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Found 10 papers, 5 papers with code
Enhancing Numerical Reasoning with the Guidance of Reliable Reasoning Processes
Numerical reasoning is an essential ability for NLP systems to handle numeric information.
Multi-Hop Table Retrieval for Open-Domain Text-to-SQL
To reduce the effect of the similar irrelevant entity, our method focuses on unretrieved entities at each hop and considers the low-ranked tables by beam search.
Improving Demonstration Diversity by Human-Free Fusing for Text-to-SQL
Currently, the in-context learning method based on large language models (LLMs) has become the mainstream of text-to-SQL research.
A Survey of Table Reasoning with Large Language Models
In this paper, we analyze the mainstream techniques used to improve table reasoning performance in the LLM era, and the advantages of LLMs compared to pre-LLMs for solving table reasoning.
Exploring Equation as a Better Intermediate Meaning Representation for Numerical Reasoning
So in this paper, we try to use equations as IMRs to solve the numerical reasoning task by addressing two problems: (1) Theoretically, how to prove that the equation is an IMR with higher generation accuracy than programs; (2) Empirically, how to improve the generation accuracy of equations with LLMs.
Controllable Data Augmentation for Context-Dependent Text-to-SQL
In this paper, we introduce ConDA, which generates interactive questions and corresponding SQL results.
Towards Knowledge-Intensive Text-to-SQL Semantic Parsing with Formulaic Knowledge
In this paper, we study the problem of knowledge-intensive text-to-SQL, in which domain knowledge is necessary to parse expert questions into SQL queries over domain-specific tables.
A Survey on Table-and-Text HybridQA: Concepts, Methods, Challenges and Future Directions
Table-and-text hybrid question answering (HybridQA) is a widely used and challenging NLP task commonly applied in the financial and scientific domain.
MultiSpider: Towards Benchmarking Multilingual Text-to-SQL Semantic Parsing
Text-to-SQL semantic parsing is an important NLP task, which greatly facilitates the interaction between users and the database and becomes the key component in many human-computer interaction systems.
UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQL
Existing text-to-SQL semantic parsers are typically designed for particular settings such as handling queries that span multiple tables, domains or turns which makes them ineffective when applied to different settings.
