6 citations · 9 across the 5 of their papers we have counts for
5 papers
Continual Learning Bench: Evaluating Frontier AI Systems in Real-World Stateful Environments
Parth Asawa, Christopher M. Glaze, Gabriel Orlanski +7
Continual learning, the ability of AI systems to improve through sequential experience, has attracted substantial interest, but no high-quality benchmark exists to evaluate it. We…
Arming Data Agents with Tribal Knowledge
Shubham Agarwal, Asim Biswal, Sepanta Zeighami +3
Natural language to SQL (NL2SQL) translation enables non-expert users to query relational databases through natural language. Recently, NL2SQL agents, powered by the reasoning capa…
AgentSM: Semantic Memory for Agentic Text-to-SQL
Asim Biswal, Chuan Lei, Xiao Qin +3
Recent advances in LLM-based Text-to-SQL have achieved remarkable gains on public benchmarks such as BIRD and Spider. Yet, these systems struggle to scale in realistic enterprise s…
Text2SQL is Not Enough: Unifying AI and Databases with TAG
Asim Biswal, Liana Patel, Siddarth Jha +5
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 knowledge…
Optimizing LLM Queries in Relational Data Analytics Workloads
Shu Liu, Asim Biswal, Amog Kamsetty +8
Batch data analytics is a growing application for Large Language Models (LLMs). LLMs enable users to perform a wide range of natural language tasks, such as classification, entity…