# Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts Source: [Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts]() Collection index: [llms.txt]() Data updated: 2025-10-25T22:44:52.991Z Authors: Ece Takmaz, Mario Giulianelli, Sandro Pezzelle, Arabella Sinclair, Raquel Fern\\'andez Published: 2020-11-09T16:53:54.000Z ## Abstract Dialogue participants often refer to entities or situations repeatedly within a conversation, which contributes to its cohesiveness. Subsequent references exploit the common ground accumulated by the interlocutors and hence have several interesting properties, namely, they tend to be shorter and reuse expressions that were effective in previous mentions. In this paper, we tackle the generation of first and subsequent references in visually grounded dialogue. We propose a generation model that produces referring utterances grounded in both the visual and the conversational context. To assess the referring effectiveness of its output, we also implement a reference resolution system. Our experiments and analyses show that the model produces better, more effective referring utterances than a model not grounded in the dialogue context, and generates subsequent references that exhibit linguistic patterns akin to humans. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Listener Task on PhotoBook (val)](): Listener Task; PhotoBook (val); Accuracy: 65. - [Listener Task on PhotoBook (test)](): Listener Task; PhotoBook (test); Accuracy: 59.7. ## Original sources and implementation [Original paper]() [PDF]()