Search Results for author:
Found 4 papers, 2 papers with code
On Evaluating the Integration of Reasoning and Action in LLM Agents with Database Question Answering
A key discovery is the identification of two primary bottlenecks hindering effective interaction: the capacity for planning and the ability to generate multiple SQL queries.
QTSumm: Query-Focused Summarization over Tabular Data
Motivated by this, we define a new query-focused table summarization task, where text generation models have to perform human-like reasoning and analysis over the given table to generate a tailored summary.
Enhancing Few-shot Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies
In-context learning (ICL) has emerged as a new approach to various natural language processing tasks, utilizing large language models (LLMs) to make predictions based on context that has been supplemented with a few examples or task-specific instructions.
R2D2: Robust Data-to-Text with Replacement Detection
Unfaithful text generation is a common problem for text generation systems.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
