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Found 9 papers, 2 papers with code
Counter-Contrastive Learning for Language GANs
Generative Adversarial Networks (GANs) have achieved great success in image synthesis, but have proven to be difficult to generate natural language.
COIN: Conversational Interactive Networks for Emotion Recognition in Conversation
Emotion recognition in conversation has received considerable attention recently because of its practical industrial applications.
Ranked #35 on
Emotion Recognition in Conversation
on IEMOCAP
Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations
Spreadsheets are widely recognized as the most popular end-user programming tools, which blend the power of formula-based computation, with an intuitive table-based interface.
NL2Formula: Generating Spreadsheet Formulas from Natural Language Queries
Writing formulas on spreadsheets, such as Microsoft Excel and Google Sheets, is a widespread practice among users performing data analysis.
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Language models, such as GPT-3. 5 and ChatGPT, demonstrate remarkable abilities to follow diverse human instructions and perform a wide range of tasks.
Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines
Data pipelines are widely employed in modern enterprises to power a variety of Machine-Learning (ML) and Business-Intelligence (BI) applications.
OneLabeler: A Flexible System for Building Data Labeling Tools
In this paper, we propose a conceptual framework for data labeling and OneLabeler based on the conceptual framework to support easy building of labeling tools for diverse usage scenarios.
Neural Text Classification by Jointly Learning to Cluster and Align
Distributional text clustering delivers semantically informative representations and captures the relevance between each word and semantic clustering centroids.
Cluster-Gated Convolutional Neural Network for Short Text Classification
Text classification plays a crucial role for understanding natural language in a wide range of applications.
