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Found 28 papers, 7 papers with code
Distantly Supervised Relation Extraction using Multi-Layer Revision Network and Confidence-based Multi-Instance Learning
Distantly supervised relation extraction is widely used in the construction of knowledge bases due to its high efficiency.
Exploring Sentence Community for Document-Level Event Extraction
Document-level event extraction is critical to various natural language processing tasks for providing structured information.
MEL: Efficient Multi-Task Evolutionary Learning for High-Dimensional Feature Selection
By incorporating information sharing between different feature selection tasks, MEL achieves enhanced learning ability and efficiency.
Adversarial Bandits with Multi-User Delayed Feedback: Theory and Application
Thus, we formulate an adversarial MAB problem with multi-user delayed feedback and design a modified EXP3 algorithm MUD-EXP3, which makes a decision at each round by considering the importance-weighted estimator of the received feedback from different users.
A Fast Task Offloading Optimization Framework for IRS-Assisted Multi-Access Edge Computing System
Terahertz communication networks and intelligent reflecting surfaces exhibit significant potential in advancing wireless networks, particularly within the domain of aerial-based multi-access edge computing systems.
A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding
Result Attention Network effectively utilizes the bidirectional interaction between results of slot filling and intent detection, mitigating the error propagation problem.
FedCL: Federated Multi-Phase Curriculum Learning to Synchronously Correlate User Heterogeneity
However, a significant challenge in FL is handling the heterogeneity of local data distribution, which often results in a drifted global model that is difficult to converge.
Capture Salient Historical Information: A Fast and Accurate Non-Autoregressive Model for Multi-turn Spoken Language Understanding
SHA captures salient historical information for the current dialogue from both historical utterances and results via a well-designed history-attention mechanism.
Mixed Strategies for Security Games with General Defending Requirements
In this work, we initiate the study of mixed strategies for the security games in which the targets can have different defending requirements.
An Effective Non-Autoregressive Model for Spoken Language Understanding
Spoken Language Understanding (SLU), a core component of the task-oriented dialogue system, expects a shorter inference latency due to the impatience of humans.
Improving the Efficiency and Robustness of Deepfakes Detection through Precise Geometric Features
Moreover, our method has shown robustness in detecting highly compressed or noise corrupted videos.
A Result based Portable Framework for Spoken Language Understanding
Spoken language understanding (SLU), which is a core component of the task-oriented dialogue system, has made substantial progress in the research of single-turn dialogue.
Regularized Attentive Capsule Network for Overlapped Relation Extraction
Distantly supervised relation extraction has been widely applied in knowledge base construction due to its less requirement of human efforts.
Generative and Discriminative Learning for Distorted Image Restoration
Due to the uncertainty in the distortion variation, restoring distorted images caused by liquify filter is a challenging task.
Active Testing: An Unbiased Evaluation Method for Distantly Supervised Relation Extraction
Distant supervision has been a widely used method for neural relation extraction for its convenience of automatically labeling datasets.
Label Smoothing and Adversarial Robustness
We find that training model with label smoothing can easily achieve striking accuracy under most gradient-based attacks.
Preserving Dynamic Attention for Long-Term Spatial-Temporal Prediction
To filter out irrelevant noises and alleviate the error propagation, DSAN dynamically extracts valuable information by applying self-attention over the noisy input and bridges each output directly to the purified inputs via implementing a switch-attention mechanism.
Interpretable Crowd Flow Prediction with Spatial-Temporal Self-Attention
Crowd flow prediction has been increasingly investigated in intelligent urban computing field as a fundamental component of urban management system.
Spatial-Temporal Self-Attention Network for Flow Prediction
Flow prediction (e. g., crowd flow, traffic flow) with features of spatial-temporal is increasingly investigated in AI research field.
Interactive Variance Attention based Online Spoiler Detection for Time-Sync Comments
In this paper, we proposed a novel Similarity-Based Network with Interactive Variance Attention (SBN-IVA) to classify comments as spoilers or not.
Improving Abstractive Document Summarization with Salient Information Modeling
Comprehensive document encoding and salient information selection are two major difficulties for generating summaries with adequate salient information.
GAN Driven Semi-distant Supervision for Relation Extraction
Distant supervision has been widely used in relation extraction tasks without hand-labeled datasets recently.
Legal Judgment Prediction via Multi-Perspective Bi-Feedback Network
To distinguish cases with similar descriptions but different penalties, we integrate word collocations features of fact descriptions into the network via an attention mechanism.
Time-sync Video Tag Extraction Using Semantic Association Graph
Finally, we gain the weight of each word by combining Semantic Weight (SW) and Inverse Document Frequency (IDF).
Herding Effect based Attention for Personalized Time-Sync Video Recommendation
Time-sync comment (TSC) is a new form of user-interaction review associated with real-time video contents, which contains a user's preferences for videos and therefore well suited as the data source for video recommendations.
Multi-labeled Relation Extraction with Attentive Capsule Network
To disclose overlapped multiple relations from a sentence still keeps challenging.
Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning
Extracting relations is critical for knowledge base completion and construction in which distant supervised methods are widely used to extract relational facts automatically with the existing knowledge bases.
Ranked #1 on
Relationship Extraction (Distant Supervised)
on New York Times Corpus
(Average Precision metric)
Chunk-based Decoder for Neural Machine Translation
The chunk-level decoder models global dependencies while the word-level decoder decides the local word order in a chunk.
