BIRCO: A Benchmark of Information Retrieval Tasks with Complex Objectives
Wang, Xiaoyue, Wang, Jianyou, Cao, Weili, Wang, Kaicheng, Paturi, Ramamohan, Bergen, Leon
–arXiv.org Artificial Intelligence
We present the Benchmark of Information Retrieval (IR) tasks with Complex Objectives (BIRCO). BIRCO evaluates the ability of IR systems to retrieve documents given multi-faceted user objectives. The benchmark's complexity and compact size make it suitable for evaluating large language model (LLM)-based information retrieval systems. We present a modular framework for investigating factors that may influence LLM performance on retrieval tasks, and identify a simple baseline model which matches or outperforms existing approaches and more complex alternatives. No approach achieves satisfactory performance on all benchmark tasks, suggesting that stronger models and new retrieval protocols are necessary to address complex user needs.
arXiv.org Artificial Intelligence
Apr-3-2024
- Country:
- Oceania > Australia
- North America
- United States
- New York > New York County
- New York City (0.04)
- Louisiana > Orleans Parish
- New Orleans (0.04)
- California > San Diego County
- San Diego (0.04)
- New York > New York County
- Canada > Ontario
- Toronto (0.04)
- United States
- Europe
- Ireland > Leinster
- County Dublin > Dublin (0.04)
- Greece > Central Macedonia
- Thessaloniki (0.04)
- Belgium > Brussels-Capital Region
- Brussels (0.04)
- Ireland > Leinster
- Asia
- Genre:
- Research Report
- New Finding (1.00)
- Experimental Study (1.00)
- Research Report
- Industry:
- Health & Medicine (1.00)
- Technology: