Muse: Text-To-Image Generation via Masked Generative Transformers

📝Compared to pixel-space diffusion models, such as Imagen and DALL-E 2, Muse is significantly more efficient due to the use of discrete tokens and requiring fewer sampling iterations; compared to autoregressive models, such as Parti, Muse is more efficient due to the use of parallel decoding.

https://github.com/lucidrains/muse-pytorch

A Survey for In-context Learning

📝With the increasing ability of large language models (LLMs), in-context learning (ICL) has become a new paradigm for natural language processing (NLP), where LLMs make predictions only based on contexts augmented with a few training examples.

https://github.com/dqxiu/icl_paperlist

Reasoning over Different Types of Knowledge Graphs: Static, Temporal and Multi-Modal

📝The early works in this domain mainly focus on static KGR and tend to directly apply general knowledge graph embedding models to the reasoning task.

https://github.com/liangke23/awesome-knowledge-graph-reasoning

BanditPAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits

📝In these experiments, we observe that BanditPAM returns the same results as state-of-the-art PAM-like algorithms up to 4x faster while performing up to 200x fewer distance computations.https://github.com/ThrunGroup/BanditPAM

SegGPT: Segmenting Everything In Context

📝We unify various segmentation tasks into a generalist in-context learning framework that accommodates different kinds of segmentation data by transforming them into the same format of images.https://github.com/baaivision/painter

Instruction Tuning with GPT-4

📝Prior work has shown that finetuning large language models (LLMs) using machine-generated instruction-following data enables such models to achieve remarkable zero-shot capabilities on new tasks, and no human-written instructions are needed.https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM

HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in HuggingFace

📝Solving complicated AI tasks with different domains and modalities is a key step toward advanced artificial intelligence.https://github.com/microsoft/JARVIS

Segment Anything

📝We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation.https://github.com/facebookresearch/segment-anything

GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

📝In this paper, we address this challenge, and propose GPTQ, a new one-shot weight quantization method based on approximate second-order information, that is both highly-accurate and highly-efficient.https://github.com/thudm/chatglm-6b

SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation📝We present SadTalker, which generates 3D motion coefficients (head pose, expression) of the 3DMM from audio and implicitly modulates a novel 3D-aware face render for talking head generation.https://github.com/winfredy/sadtalker

Segment Everything Everywhere All at Once

📝https://github.com/ux-decoder/segment-everything-everywhere-all-at-once

ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation

📝https://github.com/thudm/imagereward

Self-Instruct: Aligning Language Model with Self Generated Instructions

📝https://github.com/databrickslabs/dolly

CAMEL: Communicative Agents for "Mind" Exploration of Large Scale Language Model Society

📝https://github.com/lightaime/camel

AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

📝https://github.com/microsoft/agieval

A Method for Animating Children's Drawings of the Human Figure

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

OpenAssistant Conversations -- Democratizing Large Language Model Alignment

📝https://github.com/laion-ai/open-assistant

HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge

📝https://github.com/scir-hi/huatuo-llama-med-chinese

Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved With Text

📝https://github.com/allenai/mmc4

Inpaint Anything: Segment Anything Meets Image Inpainting

📝https://github.com/geekyutao/inpaint-anything

Tool Learning with Foundation Models

📝https://github.com/openbmb/bmtools