603 citations · 1.2k across the 70 of their papers we have counts for
10 papers · 1 filter
Generate then Select: Open-ended Visual Question Answering Guided by World Knowledge
Xingyu Fu, Sheng Zhang, Gukyeong Kwon +10
The open-ended Visual Question Answering (VQA) task requires AI models to jointly reason over visual and natural language inputs using world knowledge. Recently, pre-trained Langua…
Benchmarking Diverse-Modal Entity Linking with Generative Models
Sijia Wang, Alexander Hanbo Li, Henry Zhu +9
Entities can be expressed in diverse formats, such as texts, images, or column names and cell values in tables. While existing entity linking (EL) models work well on per modality…
UNITE: A Unified Benchmark for Text-to-SQL Evaluation
Wuwei Lan, Zhiguo Wang, Anuj Chauhan +15
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. To comprehensively e…
Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness
Shuaichen Chang, Jun Wang, Mingwen Dong +13
Neural text-to-SQL models have achieved remarkable performance in translating natural language questions into SQL queries. However, recent studies reveal that text-to-SQL models ar…
Importance of Synthesizing High-quality Data for Text-to-SQL Parsing
Yiyun Zhao, Jiarong Jiang, Yiqun Hu +14
Recently, there has been increasing interest in synthesizing data to improve downstream text-to-SQL tasks. In this paper, we first examined the existing synthesized datasets and di…
DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases
Donghan Yu, Sheng Zhang, Patrick Ng +7
Question answering over knowledge bases (KBs) aims to answer natural language questions with factual information such as entities and relations in KBs. Previous methods either gene…
Locally Aggregated Feature Attribution on Natural Language Model Understanding
Sheng Zhang, Jin Wang, Haitao Jiang +1
With the growing popularity of deep-learning models, model understanding becomes more important. Much effort has been devoted to demystify deep neural networks for better interpret…
Zero-Shot Dependency Parsing with Worst-Case Aware Automated Curriculum Learning
Miryam de Lhoneux, Sheng Zhang, Anders Søgaard
Large multilingual pretrained language models such as mBERT and XLM-RoBERTa have been found to be surprisingly effective for cross-lingual transfer of syntactic parsing models (Wu…
FairLex: A Multilingual Benchmark for Evaluating Fairness in Legal Text Processing
Ilias Chalkidis, Tommaso Pasini, Sheng Zhang +3
We present a benchmark suite of four datasets for evaluating the fairness of pre-trained language models and the techniques used to fine-tune them for downstream tasks. Our benchma…
Cross-lingual Semantic Parsing
Sheng Zhang, Kevin Duh, Benjamin Van Durme
We introduce the task of cross-lingual semantic parsing: mapping content provided in a source language into a meaning representation based on a target language. We present: (1) a m…