Trending Research
SCEdit: Efficient and Controllable Image Diffusion Generation via Skip Connection Editing
modelscope/swift
•
•
Image diffusion models have been utilized in various tasks, such as text-to-image generation and controllable image synthesis.
AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
We then propose to search for the optimal per-channel scaling that protects the salient weights by observing the activation, not weights.
Arc2Face: A Foundation Model of Human Faces
This paper presents Arc2Face, an identity-conditioned face foundation model, which, given the ArcFace embedding of a person, can generate diverse photo-realistic images with an unparalleled degree of face similarity than existing models.
Ranked #1 on
Diffusion Personalization Tuning Free
on AgeDB
Multi-domain Learning for Updating Face Anti-spoofing Models
In this work, we study multi-domain learning for face anti-spoofing(MD-FAS), where a pre-trained FAS model needs to be updated to perform equally well on both source and target domains while only using target domain data for updating.
GraFIQs: Face Image Quality Assessment Using Gradient Magnitudes
We propose in this work a novel approach to assess the quality of face images based on inspecting the required changes in the pre-trained FR model weights to minimize differences between testing samples and the distribution of the FR training dataset.
TokenHMR: Advancing Human Mesh Recovery with a Tokenized Pose Representation
We address the problem of regressing 3D human pose and shape from a single image, with a focus on 3D accuracy.
SpaceByte: Towards Deleting Tokenization from Large Language Modeling
kjslag/spacebyte
•
•
Tokenization is widely used in large language models because it significantly improves performance.
Weak-to-Strong Extrapolation Expedites Alignment
Suppose we have a moderately trained LLM (e. g., trained to align with human preference) in hand, can we further exploit its potential and cheaply acquire a stronger model?
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism
Scaling up deep neural network capacity has been known as an effective approach to improving model quality for several different machine learning tasks.
Ranked #4 on
Fine-Grained Image Classification
on Birdsnap
(using extra training data)
EasySpider: A No-Code Visual System for Crawling the Web
As such, web-crawling is an essential tool for both computational and non-computational scientists to conduct research.
