Trending Research
DeepCache: Accelerating Diffusion Models for Free
Diffusion models have recently gained unprecedented attention in the field of image synthesis due to their remarkable generative capabilities.
NEFTune: Noisy Embeddings Improve Instruction Finetuning
openaccess-ai-collective/axolotl
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We show that language model finetuning can be improved, sometimes dramatically, with a simple augmentation.
Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models
Additionally, experiments on 18 datasets further demonstrate that Monkey surpasses existing LMMs in many tasks like Image Captioning and various Visual Question Answering formats.
GauHuman: Articulated Gaussian Splatting from Monocular Human Videos
skhu101/gauhuman
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We present, GauHuman, a 3D human model with Gaussian Splatting for both fast training (1 ~ 2 minutes) and real-time rendering (up to 189 FPS), compared with existing NeRF-based implicit representation modelling frameworks demanding hours of training and seconds of rendering per frame.
HierSpeech++: Bridging the Gap between Semantic and Acoustic Representation of Speech by Hierarchical Variational Inference for Zero-shot Speech Synthesis
Furthermore, we significantly improve the naturalness and speaker similarity of synthetic speech even in zero-shot speech synthesis scenarios.
Pose Anything: A Graph-Based Approach for Category-Agnostic Pose Estimation
This approach not only enables object pose generation based on arbitrary keypoint definitions but also significantly reduces the associated costs, paving the way for versatile and adaptable pose estimation applications.
Ranked #1 on
2D Pose Estimation
on MP-100
StyleCrafter: Enhancing Stylized Text-to-Video Generation with Style Adapter
To address these challenges, we introduce StyleCrafter, a generic method that enhances pre-trained T2V models with a style control adapter, enabling video generation in any style by providing a reference image.
Large Language Models on Graphs: A Comprehensive Survey
Besides, although LLMs have shown their pure text-based reasoning ability, it is underexplored whether such ability can be generalized to graph scenarios (i. e., graph-based reasoning).
MEDITRON-70B: Scaling Medical Pretraining for Large Language Models
epfllm/meditron
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Large language models (LLMs) can potentially democratize access to medical knowledge.
Ranked #1 on
Multiple Choice Question Answering (MCQA)
on MedMCQA
(Dev Set (Acc-%) metric)
Conditional Text Generation
Multiple Choice Question Answering (MCQA)
Improving Sample Quality of Diffusion Models Using Self-Attention Guidance
lllyasviel/fooocus
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ICCV 2023
Denoising diffusion models (DDMs) have attracted attention for their exceptional generation quality and diversity.
