Hierarchical Reasoning Models (HRM) tackle complex reasoning tasks while being smaller, faster, and more data-efficient than large AI models.

It builds on the encoder-decoder model architecture where the input is encoded and passed to a decoder in a single pass as a fixed-length representation instead of the per-token processing ...

The CAGEC model employs an innovative dual-encoder structure, combining the encoder of the Transformer model with a Bi-GRU (Bidirectional Gated Recurrent Unit) neural network, and integrates encoding ...

Students often train large language models (LLMs) as part of a group. In that case, your group should implement robust access control on the platform used to train your models. The group administrator ...

This paper describes an inning summarization method for a baseball game by using an encoder-decoder model. Each inning in a baseball game contains some events, such as hits, strikeouts, homeruns and ...

In the current multi-modality support within vLLM, the vision encoder (e.g., Qwen_vl) and the language model decoder run within the same worker process. While this tightly coupled architecture is ...