Search Results for author:
Found 22 papers, 10 papers with code
Global Challenge for Safe and Secure LLMs Track 1
This paper introduces the Global Challenge for Safe and Secure Large Language Models (LLMs), a pioneering initiative organized by AI Singapore (AISG) and the CyberSG R&D Programme Office (CRPO) to foster the development of advanced defense mechanisms against automated jailbreaking attacks.
Diffusion-EXR: Controllable Review Generation for Explainable Recommendation via Diffusion Models
Denoising Diffusion Probabilistic Model (DDPM) has shown great competence in image and audio generation tasks.
Integrating Large Pre-trained Models into Multimodal Named Entity Recognition with Evidential Fusion
Multimodal Named Entity Recognition (MNER) is a crucial task for information extraction from social media platforms such as Twitter.
Localizing Anatomical Landmarks in Ocular Images using Zoom-In Attentive Networks
Therefore, localization has its unique challenges different from segmentation or detection.
CRAFT: Cross-Attentional Flow Transformer for Robust Optical Flow
This is mainly because the correlation volume, the basis of pixel matching, is computed as the dot product of the convolutional features of the two images.
Ranked #9 on
Optical Flow Estimation
on KITTI 2015 (train)
REFUGE2 Challenge: A Treasure Trove for Multi-Dimension Analysis and Evaluation in Glaucoma Screening
Here we release a multi-annotation, multi-quality, and multi-device color fundus image dataset for glaucoma analysis on an original challenge -- Retinal Fundus Glaucoma Challenge 2nd Edition (REFUGE2).
Few-Shot Domain Adaptation with Polymorphic Transformers
Thus, the chance of overfitting the annotations is greatly reduced, and the model can perform robustly on the target domain after being trained on a few annotated images.
Medical Image Segmentation Using Squeeze-and-Expansion Transformers
Medical image segmentation is important for computer-aided diagnosis.
Ranked #1 on
Brain Tumor Segmentation
on BRATS 2019
Feature Lenses: Plug-and-play Neural Modules for Transformation-Invariant Visual Representations
To make CNNs more invariant to transformations, we propose "Feature Lenses", a set of ad-hoc modules that can be easily plugged into a trained model (referred to as the "host model").
RoboCoDraw: Robotic Avatar Drawing with GAN-based Style Transfer and Time-efficient Path Optimization
The proposed RoboCoDraw system takes a real human face image as input, converts it to a stylized avatar, then draws it with a robotic arm.
Robotics Graphics
Multi-Instance Multi-Scale CNN for Medical Image Classification
Deep learning for medical image classification faces three major challenges: 1) the number of annotated medical images for training are usually small; 2) regions of interest (ROIs) are relatively small with unclear boundaries in the whole medical images, and may appear in arbitrary positions across the x, y (and also z in 3D images) dimensions.
Feature Aggregation Network for Video Face Recognition
We make the following contributions: first, we propose a meta attention-based aggregation scheme which adaptively and fine-grained weighs the feature along each feature dimension among all frames to form a compact and discriminative representation.
Facial Pose Estimation by Deep Learning from Label Distributions
Facial pose estimation has gained a lot of attentions in many practical applications, such as human-robot interaction, gaze estimation and driver monitoring.
Enhanced Attacks on Defensively Distilled Deep Neural Networks
In this paper, we first propose the epsilon-neighborhood attack, which can fool the defensively distilled networks with 100% success rate in the white-box setting, and it is fast to generate adversarial examples with good visual quality.
Laplacian-Steered Neural Style Transfer
However in the traditional optimization objective, low-level features of the content image are absent, and the low-level features of the style image dominate the low-level detail structures of the new image.
Dirichlet-vMF Mixture Model
This document is about the multi-document Von-Mises-Fisher mixture model with a Dirichlet prior, referred to as VMFMix.
PSDVec: a Toolbox for Incremental and Scalable Word Embedding
PSDVec is a Python/Perl toolbox that learns word embeddings, i. e. the mapping of words in a natural language to continuous vectors which encode the semantic/syntactic regularities between the words.
Generative Topic Embedding: a Continuous Representation of Documents (Extended Version with Proofs)
Word embedding maps words into a low-dimensional continuous embedding space by exploiting the local word collocation patterns in a small context window.
A Generative Word Embedding Model and its Low Rank Positive Semidefinite Solution
Most existing word embedding methods can be categorized into Neural Embedding Models and Matrix Factorization (MF)-based methods.
On the Equivalence of Factorized Information Criterion Regularization and the Chinese Restaurant Process Prior
We argue that when $D_{c}>2$, FIC avoids an inherent problem of DP/CRP, i. e. the data likelihood will dominate the impact of the prior, and thus the model selection capability will weaken as $D_{c}$ increases.
Factorized Asymptotic Bayesian Inference for Factorial Hidden Markov Models
Factorial hidden Markov models (FHMMs) are powerful tools of modeling sequential data.
