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Found 54 papers, 22 papers with code
How NLP Can Strengthen Digital Game Based Language Learning Resources for Less Resourced Languages
This paper provides an overview of the Cipher engine which enables the development of a Digital Educational Game (DEG) based on noticing ciphers or patterns in texts.
A Corpus-based Study of Corporate Image Represented in Corporate Social Responsibility Report: A Case Study of China Mobile and Vodafone
By examination of the high-frequency nouns, verbs, and keywords, the present study probes into the similarities and differences of corporate images represented in Corporate Social Responsibility (CSR) reports of China Mobile and Vodafone.
Faoi Gheasa an adaptive game for Irish language learning
This paper will focus on the language materials development as this is a bottleneck in the teaching and learning of minority and endangered languages.
Cipher – Faoi Gheasa: A Game-with-a-Purpose for Irish
This paper describes Cipher – Faoi Gheasa, a ‘game with a purpose’ designed to support the learning of Irish in a fun and enjoyable way.
Neural Exponential Stabilization of Control-affine Nonlinear Systems
Third, this parametrization and the inequality condition enable the design of contractivity-enforcing regularizers, which can be incorporated while designing the NN controller for exponential stabilization of the underlying nonlinear systems.
ReGenNet: Towards Human Action-Reaction Synthesis
Humans constantly interact with their surrounding environments.
Incorporating Graph Attention Mechanism into Geometric Problem Solving Based on Deep Reinforcement Learning
However, adding auxiliary components automatically is challenging due to the complexity in selecting suitable auxiliary components especially when pivotal decisions have to be made.
Structured Deep Neural Networks-Based Backstepping Trajectory Tracking Control for Lagrangian Systems
In addition, improved control performance can be achieved by further optimizing neural network parameters.
Inter-X: Towards Versatile Human-Human Interaction Analysis
We also equip Inter-X with versatile annotations of more than 34K fine-grained human part-level textual descriptions, semantic interaction categories, interaction order, and the relationship and personality of the subjects.
SC-Safety: A Multi-round Open-ended Question Adversarial Safety Benchmark for Large Language Models in Chinese
To systematically assess the safety of Chinese LLMs, we introduce SuperCLUE-Safety (SC-Safety) - a multi-round adversarial benchmark with 4912 open-ended questions covering more than 20 safety sub-dimensions.
Duration-adaptive Video Highlight Pre-caching for Vehicular Communication Network
Specifically, a highlight entropy model is devised with the consideration of the segments' popularity and continuity between segments within a period of time, based on which, an optimization problem of video highlight pre-caching is formulated.
Federated Learning in Big Model Era: Domain-Specific Multimodal Large Models
Preliminary experiments show that enterprises can enhance and accumulate intelligent capabilities through multimodal model federated learning, thereby jointly creating an smart city model that provides high-quality intelligent services covering energy infrastructure safety, residential community security, and urban operation management.
MCPA: Multi-scale Cross Perceptron Attention Network for 2D Medical Image Segmentation
The Cross Perceptron first captures the local correlations using multiple Multi-scale Cross Perceptron modules, facilitating the fusion of features across scales.
SuperCLUE: A Comprehensive Chinese Large Language Model Benchmark
We fill this gap by proposing a comprehensive Chinese benchmark SuperCLUE, named after another popular Chinese LLM benchmark CLUE.
A Surrogate Data Assimilation Model for the Estimation of Dynamical System in a Limited Area
We propose a novel learning-based surrogate data assimilation (DA) model for efficient state estimation in a limited area.
P-vectors: A Parallel-Coupled TDNN/Transformer Network for Speaker Verification
Typically, the Time-Delay Neural Network (TDNN) and Transformer can serve as a backbone for Speaker Verification (SV).
Discovering A Variety of Objects in Spatio-Temporal Human-Object Interactions
In daily HOIs, humans often interact with a variety of objects, e. g., holding and touching dozens of household items in cleaning.
Phased Progressive Learning with Coupling-Regulation-Imbalance Loss for Imbalanced Data Classification
This loss is effective in addressing quantity imbalances and outliers, while regulating the focus of attention on samples with varying classification difficulties.
Robust Classification using Contractive Hamiltonian Neural ODEs
Since in NODEs the input data corresponds to the initial condition of dynamical systems, we show contractivity can mitigate the effect of input perturbations.
ActFormer: A GAN-based Transformer towards General Action-Conditioned 3D Human Motion Generation
We present a GAN-based Transformer for general action-conditioned 3D human motion generation, including not only single-person actions but also multi-person interactive actions.
HAKE: A Knowledge Engine Foundation for Human Activity Understanding
Human activity understanding is of widespread interest in artificial intelligence and spans diverse applications like health care and behavior analysis.
The Observability in Unobservable Systems
In this paper, we introduce the concept of observability of targeted state variables for systems that may not be fully observable.
Data-Driven Computational Methods for the Domain of Attraction and Zubov's Equation
We prove that a neural network approximation exists for the Lyapunov function of power systems such that the approximation error is a cubic polynomial of the number of generators.
Neural Energy Casimir Control for Port-Hamiltonian Systems
The energy Casimir method is an effective controller design approach to stabilize port-Hamiltonian systems at a desired equilibrium.
DataCLUE: A Benchmark Suite for Data-centric NLP
However, we have not seen significant research progress in this field, especially in NLP.
Skeleton-Based Mutually Assisted Interacted Object Localization and Human Action Recognition
Skeleton data carries valuable motion information and is widely explored in human action recognition.
Yuan 1.0: Large-Scale Pre-trained Language Model in Zero-Shot and Few-Shot Learning
With this method, Yuan 1. 0, the current largest singleton language model with 245B parameters, achieves excellent performance on thousands GPUs during training, and the state-of-the-art results on NLP tasks.
Non Vanishing Gradients for Arbitrarily Deep Neural Networks: a Hamiltonian System Approach
Deep Neural Networks (DNNs) training can be difficult due to vanishing or exploding gradients during weight optimization through backpropagation.
FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark
While different learning schemes -- fine-tuning, zero-shot, and few-shot learning -- have been widely explored and compared for languages such as English, there is comparatively little work in Chinese to fairly and comprehensively evaluate and compare these methods and thus hinders cumulative progress.
Evaluating Modules in Graph Contrastive Learning
The recent emergence of contrastive learning approaches facilitates the application on graph representation learning (GRL), introducing graph contrastive learning (GCL) into the literature.
Hamiltonian Deep Neural Networks Guaranteeing Non-vanishing Gradients by Design
Deep Neural Networks (DNNs) training can be difficult due to vanishing and exploding gradients during weight optimization through backpropagation.
A unified framework for Hamiltonian deep neural networks
Training deep neural networks (DNNs) can be difficult due to the occurrence of vanishing/exploding gradients during weight optimization.
An Alignment-Agnostic Model for Chinese Text Error Correction
Most existing models based on detect-correct framework can correct mistaken characters errors, but they cannot deal with missing or redundant characters.
Direct evidence of the gradient drift instability being the origin of a rotating spoke in a crossed field plasma
A plasma rotating spoke in a crossed field discharge is studied using 2D radial-azimuthal fully kinetic Particle-In-Cell Monte Carlo Collision (PIC/MCC) simulations.
Super-Resolution
Plasma Physics
Finite-sample-based Spectral Radius Estimation and Stabilizability Test for Networked Control Systems
In the analysis and control of discrete-time linear time-invariant systems, the spectral radius of the system state matrix plays an essential role.
Optimization and Control Systems and Control Systems and Control
Transferable Interactiveness Knowledge for Human-Object Interaction Detection
Human-Object Interaction (HOI) detection is an important problem to understand how humans interact with objects.
Ranked #28 on
Human-Object Interaction Detection
on V-COCO
Pushing the Envelope of Thin Crack Detection
We experimentally show that this makes it possible to detect cracks from an image of one-third the resolution of images used for annotation with about the same accuracy.
NVAE-GAN Based Approach for Unsupervised Time Series Anomaly Detection
In recent studies, Lots of work has been done to solve time series anomaly detection by applying Variational Auto-Encoders (VAEs).
Low-cost and high-performance data augmentation for deep-learning-based skin lesion classification
At the network search stage, the DCNNs are fine-tuned with the full training set in order to select the model with the highest BACC.
Quantum-limited Localisation and Resolution in Three Dimensions
As a method to extract information from optical system, imaging can be viewed as a parameter estimation problem.
Quantum Physics Optics
On Consensusability of Linear Interconnected Multi-Agent Systems and Simultaneous Stabilization
Consensusability of multi-agent systems (MASs) certifies the existence of a distributed controller capable of driving the states of each subsystem to a consensus value.
OCNLI: Original Chinese Natural Language Inference
In this paper, we present the first large-scale NLI dataset (consisting of ~56, 000 annotated sentence pairs) for Chinese called the Original Chinese Natural Language Inference dataset (OCNLI).
Cipher: A Prototype Game-with-a-Purpose for Detecting Errors in Text
Errors commonly exist in machine-generated documents and publication materials; however, some correction algorithms do not perform well for complex errors and it is costly to employ humans to do the task.
CLUE: A Chinese Language Understanding Evaluation Benchmark
The advent of natural language understanding (NLU) benchmarks for English, such as GLUE and SuperGLUE allows new NLU models to be evaluated across a diverse set of tasks.
PaStaNet: Toward Human Activity Knowledge Engine
In light of this, we propose a new path: infer human part states first and then reason out the activities based on part-level semantics.
Ranked #3 on
Human-Object Interaction Detection
on HICO
CLUECorpus2020: A Large-scale Chinese Corpus for Pre-training Language Model
In this paper, we introduce the Chinese corpus from CLUE organization, CLUECorpus2020, a large-scale corpus that can be used directly for self-supervised learning such as pre-training of a language model, or language generation.
CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese
In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese.
Chinese Named Entity Recognition
named-entity-recognition
+2
3D Objectness Estimation via Bottom-up Regret Grouping
Further ablation study also demonstrates the effectiveness of our grouping predictor and regret mechanism.
An ensemble CNN method for biomedical entity normalization
Different representations of the same concept could often be seen in scientific reports and publications.
Ranked #2 on
Medical Concept Normalization
on BB-norm-phenotype
HAKE: Human Activity Knowledge Engine
To address these and promote the activity understanding, we build a large-scale Human Activity Knowledge Engine (HAKE) based on the human body part states.
Ranked #2 on
Human-Object Interaction Detection
on HICO
(using extra training data)
Hierarchical method for cataract grading based on retinal images using improved Haar wavelet
In this paper, a feature extraction-based method for grading cataract severity using retinal images is proposed.
Action Machine: Rethinking Action Recognition in Trimmed Videos
On NTU RGB-D, Action Machine achieves the state-of-the-art performance with top-1 accuracies of 97. 2% and 94. 3% on cross-view and cross-subject respectively.
Ranked #1 on
Action Recognition
on UTD-MHAD
Transferable Interactiveness Knowledge for Human-Object Interaction Detection
On account of the generalization of interactiveness, interactiveness network is a transferable knowledge learner and can be cooperated with any HOI detection models to achieve desirable results.
Ranked #29 on
Human-Object Interaction Detection
on V-COCO
