Trending Research
Fine-Tuning Language Models from Human Preferences
carperai/trlx
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Most work on reward learning has used simulated environments, but complex information about values is often expressed in natural language, and we believe reward learning for language is a key to making RL practical and safe for real-world tasks.
StyleGANEX: StyleGAN-Based Manipulation Beyond Cropped Aligned Faces
williamyang1991/styleganex
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Recent advances in face manipulation using StyleGAN have produced impressive results.
SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving
Towards a more comprehensive perception of a 3D scene, in this paper, we propose a SurroundOcc method to predict the 3D occupancy with multi-camera images.
LoRA: Low-Rank Adaptation of Large Language Models
We propose Low-Rank Adaptation, or LoRA, which freezes the pre-trained model weights and injects trainable rank decomposition matrices into each layer of the Transformer architecture, greatly reducing the number of trainable parameters for downstream tasks.
unilm
microsoft/unilm
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NAACL 2021
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Prismer: A Vision-Language Model with An Ensemble of Experts
nvlabs/prismer
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Recent vision-language models have shown impressive multi-modal generation capabilities.
Ranked #1 on
Image Captioning
on nocaps val
Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling
keyu-tian/spark
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This is the first use of sparse convolution for 2D masked modeling.
Ranked #1 on
Instance Segmentation
on COCO 2017 val
BiFormer: Vision Transformer with Bi-Level Routing Attention
As the core building block of vision transformers, attention is a powerful tool to capture long-range dependency.
Ranked #3 on
Object Detection
on COCO 2017
(mAP metric)
T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models
The incredible generative ability of large-scale text-to-image (T2I) models has demonstrated strong power of learning complex structures and meaningful semantics.
DIRE for Diffusion-Generated Image Detection
We find that existing detectors struggle to detect images generated by diffusion models, even if we include generated images from a specific diffusion model in their training data.
