A Survey of NL2SQL with Large Language Models: Where are we, and where are we going?
Translating users' natural language queries (NL) into SQL queries (ie, NL2SQL) can
significantly reduce barriers to accessing relational databases and support various …
significantly reduce barriers to accessing relational databases and support various …
A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability
This paper presents the first comprehensive analysis of ChatGPT's Text-to-SQL ability. Given
the recent emergence of large-scale conversational language model ChatGPT and its …
the recent emergence of large-scale conversational language model ChatGPT and its …
A survey on employing large language models for text-to-sql tasks
L Shi, Z Tang, N Zhang, X Zhang, Z Yang - arxiv preprint arxiv …, 2024 - arxiv.org
The increasing volume of data in relational databases and the expertise needed for writing
SQL queries pose challenges for users to access and analyze data. Text-to-SQL (Text2SQL) …
SQL queries pose challenges for users to access and analyze data. Text-to-SQL (Text2SQL) …
AMR-based network for aspect-based sentiment analysis
Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment classification task.
Many recent works have used dependency trees to extract the relation between aspects and …
Many recent works have used dependency trees to extract the relation between aspects and …
Preventing and detecting misinformation generated by large language models
As large language models (LLMs) become increasingly capable and widely deployed, the
risk of them generating misinformation poses a critical challenge. Misinformation from LLMs …
risk of them generating misinformation poses a critical challenge. Misinformation from LLMs …
WSFE: wasserstein sub-graph feature encoder for effective user segmentation in collaborative filtering
Maximizing the user-item engagement based on vectorized embeddings is a standard
procedure of recent recommender models. Despite the superior performance for item …
procedure of recent recommender models. Despite the superior performance for item …
GDA: Generative data augmentation techniques for relation extraction tasks
Relation extraction (RE) tasks show promising performance in extracting relations from two
entities mentioned in sentences, given sufficient annotations available during training. Such …
entities mentioned in sentences, given sufficient annotations available during training. Such …
Prompt me up: Unleashing the power of alignments for multimodal entity and relation extraction
How can we better extract entities and relations from text? Using multimodal extraction with
images and text obtains more signals for entities and relations, and aligns them through …
images and text obtains more signals for entities and relations, and aligns them through …
Read it twice: Towards faithfully interpretable fact verification by revisiting evidence
Real-world fact verification task aims to verify the factuality of a claim by retrieving evidence
from the source document. The quality of the retrieved evidence plays an important role in …
from the source document. The quality of the retrieved evidence plays an important role in …
Multimodal relation extraction with cross-modal retrieval and synthesis
Multimodal relation extraction (MRE) is the task of identifying the semantic relationships
between two entities based on the context of the sentence image pair. Existing retrieval …
between two entities based on the context of the sentence image pair. Existing retrieval …