Search Results for author:
Found 29 papers, 15 papers with code
SecureGS: Boosting the Security and Fidelity of 3D Gaussian Splatting Steganography
3D Gaussian Splatting (3DGS) has emerged as a premier method for 3D representation due to its real-time rendering and high-quality outputs, underscoring the critical need to protect the privacy of 3D assets.
GaussianSeal: Rooting Adaptive Watermarks for 3D Gaussian Generation Model
With the advancement of AIGC technologies, the modalities generated by models have expanded from images and videos to 3D objects, leading to an increasing number of works focused on 3D Gaussian Splatting (3DGS) generative models.
OmniGuard: Hybrid Manipulation Localization via Augmented Versatile Deep Image Watermarking
To address these challenges, we propose OmniGuard, a novel augmented versatile watermarking approach that integrates proactive embedding with passive, blind extraction for robust copyright protection and tamper localization.
Understanding Layer Significance in LLM Alignment
We propose a novel approach to identify the important layers for LLM alignment (ILA).
FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Models
The rapid development of generative AI is a double-edged sword, which not only facilitates content creation but also makes image manipulation easier and more difficult to detect.
Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token Recycling
New candidate tokens from the decoding process are then used to update the matrix.
Make Some Noise: Unlocking Language Model Parallel Inference Capability through Noisy Training
To address this problem, we propose the Make Some Noise (MSN) training framework as a replacement for the supervised fine-tuning stage of the large language model.
Protect-Your-IP: Scalable Source-Tracing and Attribution against Personalized Generation
With the advent of personalized generation models, users can more readily create images resembling existing content, heightening the risk of violating portrait rights and intellectual property (IP).
GS-Hider: Hiding Messages into 3D Gaussian Splatting
Therefore, ensuring the security and fidelity of the original 3D scene while embedding information into the 3DGS point cloud files is an extremely challenging task.
Diffusion-Based Hierarchical Image Steganography
This paper introduces Hierarchical Image Steganography, a novel method that enhances the security and capacity of embedding multiple images into a single container using diffusion models.
V2A-Mark: Versatile Deep Visual-Audio Watermarking for Manipulation Localization and Copyright Protection
Meanwhile, we introduce a sample-level audio localization method and a cross-modal copyright extraction mechanism to couple the information of audio and video frames.
Recurrent Drafter for Fast Speculative Decoding in Large Language Models
We present Recurrent Drafter (ReDrafter), an advanced speculative decoding approach that achieves state-of-the-art speedup for large language models (LLMs) inference.
Adaptive Convolutional Neural Network for Image Super-resolution
The lower network utilizes a symmetric architecture to enhance relations of different layers to mine more structural information, which is complementary with a upper network for image super-resolution.
Python is Not Always the Best Choice: Embracing Multilingual Program of Thoughts
In this paper, we conduct comprehensive experiments on the programming languages used in PoT and find that no single language consistently delivers optimal performance across all tasks and models.
SAPT: A Shared Attention Framework for Parameter-Efficient Continual Learning of Large Language Models
Existing methods devise the learning module to acquire task-specific knowledge with parameter-efficient tuning (PET) block and the selection module to pick out the corresponding one for the testing input, aiming at handling the challenges of catastrophic forgetting and knowledge transfer in CL.
EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protection
In the era where AI-generated content (AIGC) models can produce stunning and lifelike images, the lingering shadow of unauthorized reproductions and malicious tampering poses imminent threats to copyright integrity and information security.
Image super-resolution via dynamic network
In this paper, we present a dynamic network for image super-resolution (DSRNet), which contains a residual enhancement block, wide enhancement block, feature refinement block and construction block.
Ranked #66 on
Image Super-Resolution
on Set14 - 4x upscaling
Self-Supervised Scalable Deep Compressed Sensing
Compressed sensing (CS) is a promising tool for reducing sampling costs.
DiffLLE: Diffusion-guided Domain Calibration for Unsupervised Low-light Image Enhancement
Specifically, we adopt a naive unsupervised enhancement algorithm to realize preliminary restoration and design two zero-shot plug-and-play modules based on diffusion model to improve generalization and effectiveness.
Trajectory Generation and Tracking based on Energy Minimization for a Four-Link Brachiation Robot
Aiming to mimic the brachiation locomotion of primates, we establish a brachiation robot model capable of swinging between different bars.
CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography
Current image steganography techniques are mainly focused on cover-based methods, which commonly have the risk of leaking secret images and poor robustness against degraded container images.
CGCE: A Chinese Generative Chat Evaluation Benchmark for General and Financial Domains
Generative chat models, such as ChatGPT and GPT-4, have revolutionized natural language generation (NLG) by incorporating instructions and human feedback to achieve significant performance improvements.
Self-QA: Unsupervised Knowledge Guided Language Model Alignment
Large-scale language models like ChatGPT and GPT-4 have gained attention for their impressive conversational and generative capabilities.
XuanYuan 2.0: A Large Chinese Financial Chat Model with Hundreds of Billions Parameters
In recent years, pre-trained language models have undergone rapid development with the emergence of large-scale models.
Progressive Content-aware Coded Hyperspectral Compressive Imaging
Hyperspectral imaging plays a pivotal role in a wide range of applications, like remote sensing, medicine, and cytology.
Generative Adversarial Networks for Image Super-Resolution: A Survey
Second, we present popular architectures for GANs in big and small samples for image applications.
TranS: Transition-based Knowledge Graph Embedding with Synthetic Relation Representation
Knowledge graph embedding (KGE) aims to learn continuous vectors of relations and entities in knowledge graph.
Ranked #8 on
Link Property Prediction
on ogbl-wikikg2
HerosNet: Hyperspectral Explicable Reconstruction and Optimal Sampling Deep Network for Snapshot Compressive Imaging
Hyperspectral imaging is an essential imaging modality for a wide range of applications, especially in remote sensing, agriculture, and medicine.
MC\^2: Multi-perspective Convolutional Cube for Conversational Machine Reading Comprehension
Conversational machine reading comprehension (CMRC) extends traditional single-turn machine reading comprehension (MRC) by multi-turn interactions, which requires machines to consider the history of conversation.
Conversational Question Answering
Machine Reading Comprehension
