wawasan - Data Analysis
Automated Insight Discovery and Exploration in Large-Language-Model-Powered Data Analysis
A multi-agent framework that automatically extracts, associates, and organizes insights from conversational contexts to facilitate efficient insight discovery and exploration during LLM-powered data analysis.
G-Mapper: Optimizing Cover Parameter in Mapper Construction
G-Mapper optimizes cover parameter using G-means clustering for Mapper construction.
Exploratory Data Analysis on Code-mixed Misogynistic Comments
NLP techniques aid in detecting misogyny in code-mixed Hinglish comments.
Optimizing Large Language Model (LLM) Queries in Relational Workloads
The authors explore optimizing LLM inference for analytical workloads by leveraging relational queries, achieving significant latency improvements through innovative techniques.