Is ChatGPT Good at Search? LLMs as Re-Ranking Agent [EMNLP 2023 Outstanding Paper Award]
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论文“ChatGPT 是否擅长搜索?研究大语言模型作为重排序代理的作用”的官方代码实现。
本项目旨在探索 ChatGPT 和 GPT-4 等生成式 LLM 在信息检索(IR)领域的相关性排序能力。
以下定义了一个查询(Query)和三个候选段落:
item = {
'query': 'How much impact do masks have on preventing the spread of the COVID-19?',
'hits': [
{'content': 'Title: Universal Masking is Urgent in the COVID-19 Pandemic: SEIR and Agent Based Models, Empirical Validation, Policy Recommendations Content: We present two models for the COVID-19 pandemic predicting the impact of universal face mask wearing upon the spread of the SARS-CoV-2 virus--one employing a stochastic dynamic network based compartmental SEIR (susceptible-exposed-infectious-recovered) approach, and the other employing individual ABM (agent-based modelling) Monte Carlo simulation--indicating (1) significant impact under (near) universal masking when at least 80% of a population is wearing masks, versus minimal impact when only 50% or less of the population is wearing masks, and (2) significant impact when universal masking is adopted early, by Day 50 of a regional outbreak, versus minimal impact when universal masking is adopted late. These effects hold even at the lower filtering rates of homemade masks. To validate these theoretical models, we compare their predictions against a new empirical data set we have collected'},
{'content': 'Title: Masking the general population might attenuate COVID-19 outbreaks Content: The effect of masking the general population on a COVID-19 epidemic is estimated by computer simulation using two separate state-of-the-art web-based softwares, one of them calibrated for the SARS-CoV-2 virus. The questions addressed are these: 1. Can mask use by the general population limit the spread of SARS-CoV-2 in a country? 2. What types of masks exist, and how elaborate must a mask be to be effective against COVID-19? 3. Does the mask have to be applied early in an epidemic? 4. A brief general discussion of masks and some possible future research questions regarding masks and SARS-CoV-2. Results are as follows: (1) The results indicate that any type of mask, even simple home-made ones, may be effective. Masks use seems to have an effect in lowering new patients even the protective effect of each mask (here dubbed"one-mask protection") is'},
{'content': 'Title: To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic Content: Face mask use by the general public for limiting the spread of the COVID-19 pandemic is controversial, though increasingly recommended, and the potential of this intervention is not well understood. We develop a compartmental model for assessing the community-wide impact of mask use by the general, asymptomatic public, a portion of which may be asymptomatically infectious. Model simulations, using data relevant to COVID-19 dynamics in the US states of New York and Washington, suggest that broad adoption of even relatively ineffective face masks may meaningfully reduce community transmission of COVID-19 and decrease peak hospitalizations and deaths. Moreover, mask use decreases the effective transmission rate in nearly linear proportion to the product of mask effectiveness (as a fraction of potentially infectious contacts blocked) and coverage rate (as'}
]
}
我们可以使用 ChatGPT 通过指令式排列生成(instructional permutation generation)对这些段落进行重排序。
RankGPT是一个利用大语言模型(如ChatGPT和GPT-4)进行信息检索重排序的开源框架,荣获EMNLP 2023杰出论文奖。该项目旨在探索生成式人工智能在处理相关性排序任务中的潜力,通过指令微调提升搜索结果的精准度。
支持使用多种大语言模型(包括GPT系列、Claude、Llama2等)进行搜索结果的二次排序。
提供滑动窗口排序策略,突破了模型上下文长度的限制,实现了对大量候选段落的高效重排。
引入指令蒸馏技术,能够简化复杂的排序指令,利用开源模型达到业内领先的排序性能。
集成主流基准测试工具,方便用户在TREC、BEIR和Mr. TyDi等数据集上进行快速评估和性能对比。
该项目适用于从事信息检索研究、搜索引擎优化或需要构建高精度问答系统的开发者与学术人员,特别适合在初筛结果的基础上进一步精炼搜索相关性。