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Found 14 papers, 7 papers with code
Order-Disorder: Imitation Adversarial Attacks for Black-box Neural Ranking Models
In this study, we propose an imitation adversarial attack on black-box neural passage ranking models.
Collaborative Intelligence Orchestration: Inconsistency-Based Fusion of Semi-Supervised Learning and Active Learning
Motivated by the industry practice of labeling data, we propose an innovative Inconsistency-based virtual aDvErsarial Active Learning (IDEAL) algorithm to further investigate SSL-AL's potential superiority and achieve mutual enhancement of AL and SSL, i. e., SSL propagates label information to unlabeled samples and provides smoothed embeddings for AL, while AL excludes samples with inconsistent predictions and considerable uncertainty for SSL.
A Role-Selected Sharing Network for Joint Machine-Human Chatting Handoff and Service Satisfaction Analysis
Chatbot is increasingly thriving in different domains, however, because of unexpected discourse complexity and training data sparseness, its potential distrust hatches vital apprehension.
Adjacency List Oriented Relational Fact Extraction via Adaptive Multi-task Learning
Relational fact extraction aims to extract semantic triplets from unstructured text.
Ranked #4 on
Relation Extraction
on NYT
Semi-Supervised Active Learning for Semi-Supervised Models: Exploit Adversarial Examples With Graph-Based Virtual Labels
Although current mainstream methods begin to combine SSL and AL (SSL-AL) to excavate the diverse expressions of unlabeled samples, these methods' fully supervised task models are still trained only with labeled data.
Topic-Oriented Spoken Dialogue Summarization for Customer Service with Saliency-Aware Topic Modeling
In a customer service system, dialogue summarization can boost service efficiency by automatically creating summaries for long spoken dialogues in which customers and agents try to address issues about specific topics.
Unsupervised Summarization for Chat Logs with Topic-Oriented Ranking and Context-Aware Auto-Encoders
Automatic chat summarization can help people quickly grasp important information from numerous chat messages.
Time to Transfer: Predicting and Evaluating Machine-Human Chatting Handoff
Is chatbot able to completely replace the human agent?
Multi-Turn Dialogue Generation in E-Commerce Platform with the Context of Historical Dialogue
As an important research topic, customer service dialogue generation tends to generate generic seller responses by leveraging current dialogue information.
Camouflaged Chinese Spam Content Detection with Semi-supervised Generative Active Learning
We propose a Semi-supervIsed GeNerative Active Learning (SIGNAL) model to address the imbalance, efficiency, and text camouflage problems of Chinese text spam detection task.
Read Beyond the Lines: Understanding the Implied Textual Meaning via a Skim and Intensive Reading Model
The nonliteral interpretation of a text is hard to be understood by machine models due to its high context-sensitivity and heavy usage of figurative language.
Detect Camouflaged Spam Content via StoneSkipping: Graph and Text Joint Embedding for Chinese Character Variation Representation
The VFGE can learn both the graph embeddings of the Chinese characters (local) and the latent variation families (global).
Ranked #1 on
Chinese Spam Detection
on SMS
Sentiment Classification towards Question-Answering with Hierarchical Matching Network
On the basis, we propose a three-stage hierarchical matching network to explore deep sentiment information in a QA text pair.
Aspect Sentiment Classification with both Word-level and Clause-level AttentionNetworks
Aspect sentiment classification, a challenging taskin sentiment analysis, has been attracting more andmore attention in recent years.
