5 papers
Terminal Agents Suffice for Enterprise Automation
Patrice Bechard, Orlando Marquez Ayala, Emily Chen +5
There has been growing interest in building agents that can interact with digital platforms to execute meaningful enterprise tasks autonomously. Among the approaches explored are t…
JEF-Hinter: Leveraging Offline Knowledge for Improving Web Agents Adaptation
Hadi Nekoei, Aman Jaiswal, Patrice Bechard +7
Large language model (LLM) agents perform well in sequential decision-making tasks, but improving them on unfamiliar domains often requires costly online interactions or fine-tunin…
Multi-task retriever fine-tuning for domain-specific and efficient RAG
Patrice Béchard, Orlando Marquez Ayala
Retrieval-Augmented Generation (RAG) has become ubiquitous when deploying Large Language Models (LLMs), as it can address typical limitations such as generating hallucinated or out…
Generating a Low-code Complete Workflow via Task Decomposition and RAG
Orlando Marquez Ayala, Patrice Béchard
AI technologies are moving rapidly from research to production. With the popularity of Foundation Models (FMs) that generate text, images, and video, AI-based systems are increasin…
Reducing hallucination in structured outputs via Retrieval-Augmented Generation
Patrice Béchard, Orlando Marquez Ayala
A common and fundamental limitation of Generative AI (GenAI) is its propensity to hallucinate. While large language models (LLM) have taken the world by storm, without eliminating…