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Found 16 papers, 4 papers with code
Geo-BERT Pre-training Model for Query Rewriting in POI Search
Finally, we train a BERT-like pre-training model with text and POIs’ graph embeddings to get an integrated representation of both geographic and semantic information, and apply it in the QR of POI search.
Spectral-wise Implicit Neural Representation for Hyperspectral Image Reconstruction
The Fourier coordinate encoder enhances the SINR's ability to emphasize high-frequency components, while the spectral scale factor module guides the SINR to adapt to the variable number of spectral channels.
Spectrum-driven Mixed-frequency Network for Hyperspectral Salient Object Detection
The Spectral Saliency approximates the region of salient objects, while the Spectral Edge captures edge information of salient objects.
Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path Prediction
However, BIO-tagging scheme relies on the correct order of model inputs, which is not guaranteed in real-world NER on scanned VrDs where text are recognized and arranged by OCR systems.
Ranked #1 on
Entity Linking
on FUNSD
Empowering recommender systems using automatically generated Knowledge Graphs and Reinforcement Learning
Personalized recommendations have a growing importance in direct marketing, which motivates research to enhance customer experiences by knowledge graph (KG) applications.
LayoutMask: Enhance Text-Layout Interaction in Multi-modal Pre-training for Document Understanding
LayoutMask can enhance the interactions between text and layout modalities in a unified model and produce adaptive and robust multi-modal representations for downstream tasks.
Ranked #1 on
Semantic entity labeling
on FUNSD
Cultural-aware Machine Learning based Analysis of COVID-19 Vaccine Hesitancy
Our findings show that Hispanic and African American are most likely impacted by cultural characteristics such as religions and ethnic affiliation, whereas the vaccine trust and approval influence the Asian communities the most.
Toward An Optimal Selection of Dialogue Strategies: A Target-Driven Approach for Intelligent Outbound Robots
With the growth of the economy and society, enterprises, especially in the FinTech industry, have increasing demands of outbound calls for customers such as debt collection, marketing, anti-fraud calls, and so on.
An Emotional Comfort Framework for Improving User Satisfaction in E-Commerce Customer Service Chatbots
E-commerce has grown substantially over the last several years, and chatbots for intelligent customer service are concurrently drawing attention.
Improving Conversational Recommendation System by Pretraining on Billions Scale of Knowledge Graph
We first construct a billion-scale conversation knowledge graph (CKG) from information about users, items and conversations, and then pretrain CKG by introducing knowledge graph embedding method and graph convolution network to encode semantic and structural information respectively. To make the CTR prediction model sensible of current state of users and the relationship between dialogues and items, we introduce user-state and dialogue-interaction representations based on pre-trained CKG and propose K-DCN. In K-DCN, we fuse the user-state representation, dialogue-interaction representation and other normal feature representations via deep cross network, which will give the rank of candidate items to be recommended. We experimentally prove that our proposal significantly outperforms baselines and show it's real application in Alime.
An Emotion-controlled Dialog Response Generation Model with Dynamic Vocabulary
In response generation task, proper sentimental expressions can obviously improve the human-like level of the responses.
MLR: A Two-stage Conversational Query Rewriting Model with Multi-task Learning
In this paper, we propose the conversational query rewriting model - MLR, which is a Multi-task model on sequence Labeling and query Rewriting.
POI Semantic Model with a Deep Convolutional Structure
An accurate similarity calculation is challenging since the mismatch between a query and a retrieval text may exist in the case of a mistyped query or an alias inquiry.
DeepConfig: Automating Data Center Network Topologies Management with Machine Learning
In recent years, many techniques have been developed to improve the performance and efficiency of data center networks.
