedding. RW is often more robust to prompt variations and captures high-level semantic information. 'MoEE': Use a ...