4 papers · 1 filter
TopoFE: topology-aware LLM-guided Automated Feature Engineering
Sha Li, Naren Ramakrishnan
Automatic feature engineering (AutoFE) for tabular learning can be naturally formulated as a program synthesis problem, where the objective is to discover predictive feature transf…
Experience as a Compass: Multi-agent RAG with Evolving Orchestration and Agent Prompts
Sha Li, Naren Ramakrishnan
Multi-agent Retrieval-Augmented Generation (RAG), wherein each agent takes on a specific role, supports hard queries that require multiple steps and sources, or complex reasoning.…
LLMs as Layout Designers: Enhanced Spatial Reasoning for Content-Aware Layout Generation
Sha Li, Stefano Petrangeli, Yu Shen +2
While Large Language Models (LLMs) have demonstrated impressive reasoning and planning abilities in textual domains and can effectively follow instructions for complex tasks, their…
Exploring LLMs for Scientific Information Extraction Using The SciEx Framework
Sha Li, Ayush Sadekar, Nathan Self +10
Large language models (LLMs) are increasingly touted as powerful tools for automating scientific information extraction. However, existing methods and tools often struggle with the…