Domain specialization as the key to make large language models disruptive: A comprehensive survey
Large language models (LLMs) have significantly advanced the field of natural language
processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of …
processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of …
Large language model for table processing: A survey
Tables, typically two-dimensional and structured to store large amounts of data, are
essential in daily activities like database queries, spreadsheet manipulations, Web table …
essential in daily activities like database queries, spreadsheet manipulations, Web table …
Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls
Text-to-SQL parsing, which aims at converting natural language instructions into executable
SQLs, has gained increasing attention in recent years. In particular, GPT-4 and Claude-2 …
SQLs, has gained increasing attention in recent years. In particular, GPT-4 and Claude-2 …
Larger language models do in-context learning differently
We study how in-context learning (ICL) in language models is affected by semantic priors
versus input-label mappings. We investigate two setups-ICL with flipped labels and ICL with …
versus input-label mappings. We investigate two setups-ICL with flipped labels and ICL with …
Agentbench: Evaluating llms as agents
Large Language Models (LLMs) are becoming increasingly smart and autonomous,
targeting real-world pragmatic missions beyond traditional NLP tasks. As a result, there has …
targeting real-world pragmatic missions beyond traditional NLP tasks. As a result, there has …
Text-to-sql empowered by large language models: A benchmark evaluation
Large language models (LLMs) have emerged as a new paradigm for Text-to-SQL task.
However, the absence of a systematical benchmark inhibits the development of designing …
However, the absence of a systematical benchmark inhibits the development of designing …
Dspy: Compiling declarative language model calls into self-improving pipelines
O Khattab, A Singhvi, P Maheshwari, Z Zhang… - arXiv preprint arXiv …, 2023 - arxiv.org
The ML community is rapidly exploring techniques for prompting language models (LMs)
and for stacking them into pipelines that solve complex tasks. Unfortunately, existing LM …
and for stacking them into pipelines that solve complex tasks. Unfortunately, existing LM …
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)
Text-to-SQL, the process of translating natural language into Structured Query Language
(SQL), represents a transformative application of large language models (LLMs), potentially …
(SQL), represents a transformative application of large language models (LLMs), potentially …
C3: Zero-shot text-to-sql with chatgpt
This paper proposes a ChatGPT-based zero-shot Text-to-SQL method, dubbed C3, which
achieves 82.3\% in terms of execution accuracy on the holdout test set of Spider and …
achieves 82.3\% in terms of execution accuracy on the holdout test set of Spider and …
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 …