Search Results for author:
Found 49 papers, 15 papers with code
Wizard of Tasks: A Novel Conversational Dataset for Solving Real-World Tasks in Conversational Settings
Conversational Task Assistants (CTAs) are conversational agents whose goal is to help humans perform real-world tasks.
Knowledge Transfer between Structured and Unstructured Sources for Complex Question Answering
More fine-grained analyses on transfer behaviors reveal the types of transferred knowledge and transfer patterns.
Adaptive Learning for Multi-view Stereo Reconstruction
Deep learning has recently demonstrated its excellent performance on the task of multi-view stereo (MVS).
Chain of Compression: A Systematic Approach to Combinationally Compress Convolutional Neural Networks
Convolutional neural networks (CNNs) have achieved significant popularity, but their computational and memory intensity poses challenges for resource-constrained computing systems, particularly with the prerequisite of real-time performance.
OpenMEDLab: An Open-source Platform for Multi-modality Foundation Models in Medicine
The emerging trend of advancing generalist artificial intelligence, such as GPTv4 and Gemini, has reshaped the landscape of research (academia and industry) in machine learning and many other research areas.
Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models
When LLMs perform zero-shot inference, they typically use a prompt with a task specification, and generate a completion.
BET: Explaining Deep Reinforcement Learning through The Error-Prone Decisions
To address this issue, we propose a novel self-interpretable structure, named Backbone Extract Tree (BET), to better explain the agent's behavior by identify the error-prone states.
Large Language Models Illuminate a Progressive Pathway to Artificial Healthcare Assistant: A Review
This has sparked significant interest in applying LLMs to enhance various aspects of healthcare, ranging from medical education to clinical decision support.
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
Large language models (LLMs) such as GPT-4 have exhibited remarkable performance in a variety of tasks, but this strong performance often comes with the high expense of using paid API services.
Few-Shot Domain Adaptation for Charge Prediction on Unprofessional Descriptions
Recent works considering professional legal-linguistic style (PLLS) texts have shown promising results on the charge prediction task.
Leveraging the Power of Data Augmentation for Transformer-based Tracking
Due to long-distance correlation and powerful pretrained models, transformer-based methods have initiated a breakthrough in visual object tracking performance.
Utilizing Large Language Models for Natural Interface to Pharmacology Databases
The drug development process necessitates that pharmacologists undertake various tasks, such as reviewing literature, formulating hypotheses, designing experiments, and interpreting results.
Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning
Coverage path planning (CPP) is the problem of finding a path that covers the entire free space of a confined area, with applications ranging from robotic lawn mowing to search-and-rescue.
MedFMC: A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image Classification
Foundation models, often pre-trained with large-scale data, have achieved paramount success in jump-starting various vision and language applications.
propnet: Propagating 2D Annotation to 3D Segmentation for Gastric Tumors on CT Scans
This model consists of a proposing stage for coarse segmentation and a refining stage for improved segmentation, using two-way branches for enhanced performance and an up-down strategy for efficiency.
NeuralMatrix: Compute the Entire Neural Networks with Linear Matrix Operations for Efficient Inference
The inherent diversity of computation types within individual Deep Neural Network (DNN) models imposes a corresponding need for a varied set of computation units within hardware processors.
Efficient Gridless DoA Estimation Method of Non-uniform Linear Arrays with Applications in Automotive Radars
This paper focuses on the gridless direction-of-arrival (DoA) estimation for data acquired by non-uniform linear arrays (NLAs) in automotive applications.
Reinforced Question Rewriting for Conversational Question Answering
Furthermore, human evaluation shows that our method can generate more accurate and detailed rewrites when compared to human annotations.
Vision-based Anti-UAV Detection and Tracking
It contains a detection dataset with a total of 10, 000 images and a tracking dataset with 20 videos that include short-term and long-term sequences.
Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation
Therefore, we propose a method called region-aware metric learning (RAML), which first separates the regions of the images and generates region-aware features for further metric learning.
Shape-Aware Monocular 3D Object Detection
In this paper, a single-stage monocular 3D object detection model is proposed.
Visible-Thermal UAV Tracking: A Large-Scale Benchmark and New Baseline
With the popularity of multi-modal sensors, visible-thermal (RGB-T) object tracking is to achieve robust performance and wider application scenarios with the guidance of objects' temperature information.
Ranked #2 on
Rgb-T Tracking
on GTOT
Multi-Scale Context-Guided Lumbar Spine Disease Identification with Coarse-to-fine Localization and Classification
Accurate and efficient lumbar spine disease identification is crucial for clinical diagnosis.
Online Deep Metric Learning via Mutual Distillation
Existing solutions either retrain the model from scratch or require the replay of old samples during the training.
Imitation of Manipulation Skills Using Multiple Geometries
Daily manipulation tasks are characterized by geometric primitives related to actions and object shapes.
Recursive Least Squares Policy Control with Echo State Network
However, limited by the strong correlation among sequential samples of the agent, ESN-based policy control algorithms are difficult to use the recursive least squares (RLS) algorithm to update the ESN's parameters.
OneFlow: Redesign the Distributed Deep Learning Framework from Scratch
Aiming at a simple, neat redesign of distributed deep learning frameworks for various parallelism paradigms, we present OneFlow, a novel distributed training framework based on an SBP (split, broadcast and partial-value) abstraction and the actor model.
Unsupervised Domain Adaptation in Semantic Segmentation Based on Pixel Alignment and Self-Training
This paper proposes an unsupervised cross-modality domain adaptation approach based on pixel alignment and self-training.
Contrastive Learning for Mitochondria Segmentation
However, due to the image degradation during the imaging process, the large variety of mitochondrial structures, as well as the presence of noise, artifacts and other sub-cellular structures, mitochondria segmentation is very challenging.
Video Annotation for Visual Tracking via Selection and Refinement
Deep learning based visual trackers entail offline pre-training on large volumes of video datasets with accurate bounding box annotations that are labor-expensive to achieve.
AKG: Automatic Kernel Generation for Neural Processing Units using Polyhedral Transformations
Existing tensor compilers have proven their effectiveness in deploying deep neural networks on general-purpose hardware like CPU and GPU, but optimizing for neural processing units (NPUs) is still challenging due to the heterogeneous compute units and complicated memory hierarchy.
BEFD: Boundary Enhancement and Feature Denoising for Vessel Segmentation
Blood vessel segmentation is crucial for many diagnostic and research applications.
Efficient Client Contribution Evaluation for Horizontal Federated Learning
In this paper an efficient method is proposed to evaluate the contributions of federated participants.
Phase-controlled pathway interferences and switchable fast-slow light in a cavity-magnon polariton system
We study the phase controlled transmission properties in a compound system consisting of a 3D copper cavity and an yttrium iron garnet (YIG) sphere.
Quantum Physics Applied Physics Optics
Finite Volume Element Methods for Two-Dimensional Time Fractional Reaction-Diffusion Equations on Triangular Grids
In this paper, the time fractional reaction-diffusion equations with the Caputo fractional derivative are solved by using the classical $L1$-formula and the finite volume element (FVE) methods on triangular grids.
Numerical Analysis Numerical Analysis 65N30, 65M60, 26A33 G.1.2; G.1.8
Skin disease diagnosis with deep learning: a review
As an important part of this article, we then review the literature involving deep learning methods for skin disease diagnosis from several aspects according to the specific tasks.
Optimizing the Memory Hierarchy by Compositing Automatic Transformations on Computations and Data
Optimizing compilers exploit the memory hierarchy using loop tiling and fusion, but these two transformations usually interfere with each other due to the oversight of transformations on data in memories.
Adversarial Training for Code Retrieval with Question-Description Relevance Regularization
Code retrieval is a key task aiming to match natural and programming languages.
Jointly Modeling Motion and Appearance Cues for Robust RGB-T Tracking
In this study, we propose a novel RGB-T tracking framework by jointly modeling both appearance and motion cues.
Ranked #4 on
Rgb-T Tracking
on GTOT
Easy-to-Hard: Leveraging Simple Questions for Complex Question Generation
This paper makes one of the first efforts toward automatically generating complex questions from knowledge graphs.
An End-to-End Framework for Cold Question Routing in Community Question Answering Services
Routing newly posted questions (a. k. a cold questions) to potential answerers with the suitable expertise in Community Question Answering sites (CQAs) is an important and challenging task.
PGU-net+: Progressive Growing of U-net+ for Automated Cervical Nuclei Segmentation
The experimental results show that the PGU-net+ has superior accuracy than the previous state-of-the-art methods on cervical nuclei segmentation.
Assembly of randomly placed parts realized by using only one robot arm with a general parallel-jaw gripper
The proposal in this paper is verified by a simulated assembly in which a robot arm completed the assembly process including parts picking from bin and a subsequent peg-in-hole assembly.
Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images
Segmenting coronary arteries is challenging, as classic unsupervised methods fail to produce satisfactory results and modern supervised learning (deep learning) requires manual annotation which is often time-consuming and can some time be infeasible.
ASCNet: Adaptive-Scale Convolutional Neural Networks for Multi-Scale Feature Learning
Such pixel-level dilation rates produce optimal receptive fields so that the information of objects with different sizes can be extracted at the corresponding scale.
Automated Segmentation of Pulmonary Lobes using Coordination-Guided Deep Neural Networks
The proposed model is trained and evaluated on a few publicly available datasets and has achieved the state-of-the-art accuracy with a mean Dice coefficient index of 0. 947 $\pm$ 0. 044.
Efficient Fully Convolution Neural Network for Generating Pixel Wise Robotic Grasps With High Resolution Images
This paper presents an efficient neural network model to generate robotic grasps with high resolution images.
Robotics
Automated Segmentation of Cervical Nuclei in Pap Smear Images using Deformable Multi-path Ensemble Model
Pap smear testing has been widely used for detecting cervical cancers based on the morphology properties of cell nuclei in microscopic image.
An End-to-End Deep Framework for Answer Triggering with a Novel Group-Level Objective
Given a question and a set of answer candidates, answer triggering determines whether the candidate set contains any correct answers.
