2 citations · 2 across the 2 of their papers we have counts for
4 papers
ReToolSQL: Agentic Reinforcement Learning for Robust Text-to-SQL
Pratik Kakkar, Chandra Dhir, Ravi Shankar +2
Recent work has shown that reinforcement learning from execution feedback can substantially improve text-to-SQL performance, often enabling smaller models to match or exceed much l…
AgentNLQ: A General-Purpose Agent for Natural Language to SQL
Olena Bogdanov, Yeunji Jung, Chandra Dhir +5
Natural language to SQL (NL2SQL) conversion is an important problem for researchers and enterprises due to the ubiquitous importance of relational databases in broad-ranging practi…
Knowledge Distillation Using Frontier Open-source LLMs: Generalizability and the Role of Synthetic Data
Anup Shirgaonkar, Nikhil Pandey, Nazmiye Ceren Abay +2
Leading open-source large language models (LLMs) such as Llama-3.1-Instruct-405B are extremely capable at generating text, answering questions, and solving a variety of natural lan…
A Study of Optimizations for Fine-tuning Large Language Models
Arjun Singh, Nikhil Pandey, Anup Shirgaonkar +2
Fine-tuning large language models is a popular choice among users trying to adapt them for specific applications. However, fine-tuning these models is a demanding task because the…