Going Denser with Open-Vocabulary Part Segmentation

📝
https://github.com/facebookresearch/vlpart

Sparks of Artificial General Intelligence: Early experiments with GPT-4

📝
https://github.com/microsoft/guidance

FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention

📝
https://github.com/mit-han-lab/fastcomposer

VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks

📝
https://github.com/opengvlab/visionllm

Official pytorch implementation of "ControlVideo: Training-free Controllable Text-to-Video Generation"

📝
https://github.com/ybybzhang/controlvideo

EasySpider: A No-Code Visual System for Crawling the Web

📝https://github.com/NaiboWang/EasySpider

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

📝https://github.com/kyegomez/tree-of-thoughts

Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models

📝https://github.com/shihaozhaozsh/uni-controlnet

Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training

📝https://github.com/Liuhong99/Sophia

Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models

📝https://github.com/shi-labs/prompt-free-diffusion

ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation

📝https://github.com/thu-ml/prolificdreamer

Gorilla: Large Language Model Connected with Massive APIs

📝https://github.com/ShishirPatil/gorilla

QLoRA: Efficient Finetuning of Quantized LLMs

📝https://github.com/artidoro/qlora

Large Language Models as Tool Makers

📝Recent research shows the potential of enhancing the problem-solving ability of large language models (LLMs) through the use of external tools. However, prior work along this line depends on the availability of existing tools. In this work, we take an initial step towards removing this dependency by proposing a closed-loop framework, referred to as LLMs A s Tool M akers (LATM), where LLMs create their own reusable tools for problem-solving
https://github.com/ctlllll/llm-toolmaker

Fine-Tuning Language Models with Just Forward Passes

📝Fine-tuning language models (LMs) has yielded success on diverse downstream tasks, but as LMs grow in size, backpropagation requires a prohibitively large amount of memory.
https://github.com/princeton-nlp/MeZO

NeRO: Neural Geometry and BRDF Reconstruction of Reflective Objects from Multiview Images

📝We present a neural rendering-based method called NeRO for reconstructing the geometry and the BRDF of reflective objects from multiview images captured in an unknown environment.
https://github.com/liuyuan-pal/NeRO

SoundStorm: Efficient Parallel Audio Generation

📝We present SoundStorm, a model for efficient, non-autoregressive audio generation.
https://github.com/rishikksh20/SoundStorm-pytorch

CodeTF: One-stop Transformer Library for State-of-the-art Code LLM

📖In this paper, we present CodeTF, an open-source Transformer-based library for state-of-the-art Code LLMs and code intelligence.

https://github.com/salesforce/codetf

AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

📖Large language models (LLMs) have shown excellent performance on various tasks, but the astronomical model size raises the hardware barrier for serving (memory size) and slows down token generation (memory bandwidth).

https://github.com/mit-han-lab/llm-awq

Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles

📖Modern hierarchical vision transformers have added several vision-specific components in the pursuit of supervised classification performance.

https://github.com/facebookresearch/hiera