5 papers
Trajectory-Informed Memory Generation for Self-Improving Agent Systems
Gaodan Fang, Vatche Isahagian, K. R. Jayaram +4
LLM-powered agents face a persistent challenge: learning from their execution experiences to improve future performance. While agents can successfully complete many tasks, they oft…
VOILA: Value-of-Information Guided Fidelity Selection for Cost-Aware Multimodal Question Answering
Rahul Atul Bhope, K. R. Jayaram, Vinod Muthusamy +3
Despite significant costs from retrieving and processing high-fidelity visual inputs, most multimodal vision-language systems operate at fixed fidelity levels. We introduce VOILA,…
On Automating Security Policies with Contemporary LLMs
Pablo Fernández Saura, K. R. Jayaram, Vatche Isahagian +2
The complexity of modern computing environments and the growing sophistication of cyber threats necessitate a more robust, adaptive, and automated approach to security enforcement.…
FLOW-BENCH: Towards Conversational Generation of Enterprise Workflows
Evelyn Duesterwald, Siyu Huo, Vatche Isahagian +7
Business process automation (BPA) that leverages Large Language Models (LLMs) to convert natural language (NL) instructions into structured business process artifacts is becoming a…
OptiSeq: Ordering Examples On-The-Fly for In-Context Learning
Rahul Atul Bhope, Praveen Venkateswaran, K. R. Jayaram +3
Developers using LLMs and LLM-based agents in their applications have provided plenty of anecdotal evidence that in-context-learning (ICL) is fragile. In this paper, we show that i…