Reranker model

What is Reranker?

Reranker is a type of model or system used forranking tasksthat is typically used in information retrieval, recommender systems, or natural language processing (NLP). Its primary purpose is to reorder a set of candidate results to return the most relevant or suitable options.

How a Reranker works

Typically, when a search engine or recommender system returns a series of candidate items (such as search results, recommended products, or articles), they have already been ordered according to some initial ranking criteria. These initial rankings may be based on simple matching or basic relevance metrics. However, such rankings do not fully consider all details or deeper semantic relationships and may produce results that do not completely meet the user's needs.

For example, suppose you search online for “best pizza places”; the search engine will return many results based on basic criteria like restaurant name, rating, address, etc. These results may already be ordered by keywords or simple matching, but they may not perfectly match what you want.

At this point, the Reranker will further help you “optimize the ranking” by checking these results with more details. It may consider your past search habits, other people's reviews of the restaurant, or the restaurant's current status, and then rearrange the results to pick out the most relevant restaurants so you can more quickly find the best choice. In this example, the Reranker's workflow is as follows:

1

Initial ranking: use a simple ranking model (such as keyword matching, TF-IDF, or other features) to perform an initial ordering of candidate items

Search: “best pizza places,” the search engine returns a list of restaurants

2

Candidate refinement: refine the ranking based on additional features (such as contextual understanding, semantic associations, user behavior, etc.) and rescore the candidates

Take a closer look at these restaurants, considering whether any are in areas you frequent, whether other users gave high ratings, or whether the restaurant offers promotions, etc.

3

Final ranking: return the most relevant or suitable results based on their scores

The Reranker will place the restaurants that best meet your needs at the top, making it easier for you to find the most suitable choice

Reranker models provided by MaiAgent

Features of Cohere Rerank v3.5

Cohere Rerank v3.5 is a reranking model offered by Cohere, specifically designed to optimize the ordering of search results or candidate answers. It can perform fine-grained ranking among candidates and select the most relevant results based on deeper semantic understanding and context, thereby improving the final quality.