# Listener Model for the PhotoBook Referential Game with CLIPScores as Implicit Reference Chain Source: [Listener Model for the PhotoBook Referential Game with CLIPScores as Implicit Reference Chain]() Collection index: [llms.txt]() Data updated: 2026-01-04T04:34:33.837Z Authors: Shih-Lun Wu, Yi-Hui Chou, Liangze Li Published: 2023-06-16T03:41:14.000Z ## Abstract PhotoBook is a collaborative dialogue game where two players receive private, partially-overlapping sets of images and resolve which images they have in common. It presents machines with a great challenge to learn how people build common ground around multimodal context to communicate effectively. Methods developed in the literature, however, cannot be deployed to real gameplay since they only tackle some subtasks of the game, and they require additional reference chains inputs, whose extraction process is imperfect. Therefore, we propose a reference chain-free listener model that directly addresses the game's predictive task, i.e., deciding whether an image is shared with partner. Our DeBERTa-based listener model reads the full dialogue, and utilizes CLIPScore features to assess utterance-image relevance. We achieve \>77% accuracy on unseen sets of images/game themes, outperforming baseline by \>17 points. ## 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: 84.8. - [Listener Task on PhotoBook (test)](): Listener Task; PhotoBook (test); Accuracy: 77.3. ## Original sources and implementation [Original paper]() [PDF]() [Implementation]()