Text2sql is not enough: Unifying ai and databases with tag
AI systems that serve natural language questions over databases promise to unlock
tremendous value. Such systems would allow users to leverage the powerful reasoning and …
tremendous value. Such systems would allow users to leverage the powerful reasoning and …
Databases Unbound: Querying All of the World's Bytes with AI
Over the past five decades, the relational database model has proven to be a scaleable and
adaptable model for querying a variety of structured data, with use cases in analytics …
adaptable model for querying a variety of structured data, with use cases in analytics …
DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing
Analyzing unstructured data, such as complex documents, has been a persistent challenge
in data processing. Large Language Models (LLMs) have shown promise in this regard …
in data processing. Large Language Models (LLMs) have shown promise in this regard …
Knowledge-Aware Query Expansion with Large Language Models for Textual and Relational Retrieval
Large language models (LLMs) have been used to generate query expansions augmenting
original queries for improving information search. Recent studies also explore providing …
original queries for improving information search. Recent studies also explore providing …
The Design of an LLM-powered Unstructured Analytics System
E Anderson, J Fritz, A Lee, B Li, M Lindblad… - arXiv preprint arXiv …, 2024 - arxiv.org
LLMs demonstrate an uncanny ability to process unstructured data, and as such, have the
potential to go beyond search and run complex, semantic analyses at scale. We describe …
potential to go beyond search and run complex, semantic analyses at scale. We describe …
Variable Extraction for Model Recovery in Scientific Literature
The global output of academic publications exceeds 5 million articles per year, making it
difficult for humans to keep up with even a tiny fraction of scientific output. We need methods …
difficult for humans to keep up with even a tiny fraction of scientific output. We need methods …
Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches
A Mumuni, F Mumuni - arXiv preprint arXiv:2501.03151, 2025 - arxiv.org
Generative artificial intelligence (AI) systems based on large-scale pretrained foundation
models (PFMs) such as vision-language models, large language models (LLMs), diffusion …
models (PFMs) such as vision-language models, large language models (LLMs), diffusion …
Code-Survey: An LLM-Driven Methodology for Analyzing Large-Scale Codebases
Modern software systems like the Linux kernel are among the world's largest and most
intricate codebases, continually evolving with new features and increasing complexity …
intricate codebases, continually evolving with new features and increasing complexity …
TQA-Bench: Evaluating LLMs for Multi-Table Question Answering with Scalable Context and Symbolic Extension
Z Qiu, Y Peng, G He, B Yuan, C Wang - arXiv preprint arXiv:2411.19504, 2024 - arxiv.org
The advent of large language models (LLMs) has unlocked great opportunities in complex
data management tasks, particularly in question answering (QA) over complicated multi …
data management tasks, particularly in question answering (QA) over complicated multi …
CHASE: A Native Relational Database for Hybrid Queries on Structured and Unstructured Data
R Ma, K Zhang, Z He, Y Jing, XS Wang… - arXiv preprint arXiv …, 2025 - arxiv.org
Querying both structured and unstructured data has become a new paradigm in data
analytics and recommendation. With unstructured data, such as text and videos, are …
analytics and recommendation. With unstructured data, such as text and videos, are …