Cybersecurity has always been the focus of Internet research. Malware refers to software intentionally designed to harm computer systems, networks, ...

Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

研究团队张犬俊，房春荣，谢杨，张雅欣，虞圣呈，陈振宇：南京大学孙伟松：南洋理工大学杨耘：斯威本科技大学#大语言模型，#软件工程，#人工智能，#智能软件工程引用本文: Zhang Q J, Fang C R, Xie Y, et al. A survey on large language models for software engineering. Sci China Inf Sci, 202 ...

Microsoft launches three in-house AI models for transcription, voice, and image generation, challenging OpenAI and Google ...

Similar to BERT and GPT2, massive pre-trained encoder-decoder models have shown to significantly boost performance on a variety of sequence-to-sequence tasks Lewis et al. (2019), Raffel et al. (2019).

I noticed an inaccuracy in the model description between the README and the Technical Report. README: mentions "...unified encoder-decoder architecture..." Technical Report: states "...adopts a ...

Abstract: Long-term time-series forecasting remains a critical challenge, with deep learning models often facing persistent training instability. This study reveals a critical insight: the ...

Abstract: Code search is essential for code reuse, allowing developers to efficiently locate relevant code snippets. The advent of powerful decoder-only Large Language Models (LLMs) has revolutionized ...

Why was a new multilingual encoder needed? XLM-RoBERTa (XLM-R) has dominated multilingual NLP for more than 5 years, an unusually long reign in AI research. While encoder-only models like BERT and ...