1.1 相关度排序模型(Relevance Ranking Model) 相关度排序模型根据查询和文档之间的相似度来对文档进行排序。常用的模型包括:布尔模型(Boolean Model),向量空间模型(Vector Space Model),隐语义分析(Latent Semantic Analysis),BM25,LMIR模型等等。 1.2 重要性排序模型(Importance Ranking Model) 重要性排序模型不考虑查询...
using ground-truth answers provided in conversational history. It remains unclear whether we can rely on this static evaluation for model development and whether current systems
研究者在六个数据集进行实验:包括一些多类数据集和多标签数据集,结果表明在各自领域的 SOTA 基准测试中呈现出持续的改进。 MACH 架构图。 MACH 与 Parabel、Embedding Model 在 Matching 度量指标上的结果对比。 MACH 与 Parabel、Embedding Model 在 Ranking 度量指标上的结果对比。 推荐:实验结果表明,本文提出的 ...
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基于排名的:人类对语言模型输出进行排名,用于定义微调的优化目标,完全避免了强化学习。这包括 Preference Ranking Optimization (PRO; Song 等人,2023)和 Direct Preference Optimization (DPO; Rafailov 等人,2023)等方法。 基于语言:人类通过自然语言提供反馈,并通过标准监督学习利用。例如,Chain of Hindsight (CoH; Li...
Nevertheless, ranking them in a specific order is challenging due to the differences between each AI productivity tool and its intended application. Despite this challenge, we have tried to provide you with a comprehensive list of almost everything AI can help you with. Additionally, rest assured...
我们的早期用户们发现,要实现一个好用的检索需要用到很多个系统:一个用于全文检索,一个向量数据库,一个用于存储实际数据的系统,一些自定义代码进行 reranking,并且可能还需要数据的其他数据副本用于 fine-tuning,以及自定义工作流等等。 LanceDB 就是想解决这个问题,这些都是人们绝对需要做的事情,但让我们将其从五...
Moonshot AI's flagship product, Kimi, has seen a surge in popularity since its launch. In January 2024, Kimi's intelligent assistant recorded over 1.42 million visits, ranking first among AI ChatBots products in large model startups, with a month-on-month increase of 94.1%. ...
is a growing trend to employ these models in creating innovative evaluation metrics for automated assessment of generation tasks. This paper investigates a pivotal question: Do language model-driven evaluation metrics inherently exhibit bias favoring texts generated by the same underlying language model?
王哲是上一届DLP-KDD workshop Best Paper Award的获得者,获奖paperCOLD: Towards the Next Generation of Pre-Ranking System深入探讨了阿里大规模推荐系统粗排层的设计和实现,是我非常推崇的业界实践文章。所以今天我们也围绕大规模推荐系统方向提出了十个问题,来看一下业界最前沿推荐系统的实践经验。