Search Results for author:
Found 16 papers, 4 papers with code
Learn to Copy from the Copying History: Correlational Copy Network for Abstractive Summarization
It thereby takes advantage of prior copying distributions and, at each time step, explicitly encourages the model to copy the input word that is relevant to the previously copied one.
Ranked #11 on
Abstractive Text Summarization
on CNN / Daily Mail
(using extra training data)
Dynamical phases of short-term memory mechanisms in RNNs
Short-term memory is essential for cognitive processing, yet our understanding of its neural mechanisms remains unclear.
Latent computing by biological neural networks: A dynamical systems framework
These observations motivate a dynamical systems framework for neural network activity that focuses on the concept of \emph{latent processing units,} core elements for robust coding and computation embedded in collective neural dynamics.
An Integrated Sensing and Communications System Based on Affine Frequency Division Multiplexing
This paper proposes an integrated sensing and communications (ISAC) system based on affine frequency division multiplexing (AFDM) waveform.
MDS-GNN: A Mutual Dual-Stream Graph Neural Network on Graphs with Incomplete Features and Structure
Graph Neural Networks (GNNs) have emerged as powerful tools for analyzing and learning representations from graph-structured data.
Respiratory Subtraction for Pulmonary Microwave Ablation Evaluation
The experimental results confirm the effectiveness of the respiratory subtraction method and the proposed quantitative evaluation metric in assessing lung tumor treatment.
Amplify Graph Learning for Recommendation via Sparsity Completion
In this paper, we propose an Amplify Graph Learning framework based on Sparsity Completion (called AGL-SC).
AttentionShift: Iteratively Estimated Part-Based Attention Map for Pointly Supervised Instance Segmentation
Pointly supervised instance segmentation (PSIS) learns to segment objects using a single point within the object extent as supervision.
An AFDM-Based Integrated Sensing and Communications
This paper considers an affine frequency division multiplexing (AFDM)-based integrated sensing and communications (ISAC) system, where the AFDM waveform is used to simultaneously carry communications information and sense targets.
Semi-Supervised Object Detection via Multi-Instance Alignment With Global Class Prototypes
Semi-Supervised object detection (SSOD) aims to improve the generalization ability of object detectors with large-scale unlabeled images.
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce
K-PLUG achieves new state-of-the-art results on a suite of domain-specific NLP tasks, including product knowledge base completion, abstractive product summarization, and multi-turn dialogue, significantly outperforms baselines across the board, which demonstrates that the proposed method effectively learns a diverse set of domain-specific knowledge for both language understanding and generation tasks.
K-PLUG: KNOWLEDGE-INJECTED PRE-TRAINED LANGUAGE MODEL FOR NATURAL LANGUAGE UNDERSTANDING AND GENERATION
K-PLUG achieves new state-of-the-art results on a suite of domain-specific NLP tasks, including product knowledge base completion, abstractive product summarization, and multi-turn dialogue, significantly outperforms baselines across the board, which demonstrates that the proposed method effectively learns a diverse set of domain-specific knowledge for both language understanding and generation tasks.
A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data
However, it is difficult to evaluate the quality of pseudo labels since no labels are available in target domain.
On the Faithfulness for E-commerce Product Summarization
In this work, we present a model to generate e-commerce product summaries.
Self-Attention Guided Copy Mechanism for Abstractive Summarization
Copy module has been widely equipped in the recent abstractive summarization models, which facilitates the decoder to extract words from the source into the summary.
Efficient Privacy Preserving Viola-Jones Type Object Detection via Random Base Image Representation
Only the base images are submitted randomly to the cloud server.
