English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

When re-finding items, users who forget or are uncertain about identifyingdetails often rely on creative strategies for expressing their informationneeds -- complex queries that describe content elements (e.g., book charactersor events), information beyond the document text (e.g., descriptions of bookcovers), or personal context (e.g., when they read a book). This retrievalsetting, called tip of the tongue (TOT), is especially challenging for modelsheavily reliant on lexical and semantic overlap between query and documenttext. In this work, we introduce a simple yet effective framework for handlingsuch complex queries by decomposing the query into individual clues, routingthose as sub-queries to specialized retrievers, and ensembling the results.This approach allows us to take advantage of off-the-shelf retrievers (e.g.,CLIP for retrieving images of book covers) or incorporate retriever-specificlogic (e.g., date constraints). We show that our framework incorportating querydecompositions into retrievers can improve gold book recall up to 7% relativeagain for Recall@5 on a new collection of 14,441 real-world query-book pairsfrom an online community for resolving TOT inquiries.

Decomposing Complex Queries for Tip-of-the-tongue Retrieval