5 papers
MoFlow: Multi-Objective Agentic Workflow Generation
Yining Lu, Aurelie Lozano, Xi Yang +3
We study the generation of agentic workflows that jointly optimize multiple objectives, such as accuracy, cost, latency, robustness, and consistency. Existing methods for workflow…
Uncovering Cross-Objective Interference in Multi-Objective Alignment
Yining Lu, Meng Jiang
We study a persistent failure mode in multi-objective alignment for large language models (LLMs), in which scalarized training improves only some objectives while the others degrad…
A Decentralized Retrieval Augmented Generation System with Source Reliabilities Secured on Blockchain
Yining Lu, Wenyi Tang, Max Johnson +2
Existing retrieval-augmented generation (RAG) systems typically use a centralized architecture, causing a high cost of data collection, integration, and management, as well as priv…
CreativityPrism: A Cross-Domain Evaluation Framework for Large Language Model Creativity
Zhaoyi Joey Hou, Bowei Alvin Zhang, Yining Lu +9
Creativity is often seen as a hallmark of human intelligence. While large language models(LLMs) are increasingly perceived as generating creative text, there is still no cross-doma…
Learning to Optimize Multi-Objective Alignment Through Dynamic Reward Weighting
Yining Lu, Zilong Wang, Shiyang Li +6
Prior work in multi-objective reinforcement learning typically uses linear reward scalarization with fixed weights, which provably fails to capture non-convex Pareto fronts and thu…