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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Dialogue models are able to generate coherent and fluent responses, but theycan still be challenging to control and may produce non-engaging, unsaferesults. This unpredictability diminishes user trust and can hinder the use ofthe models in the real world. To address this, we introduce DialGuide, a novelframework for controlling dialogue model behavior using natural language rules,or guidelines. These guidelines provide information about the context they areapplicable to and what should be included in the response, allowing the modelsto generate responses that are more closely aligned with the developer'sexpectations and intent. We evaluate DialGuide on three tasks in open-domaindialogue response generation: guideline selection, response generation, andresponse entailment verification. Our dataset contains 10,737 positive and15,467 negative dialogue context-response-guideline triplets across two domains- chit-chat and safety. We provide baseline models for the tasks and benchmarktheir performance. We also demonstrate that DialGuide is effective in thedialogue safety domain, producing safe and engaging responses that followdeveloper guidelines.

DialGuide: Aligning Dialogue Model Behavior with Developer Guidelines