17 citations · 75 across the 25 of their papers we have counts for
20 papers · 1 filter
AirQA: A Comprehensive QA Dataset for AI Research with Instance-Level Evaluation
Tiancheng Huang, Ruisheng Cao, Yuxin Zhang +8
The growing volume of academic papers has made it increasingly difficult for researchers to efficiently extract key information. While large language models (LLMs) based agents are…
NeuSym-RAG: Hybrid Neural Symbolic Retrieval with Multiview Structuring for PDF Question Answering
Ruisheng Cao, Hanchong Zhang, Tiancheng Huang +8
The increasing number of academic papers poses significant challenges for researchers to efficiently acquire key details. While retrieval augmented generation (RAG) shows great pro…
Reducing Tool Hallucination via Reliability Alignment
Hongshen Xu, Zichen Zhu, Lei Pan +6
Large Language Models (LLMs) have expanded their capabilities beyond language generation to interact with external tools, enabling automation and real-world applications. However,…
Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows
Fangyu Lei, Jixuan Chen, Yuxiao Ye +13
Real-world enterprise text-to-SQL workflows often involve complex cloud or local data across various database systems, multiple SQL queries in various dialects, and diverse operati…
CoE-SQL: In-Context Learning for Multi-Turn Text-to-SQL with Chain-of-Editions
Hanchong Zhang, Ruisheng Cao, Hongshen Xu +2
Recently, Large Language Models (LLMs) have been demonstrated to possess impressive capabilities in a variety of domains and tasks. We investigate the issue of prompt design in the…
Hierarchical Multimodal Pre-training for Visually Rich Webpage Understanding
Hongshen Xu, Lu Chen, Zihan Zhao +4
The growing prevalence of visually rich documents, such as webpages and scanned/digital-born documents (images, PDFs, etc.), has led to increased interest in automatic document und…
A BiRGAT Model for Multi-intent Spoken Language Understanding with Hierarchical Semantic Frames
Hongshen Xu, Ruisheng Cao, Su Zhu +4
Previous work on spoken language understanding (SLU) mainly focuses on single-intent settings, where each input utterance merely contains one user intent. This configuration signif…
ASTormer: An AST Structure-aware Transformer Decoder for Text-to-SQL
Ruisheng Cao, Hanchong Zhang, Hongshen Xu +4
Text-to-SQL aims to generate an executable SQL program given the user utterance and the corresponding database schema. To ensure the well-formedness of output SQLs, one prominent a…
ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thought
Hanchong Zhang, Ruisheng Cao, Lu Chen +2
Recently Large Language Models (LLMs) have been proven to have strong abilities in various domains and tasks. We study the problem of prompt designing in the text-to-SQL task and a…
CSS: A Large-scale Cross-schema Chinese Text-to-SQL Medical Dataset
Hanchong Zhang, Jieyu Li, Lu Chen +5
The cross-domain text-to-SQL task aims to build a system that can parse user questions into SQL on complete unseen databases, and the single-domain text-to-SQL task evaluates the p…
TIE: Topological Information Enhanced Structural Reading Comprehension on Web Pages
Zihan Zhao, Lu Chen, Ruisheng Cao +3
Recently, the structural reading comprehension (SRC) task on web pages has attracted increasing research interests. Although previous SRC work has leveraged extra information such…
Few-Shot NLU with Vector Projection Distance and Abstract Triangular CRF
Su Zhu, Lu Chen, Ruisheng Cao +3
Data sparsity problem is a key challenge of Natural Language Understanding (NLU), especially for a new target domain. By training an NLU model in source domains and applying the mo…
LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations
Ruisheng Cao, Lu Chen, Zhi Chen +3
This work aims to tackle the challenging heterogeneous graph encoding problem in the text-to-SQL task. Previous methods are typically node-centric and merely utilize different weig…
Decoupled Dialogue Modeling and Semantic Parsing for Multi-Turn Text-to-SQL
Zhi Chen, Lu Chen, Hanqi Li +4
Recently, Text-to-SQL for multi-turn dialogue has attracted great interest. Here, the user input of the current turn is parsed into the corresponding SQL query of the appropriate d…
ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parser
Zhi Chen, Lu Chen, Yanbin Zhao +4
Given a database schema, Text-to-SQL aims to translate a natural language question into the corresponding SQL query. Under the setup of cross-domain, traditional semantic parsing m…
Vector Projection Network for Few-shot Slot Tagging in Natural Language Understanding
Su Zhu, Ruisheng Cao, Lu Chen +1
Few-shot slot tagging becomes appealing for rapid domain transfer and adaptation, motivated by the tremendous development of conversational dialogue systems. In this paper, we prop…
Unsupervised Dual Paraphrasing for Two-stage Semantic Parsing
Ruisheng Cao, Su Zhu, Chenyu Yang +5
One daunting problem for semantic parsing is the scarcity of annotation. Aiming to reduce nontrivial human labor, we propose a two-stage semantic parsing framework, where the first…
Jointly Encoding Word Confusion Network and Dialogue Context with BERT for Spoken Language Understanding
Chen Liu, Su Zhu, Zijian Zhao +3
Spoken Language Understanding (SLU) converts hypotheses from automatic speech recognizer (ASR) into structured semantic representations. ASR recognition errors can severely degener…
Dual Learning for Semi-Supervised Natural Language Understanding
Su Zhu, Ruisheng Cao, Kai Yu
Natural language understanding (NLU) converts sentences into structured semantic forms. The paucity of annotated training samples is still a fundamental challenge of NLU. To solve…
Semantic Parsing with Dual Learning
Ruisheng Cao, Su Zhu, Chen Liu +2
Semantic parsing converts natural language queries into structured logical forms. The paucity of annotated training samples is a fundamental challenge in this field. In this work,…