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Found 7 papers, 1 papers with code
Benchmarking Diverse-Modal Entity Linking with Generative Models
Entities can be expressed in diverse formats, such as texts, images, or column names and cell values in tables.
UNITE: A Unified Benchmark for Text-to-SQL Evaluation
A practical text-to-SQL system should generalize well on a wide variety of natural language questions, unseen database schemas, and novel SQL query structures.
Importance of Synthesizing High-quality Data for Text-to-SQL Parsing
In this paper, we first examined the existing synthesized datasets and discovered that state-of-the-art text-to-SQL algorithms did not further improve on popular benchmarks when trained with augmented synthetic data.
Improved Text Classification via Contrastive Adversarial Training
We propose a simple and general method to regularize the fine-tuning of Transformer-based encoders for text classification tasks.
Multilingual BERT Post-Pretraining Alignment
We propose a simple method to align multilingual contextual embeddings as a post-pretraining step for improved zero-shot cross-lingual transferability of the pretrained models.
Octa: Omissions and Conflicts in Target-Aspect Sentiment Analysis
Sentiments in opinionated text are often determined by both aspects and target words (or targets).
Empirical Study on Deep Learning Models for Question Answering
In this paper we explore deep learning models with memory component or attention mechanism for question answering task.
