BIRCO: A Benchmark of Information Retrieval Tasks with Complex Objectives

Xiaoyue Wang, Jianyou Wang, Weili Cao, Kaicheng Wang, Ramamohan Paturi +1 more
2/21/2024
cs.IRcs.AIcs.CL

No official code found. Best implementation: BIRCO-benchmark/BIRCO_dataset (6 stars, last commit 2024-06-05).

Abstract

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.

View on arXivView PDF

Code Implementations(1)

60Shell, PythonMay 30, 20242 years agoNOASSERTION

Similar Papers

Cite this paper

@article{wang2024birco,
  title  = {BIRCO: A Benchmark of Information Retrieval Tasks with Complex Objectives},
  author = {Xiaoyue Wang and Jianyou Wang and Weili Cao and Kaicheng Wang and Ramamohan Paturi and Leon Bergen},
  year   = {2024},
  eprint = {2402.14151},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2402.14151v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2402.14151.svg)](https://codeofpaper.com/paper/2402.14151)

Discussion