Trending Research
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)
YUAN 2.0: A Large Language Model with Localized Filtering-based Attention
In this work, the Localized Filtering-based Attention (LFA) is introduced to incorporate prior knowledge of local dependencies of natural language into Attention.
On Bringing Robots Home
notmahi/dobb-e
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We use the Stick to collect 13 hours of data in 22 homes of New York City, and train Home Pretrained Representations (HPR).
LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS
Recent advancements in real-time neural rendering using point-based techniques have paved the way for the widespread adoption of 3D representations.
GS-IR: 3D Gaussian Splatting for Inverse Rendering
We propose GS-IR, a novel inverse rendering approach based on 3D Gaussian Splatting (GS) that leverages forward mapping volume rendering to achieve photorealistic novel view synthesis and relighting results.
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.
LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models
Current VLMs, while proficient in tasks like image captioning and visual question answering, face computational burdens when processing long videos due to the excessive visual tokens.
OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving
wzzheng/occworld
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In this paper, we explore a new framework of learning a world model, OccWorld, in the 3D Occupancy space to simultaneously predict the movement of the ego car and the evolution of the surrounding scenes.
Animatable Gaussians: Learning Pose-dependent Gaussian Maps for High-fidelity Human Avatar Modeling
Overall, our method can create lifelike avatars with dynamic, realistic and generalized appearances.
UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition
1) We propose four architectural guidelines for designing large-kernel ConvNets, the core of which is to exploit the essential characteristics of large kernels that distinguish them from small kernels - they can see wide without going deep.
Ranked #1 on
Object Detection
on COCO 2017
(mAP metric)
