Trending Research
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Foundation models, now powering most of the exciting applications in deep learning, are almost universally based on the Transformer architecture and its core attention module.
Pearl: A Production-ready Reinforcement Learning Agent
Reinforcement Learning (RL) offers a versatile framework for achieving long-term goals.
An LLM Compiler for Parallel Function Calling
LLMCompiler automatically computes an optimized orchestration for the function calls and can be used with open-source models such as LLaMA-2.
DemoFusion: Democratising High-Resolution Image Generation With No $$$
High-resolution image generation with Generative Artificial Intelligence (GenAI) has immense potential but, due to the enormous capital investment required for training, it is increasingly centralised to a few large corporations, and hidden behind paywalls.
Self-conditioned Image Generation via Generating Representations
LTH14/rcg
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During generation, RCG samples from such representation distribution using a representation diffusion model (RDM), and employs a pixel generator to craft image pixels conditioned on the sampled representation.
Ranked #1 on
Unconditional Image Generation
on ImageNet 256x256
Magicoder: Source Code Is All You Need
Magicoder models are trained on 75K synthetic instruction data using OSS-Instruct, a novel approach to enlightening LLMs with open-source code snippets to generate high-quality instruction data for code.
Style Aligned Image Generation via Shared Attention
Large-scale Text-to-Image (T2I) models have rapidly gained prominence across creative fields, generating visually compelling outputs from textual prompts.
Sequential Modeling Enables Scalable Learning for Large Vision Models
We introduce a novel sequential modeling approach which enables learning a Large Vision Model (LVM) without making use of any linguistic data.
Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation
prs-eth/marigold
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Monocular depth estimation is a fundamental computer vision task.
TaskWeaver: A Code-First Agent Framework
TaskWeaver provides support for rich data structures, flexible plugin usage, and dynamic plugin selection, and leverages LLM coding capabilities for complex logic.
