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Found 38 papers, 9 papers with code
Discourse Self-Attention for Discourse Element Identification in Argumentative Student Essays
First, we propose structural sentence positional encodings to explicitly represent sentence positions.
Multi-Stage Pre-training for Automated Chinese Essay Scoring
This paper proposes a pre-training based automated Chinese essay scoring method.
Flickr30K-CFQ: A Compact and Fragmented Query Dataset for Text-image Retrieval
Text-image retrieval research is needed to realize high-quality and efficient retrieval between different modalities.
Adaptive Multi-modal Fusion of Spatially Variant Kernel Refinement with Diffusion Model for Blind Image Super-Resolution
Harnessing the potential of leveraging this a priori knowledge in the context of image super-resolution presents a compelling avenue.
Aligning Knowledge Graph with Visual Perception for Object-goal Navigation
Object-goal navigation is a challenging task that requires guiding an agent to specific objects based on first-person visual observations.
Target Recognition Algorithm for Monitoring Images in Electric Power Construction Process
To enhance precision and comprehensiveness in identifying targets in electric power construction monitoring video, a novel target recognition algorithm utilizing infrared imaging is explored.
Transmission Line Detection Based on Improved Hough Transform
To address the challenges of low detection accuracy and high false positive rates of transmission lines in UAV (Unmanned Aerial Vehicle) images, we explore the linear features and spatial distribution.
M2ConceptBase: A Fine-grained Aligned Multi-modal Conceptual Knowledge Base
To collect concept-image and concept-description alignments, we propose a context-aware multi-modal symbol grounding approach that considers context information in existing large-scale image-text pairs with respect to each concept.
Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning
In conclusion, the proposed pipeline, with its incorporation of self-supervised pre-training using MiM and other advanced deep learning techniques, emerges as a robust solution for enhancing the accuracy and efficiency of lane rendering image anomaly detection in digital navigation systems.
Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering
To this end, we propose an answer-sensitive KG-to-Text approach that can transform KG knowledge into well-textualized statements most informative for KGQA.
B2C-AFM: Bi-Directional Co-Temporal and Cross-Spatial Attention Fusion Model for Human Action Recognition
Human Action Recognition plays a driving engine of many human-computer interaction applications.
Ranked #19 on
Action Recognition
on NTU RGB+D
Fine-grained Text and Image Guided Point Cloud Completion with CLIP Model
In this work, we propose a novel multimodal fusion network for point cloud completion, which can simultaneously fuse visual and textual information to predict the semantic and geometric characteristics of incomplete shapes effectively.
Multivariate Time Series characterization and forecasting of VoIP traffic in real mobile networks
Predicting the behavior of real-time traffic (e. g., VoIP) in mobility scenarios could help the operators to better plan their network infrastructures and to optimize the allocation of resources.
Robust Calibrate Proxy Loss for Deep Metric Learning
The mainstream researche in deep metric learning can be divided into two genres: proxy-based and pair-based methods.
Fast Contextual Scene Graph Generation With Unbiased Context Augmentation
Therefore, at the context level, we can produce diverse context descriptions by using a context augmentation method based on the original dataset.
DPCNet: Dual Path Multi-Excitation Collaborative Network for Facial Expression Representation Learning in Videos
To obtain consistent prediction probabilities from the dual path, we further propose a dual path regularization loss, aiming to minimize the divergence between the distributions of two-path embeddings.
Ranked #13 on
Dynamic Facial Expression Recognition
on DFEW
Dynamic Facial Expression Recognition
Representation Learning
End-To-End Audiovisual Feature Fusion for Active Speaker Detection
After fusion, one BiGRU layer is attached to model the joint temporal dynamics.
TGRMPT: A Head-Shoulder Aided Multi-Person Tracker and a New Large-Scale Dataset for Tour-Guide Robot
A service robot serving safely and politely needs to track the surrounding people robustly, especially for Tour-Guide Robot (TGR).
IFlyEA: A Chinese Essay Assessment System with Automated Rating, Review Generation, and Recommendation
IFlyEA provides multi-level and multi-dimension analytical modules for essay assessment.
Verb Metaphor Detection via Contextual Relation Learning
Correct natural language understanding requires computers to distinguish the literal and metaphorical senses of a word.
Gated Transformer Networks for Multivariate Time Series Classification
In this work, we explored a simple extension of the current Transformer Networks with gating, named Gated Transformer Networks (GTN) for the multivariate time series classification problem.
Gravitational perturbations from NHEK to Kerr
Our aim is to characterise those perturbations that are responsible for the deviations away from extremality, and to contrast them with the linearized perturbations treated in the Newman-Penrose formalism.
High Energy Physics - Theory General Relativity and Quantum Cosmology
Improving Prosody Modelling with Cross-Utterance BERT Embeddings for End-to-end Speech Synthesis
Despite prosody is related to the linguistic information up to the discourse structure, most text-to-speech (TTS) systems only take into account that within each sentence, which makes it challenging when converting a paragraph of texts into natural and expressive speech.
MAB-Malware: A Reinforcement Learning Framework for Attacking Static Malware Classifiers
However, it is well-known that machine learning models are vulnerable to adversarial examples (AEs).
Cryptography and Security
Neural Simile Recognition with Cyclic Multitask Learning and Local Attention
Simile recognition is to detect simile sentences and to extract simile components, i. e., tenors and vehicles.
An Experimental-based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging
Underwater images play a key role in ocean exploration, but often suffer from severe quality degradation due to light absorption and scattering in water medium.
Building a mixed-lingual neural TTS system with only monolingual data
When deploying a Chinese neural text-to-speech (TTS) synthesis system, one of the challenges is to synthesize Chinese utterances with English phrases or words embedded.
Neural Multitask Learning for Simile Recognition
Simile is a special type of metaphor, where comparators such as like and as are used to compare two objects.
Exploiting Syntactic Structures for Humor Recognition
Humor recognition is an interesting and challenging task in natural language processing.
Modeling Sentiment Association in Discourse for Humor Recognition
Humor is one of the most attractive parts in human communication.
Chinese Grammatical Error Diagnosis using Statistical and Prior Knowledge driven Features with Probabilistic Ensemble Enhancement
This paper describes our system at NLPTEA-2018 Task {\#}1: Chinese Grammatical Error Diagnosis.
TRANSRW at SemEval-2018 Task 12: Transforming Semantic Representations for Argument Reasoning Comprehension
The task is to select the correct warrant that explains reasoning of a particular argument consisting of a claim and a reason.
Discourse Mode Identification in Essays
Evaluation results show that discourse modes can be identified automatically with an average F1-score of 0. 7.
Anecdote Recognition and Recommendation
More importantly, we uncover the anecdote implication, which reveals the meaning and topic of an anecdote.
Learning to Identify Sentence Parallelism in Student Essays
Parallelism is an important rhetorical device.
Representation Learning with Deconvolution for Multivariate Time Series Classification and Visualization
We propose a new model based on the deconvolutional networks and SAX discretization to learn the representation for multivariate time series.
Empirical Studies on Symbolic Aggregation Approximation Under Statistical Perspectives for Knowledge Discovery in Time Series
Our work provides an analytical framework with several statistical tools to analyze, evaluate and further improve the symbolic dynamics for knowledge discovery in time series.
