Trending Research
ClickDiffusion: Harnessing LLMs for Interactive Precise Image Editing
We demonstrate that by serializing both an image and a multi-modal instruction into a textual representation it is possible to leverage LLMs to perform precise transformations of the layout and appearance of an image.
RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment
RLHFlow/RLHF-Reward-Modeling
•
•
Utilizing a reward model and a sufficient number of samples, our approach selects the high-quality samples, discarding those that exhibit undesired behavior, and subsequently enhancing the model by fine-tuning on these filtered samples.
CDFormer:When Degradation Prediction Embraces Diffusion Model for Blind Image Super-Resolution
i2-multimedia-lab/cdformer
•
•
Existing Blind image Super-Resolution (BSR) methods focus on estimating either kernel or degradation information, but have long overlooked the essential content details.
Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts
hitsz-tmg/umoe-scaling-unified-multimodal-llms
•
•
Although the Mixture of Experts (MoE) architecture has been employed to efficiently scale large language and image-text models, these efforts typically involve fewer experts and limited modalities.
GIVT: Generative Infinite-Vocabulary Transformers
google-research/big_vision
•
•
We introduce generative infinite-vocabulary transformers (GIVT) which generate vector sequences with real-valued entries, instead of discrete tokens from a finite vocabulary.
Ranked #13 on
Image Generation
on ImageNet 256x256
Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models
We study how to apply large language models to write grounded and organized long-form articles from scratch, with comparable breadth and depth to Wikipedia pages.
Real-time Transformer-based Open-Vocabulary Detection with Efficient Fusion Head
om-ai-lab/OmDet
•
•
End-to-end transformer-based detectors (DETRs) have shown exceptional performance in both closed-set and open-vocabulary object detection (OVD) tasks through the integration of language modalities.
Improving Diffusion Models for Virtual Try-on
yisol/IDM-VTON
•
•
Finally, we present a customization method using a pair of person-garment images, which significantly improves fidelity and authenticity.
Ranked #1 on
Virtual Try-on
on VITON-HD
Kolmogorov-Arnold Networks are Radial Basis Function Networks
ZiyaoLi/fast-kan
•
•
This short paper is a fast proof-of-concept that the 3-order B-splines used in Kolmogorov-Arnold Networks (KANs) can be well approximated by Gaussian radial basis functions.
Speaker Embedding-aware Neural Diarization for Flexible Number of Speakers with Textual Information
alibaba-damo-academy/FunASR
•
•
In this paper, we reformulate this task as a single-label prediction problem by encoding the multi-speaker labels with power set.
