Search Results for author:
Found 9 papers, 7 papers with code
JailbreakLens: Visual Analysis of Jailbreak Attacks Against Large Language Models
Addressing these concerns necessitates a comprehensive analysis of jailbreak prompts to evaluate LLMs' defensive capabilities and identify potential weaknesses.
Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning
The surge in Large Language Models (LLMs) has revolutionized natural language processing, but fine-tuning them for specific tasks often encounters challenges in balancing performance and preserving general instruction-following abilities.
PromptMagician: Interactive Prompt Engineering for Text-to-Image Creation
Generative text-to-image models have gained great popularity among the public for their powerful capability to generate high-quality images based on natural language prompts.
CoSDA: Continual Source-Free Domain Adaptation
Recently, SFDA has gained popularity due to the need to protect the data privacy of the source domain, but it suffers from catastrophic forgetting on the source domain due to the lack of data.
Interactive Image Synthesis with Panoptic Layout Generation
In particular, the stuff layouts can take amorphous shapes and fill up the missing regions left out by the instance layouts.
Ranked #2 on
Layout-to-Image Generation
on Visual Genome 128x128
SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations
Semi-supervised variational autoencoders (VAEs) have obtained strong results, but have also encountered the challenge that good ELBO values do not always imply accurate inference results.
KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation
(2) A dynamic weighting strategy named Consensus Focus to identify both the malicious and irrelevant domains.
Knowledge Distillation
Multi-Source Unsupervised Domain Adaptation
+2
A Natural-language-based Visual Query Approach of Uncertain Human Trajectories
Visual querying is essential for interactively exploring massive trajectory data.
DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis
If the initial image is not well initialized, the following processes can hardly refine the image to a satisfactory quality.
Ranked #6 on
Text-to-Image Generation
on CUB
(Inception score metric)
