Ji Lin, Hongxu Yin, Wei Ping, Yao Lu, Pavlo Molchanov, Andrew Tao, Huizi Mao, Jan Kautz, Mohammad Shoeybi, Song Han ...

To fill this gap, we propose two attention-mechanism-based encoder–decoder models that incorporate multisource information: one is MAEDDI, which can predict DDIs, and the other is MAEDDIE, which can ...

According to Hugging Face, advancements in robotics have been slow, despite the growth in the AI space. The company says that this is due to a lack of high-quality and diverse data, and large language ...

This effort focuses on developing a technical specification to help publishers respond to increased AI scraping and to support a fair value exchange between content owners and LLM developers.

The research discusses various LLM architectures, including encoder-only models like DNABERT, decoder-only models such as DNAGPT, and encoder-decoder models like ENBED. The team employed a ...

Large language models (LLMs), when trained on extensive plant genomic data, can accurately predict gene functions and regula ...

Abstract: The output of a discrete-time Markov source must be encoded into a sequence of discrete variables. The encoded sequence is transmitted through a noisy channel to a receiver that must attempt ...

and then provide a combined response leveraging the strengths of said models. The available LLMs include: Unlike other chatbot platforms, Token Monster automatically identifies which LLM is best ...