112 citations · 313 across the 18 of their papers we have counts for
4 papers · 1 filter
Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environments
Yu Gu, Xiang Deng, Yu Su
A key missing capacity of current language models (LMs) is grounding to real-world environments. Most existing work for grounded language understanding uses LMs to directly generat…
Knowledge Base Question Answering: A Semantic Parsing Perspective
Yu Gu, Vardaan Pahuja, Gong Cheng +1
Recent advances in deep learning have greatly propelled the research on semantic parsing. Improvement has since been made in many downstream tasks, including natural language inter…
Clues Before Answers: Generation-Enhanced Multiple-Choice QA
Zixian Huang, Ao Wu, Jiaying Zhou +3
A trending paradigm for multiple-choice question answering (MCQA) is using a text-to-text framework. By unifying data in different tasks into a single text-to-text format, it train…
ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question Answering
Yu Gu, Yu Su
Question answering on knowledge bases (KBQA) poses a unique challenge for semantic parsing research due to two intertwined challenges: large search space and ambiguities in schema…