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Found 6 papers, 1 papers with code
Addressing Limitations of Encoder-Decoder Based Approach to Text-to-SQL
Most attempts on Text-to-SQL task using encoder-decoder approach show a big problem of dramatic decline in performance for new databases.
Domain Adaptation of a State of the Art Text-to-SQL Model: Lessons Learned and Challenges Found
There are many recent advanced developments for the Text-to-SQL task, where the Picard model is one of the the top performing models as measured by the Spider dataset competition.
Recognizing and Splitting Conditional Sentences for Automation of Business Processes Management
Business Process Management (BPM) is the discipline which is responsible for management of discovering, analyzing, redesigning, monitoring, and controlling business processes.
Identifying Motion Entities in Natural Language and A Case Study for Named Entity Recognition
Motion recognition is one of the basic cognitive capabilities of many life forms, however, detecting and understanding motion in text is not a trivial task.
LiMiT: The Literal Motion in Text Dataset
Motion recognition is one of the basic cognitive capabilities of many life forms, yet identifying motion of physical entities in natural language have not been explored extensively and empirically.
SECRET: Semantically Enhanced Classification of Real-world Tasks
SECRET performs classifications by fusing the semantic information of the labels with the available data: it combines the feature space of the supervised algorithms with the semantic space of the NLP algorithms and predicts labels based on this joint space.
