Thus, we open-source a new AI agent library, AgentLite, which simplifies this process by offering a lightweight, user-friendly platform for innovating LLM agent reasoning, architectures, and applications with ease.
Knowledge distillation involves transferring soft labels from a teacher to a student using a shared temperature-based softmax function.
Ranked #1 on Knowledge Distillation on CIFAR-100
We introduce Chronos, a simple yet effective framework for pretrained probabilistic time series models.
Chest X-ray images are commonly used for predicting acute and chronic cardiopulmonary conditions, but efforts to integrate them with structured clinical data face challenges due to incomplete electronic health records (EHR).
We demonstrate that these directions can be used to augment the prompt text input with fine-grained control over attributes of specific subjects in a compositional manner (control over multiple attributes of a single subject) without having to adapt the diffusion model.
In this paper, we introduce FRESCO, intra-frame correspondence alongside inter-frame correspondence to establish a more robust spatial-temporal constraint.
To that end, we introduce a novel training-free technique named Attention Interpolation via Diffusion (AID).
In recent years, the application of multimodal large language models (MLLM) in various fields has achieved remarkable success.
Prompt compression is an innovative method for efficiently condensing input prompts while preserving essential information.
We present MegaBlocks, a system for efficient Mixture-of-Experts (MoE) training on GPUs.