Zhiyu Zoey Chen

Do Retrieval-Augmented Language Models Adapt to Varying User Needs?

2025 · arXiv (Cornell University)

Recent advancements in Retrieval-Augmented Language Models (RALMs) have demonstrated their efficacy in knowledge-intensive tasks. However, existing evaluation benchmarks often assume a single optimal approach to leveraging retrieved information, failing to account for varying user needs. …