{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/ducho-meets-elliot-large-scale-benchmarks-for-1","title":"Ducho meets Elliot: Large-scale Benchmarks for Multimodal Recommendation","arxiv_id":"2409.15857","date":"2024-09-24","proceeding":null,"authors":["Matteo Attimonelli","Danilo Danese","Angela Di Fazio","Daniele Malitesta","Claudio Pomo","Tommaso Di Noia"],"abstract":"In specific domains like fashion, music, and movie recommendation, the multi-faceted features characterizing products and services may influence each customer on online selling platforms differently, paving the way to novel multimodal recommendation models that can learn from such multimodal content. According to the literature, the common multimodal recommendation pipeline involves (i) extracting multimodal features, (ii) refining their high-level representations to suit the recommendation task, (iii) optionally fusing all multimodal features, and (iv) predicting the user-item score. While great effort has been put into designing optimal solutions for (ii-iv), to the best of our knowledge, very little attention has been devoted to exploring procedures for (i). In this respect, the existing literature outlines the large availability of multimodal datasets and the ever-growing number of large models accounting for multimodal-aware tasks, but (at the same time) an unjustified adoption of limited standardized solutions. This motivates us to explore more extensive techniques for the (i) stage of the pipeline. To this end, this paper settles as the first attempt to offer a large-scale benchmarking for multimodal recommender systems, with a specific focus on multimodal extractors. Specifically, we take advantage of two popular and recent frameworks for multimodal feature extraction and reproducibility in recommendation, Ducho and Elliot, to offer a unified and ready-to-use experimental environment able to run extensive benchmarking analyses leveraging novel multimodal feature extractors. Results, largely validated under different hyper-parameter settings for the chosen extractors, provide important insights on how to train and tune the next generation of multimodal recommendation algorithms.","url_abs":"https://arxiv.org/abs/2409.15857v1","url_pdf":"https://arxiv.org/pdf/2409.15857v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"ducho-meets-elliot-large-scale-benchmarks-for-1","repo_url":"https://github.com/sisinflab/Ducho-meets-Elliot","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"benchmarking","task_name":"Benchmarking"},{"task_slug":"movie-recommendation","task_name":"Movie Recommendation"},{"task_slug":"multimodal-recommendation","task_name":"Multimodal Recommendation"},{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"}],"methods":[{"method_slug":"attention","method_name":"Attention"},{"method_slug":"focus","method_name":"Focus"},{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"FREEDOM (CLIP)","rank_in_archive_order":1,"of":18,"metrics":{"Hit Ratio":"14.45","Recall":"8.95","nDCG":"4.36"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"FREEDOM (ResNet50 + Sentence Bert)","rank_in_archive_order":2,"of":18,"metrics":{"Hit Ratio":"14.28","Recall":"8.81","nDCG":"4.31"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"LATTICE (ResNet50 + Sentence Bert)","rank_in_archive_order":3,"of":18,"metrics":{"Hit Ratio":"13.69","Recall":"8.41","nDCG":"4.06"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"LATTICE (MMFashion + Sentence Bert)","rank_in_archive_order":4,"of":18,"metrics":{"Hit Ratio":"13.63","Recall":"8.38","nDCG":"4.13"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"BM3 (AltCLIP)","rank_in_archive_order":5,"of":18,"metrics":{"Hit Ratio":"13.53","Recall":"8.15","nDCG":"4.10"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"BM3 (ResNet50 + Sentence Bert)","rank_in_archive_order":6,"of":18,"metrics":{"Hit Ratio":"13.29","Recall":"8.05","nDCG":"3.91"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"NGCF-M (Align)","rank_in_archive_order":7,"of":18,"metrics":{"Hit Ratio":"12.61","Recall":"7.70","nDCG":"3.66"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"LightGCN","rank_in_archive_order":8,"of":18,"metrics":{"Hit Ratio":"12.60","Recall":"7.56","nDCG":"3.82"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"NGCF-M (ResNet50 + Sentence Bert)","rank_in_archive_order":9,"of":18,"metrics":{"Hit Ratio":"11.91","Recall":"7.18","nDCG":"3.50"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"VBPR (MMFashion + Sentence Bert)","rank_in_archive_order":10,"of":18,"metrics":{"Hit Ratio":"10.39","Recall":"6.42","nDCG":"3.12"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"VBPR (ResNet50 + Sentence Bert)","rank_in_archive_order":11,"of":18,"metrics":{"Hit Ratio":"10.18","Recall":"6.21","nDCG":"2.99"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"DGCF","rank_in_archive_order":12,"of":18,"metrics":{"Hit Ratio":"10.26","Recall":"6.08","nDCG":"3.03"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"SGL","rank_in_archive_order":13,"of":18,"metrics":{"Hit Ratio":"9.40","Recall":"5.77","nDCG":"2.93"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"BPRMF","rank_in_archive_order":14,"of":18,"metrics":{"Hit Ratio":"9.04","Recall":"5.48","nDCG":"2.67"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"GRCN (ResNet50 + Sentence Bert)","rank_in_archive_order":15,"of":18,"metrics":{"Hit Ratio":"8.81","Recall":"5.29","nDCG":"2.48"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"GRCN (Align)","rank_in_archive_order":16,"of":18,"metrics":{"Hit Ratio":"8.76","Recall":"5.21","nDCG":"2.43"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"NGCF","rank_in_archive_order":17,"of":18,"metrics":{"Hit Ratio":"8.59","Recall":"5.09","nDCG":"2.39"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-baby","task":"Multimodal Recommendation","dataset":"Amazon Baby","model":"ItemKNN","rank_in_archive_order":18,"of":18,"metrics":{"Hit Ratio":"4.21","Recall":"2.46","nDCG":"1.19"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"LATTICE (ALIGN)","rank_in_archive_order":1,"of":18,"metrics":{"Hit Ratio":"21.31","Recall":"13.93","nDCG":"7.21"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"FREEDOM (MMFashion + Sentecen Bert)","rank_in_archive_order":2,"of":18,"metrics":{"Hit Ratio":"21.18","Recall":"13.87","nDCG":"7.17"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"FREEDOM (ResNet50 + Sentence Bert)","rank_in_archive_order":3,"of":18,"metrics":{"Hit Ratio":"21.11","Recall":"13.85","nDCG":"7.24"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"LATTICE (ResNet50 + Sentence Bert)","rank_in_archive_order":4,"of":18,"metrics":{"Hit Ratio":"20.65","Recall":"13.44","nDCG":"7.03"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"LightGCN","rank_in_archive_order":5,"of":18,"metrics":{"Hit Ratio":"19.03","Recall":"12.30","nDCG":"6.42"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"VBPR (AltCLIP)","rank_in_archive_order":6,"of":18,"metrics":{"Hit Ratio":"18.19","Recall":"11.94","nDCG":"6.15"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"NGCF-M (MMFashion + Sentecen Bert)","rank_in_archive_order":7,"of":18,"metrics":{"Hit Ratio":"18.22","Recall":"11.93","nDCG":"6.21"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"SGL","rank_in_archive_order":8,"of":18,"metrics":{"Hit Ratio":"18.17","Recall":"11.82","nDCG":"6.50"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"NGCF-M (ResNet50 + Sentence Bert)","rank_in_archive_order":9,"of":18,"metrics":{"Hit Ratio":"18.12","Recall":"11.72","nDCG":"6.11"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"BM3 (ALIGN)","rank_in_archive_order":10,"of":18,"metrics":{"Hit Ratio":"18.04","Recall":"11.67","nDCG":"6.04"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"VBPR (ResNet50 + Sentence Bert)","rank_in_archive_order":11,"of":18,"metrics":{"Hit Ratio":"17.64","Recall":"11.54","nDCG":"6.08"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"BM3 (ResNet50 + Sentence Bert)","rank_in_archive_order":12,"of":18,"metrics":{"Hit Ratio":"17.65","Recall":"11.28","nDCG":"5.83"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"BPRMF","rank_in_archive_order":13,"of":18,"metrics":{"Hit Ratio":"16.55","Recall":"10.72","nDCG":"5.36"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"NGCF","rank_in_archive_order":14,"of":18,"metrics":{"Hit Ratio":"16.21","Recall":"10.42","nDCG":"5.27"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"DGCF","rank_in_archive_order":15,"of":18,"metrics":{"Hit Ratio":"16.21","Recall":"10.42","nDCG":"5.27"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"GRCN (ALIGN)","rank_in_archive_order":16,"of":18,"metrics":{"Hit Ratio":"16.09","Recall":"10.26","nDCG":"5.15"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"GRCN (ResNet50 + Sentence Bert)","rank_in_archive_order":17,"of":18,"metrics":{"Hit Ratio":"14.89","Recall":"9.57","nDCG":"4.83"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-beauty","task":"Multimodal Recommendation","dataset":"Amazon Beauty","model":"ItemKNN","rank_in_archive_order":18,"of":18,"metrics":{"Hit Ratio":"10.89","Recall":"6.97","nDCG":"3.85"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"LATTICE (ResNet50 + Sentence Bert)","rank_in_archive_order":2,"of":18,"metrics":{"Hit Ratio":"43.60","Recall":"29.40","nDCG":"16.07"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"FREEDOM (ResNet50 + Sentence Bert)","rank_in_archive_order":4,"of":18,"metrics":{"Hit Ratio":"43.46","Recall":"29.05","nDCG":"16.15"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"LightGCN","rank_in_archive_order":5,"of":18,"metrics":{"Hit Ratio":"43.19","Recall":"28.66","nDCG":"14.95"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"VBPR (ResNet50 + Sentence Bert)","rank_in_archive_order":6,"of":18,"metrics":{"Hit Ratio":"43.54","Recall":"28.37","nDCG":"15.22"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"NGCF-M (ResNet50 + Sentence Bert)","rank_in_archive_order":8,"of":18,"metrics":{"Hit Ratio":"41.91","Recall":"27.84","nDCG":"15.35"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"BRMF","rank_in_archive_order":10,"of":18,"metrics":{"Hit Ratio":"41.13","Recall":"27.32","nDCG":"14.94"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"SGL","rank_in_archive_order":11,"of":18,"metrics":{"Hit Ratio":"40.81","Recall":"27.09","nDCG":"15.03"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"BM3 (ResNet50 + Sentence Bert)","rank_in_archive_order":12,"of":18,"metrics":{"Hit Ratio":"41.42","Recall":"27.07","nDCG":"14.34"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"DGCF","rank_in_archive_order":13,"of":18,"metrics":{"Hit Ratio":"40.46","Recall":"26.47","nDCG":"14.46"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"NGCF","rank_in_archive_order":14,"of":18,"metrics":{"Hit Ratio":"40.14","Recall":"26.46","nDCG":"14.58"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"GRCN (ResNet50 + Sentence Bert)","rank_in_archive_order":17,"of":18,"metrics":{"Hit Ratio":"36.25","Recall":"22.88","nDCG":"12.17"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-digital","task":"Multimodal Recommendation","dataset":"Amazon Digital Music","model":"ItemKNN","rank_in_archive_order":18,"of":18,"metrics":{"Hit Ratio":"34.51","Recall":"21.74","nDCG":"12.00"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"LATTICE (ResNet50+ Sentence Bert)","rank_in_archive_order":1,"of":18,"metrics":{"Hit Ratio":"25.79","Recall":"15.75","nDCG":"7.71"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"LATTICE (ALIGN)","rank_in_archive_order":2,"of":18,"metrics":{"Hit Ratio":"25.65","Recall":"15.71","nDCG":"7.63"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"FREEDOM (CLIP)","rank_in_archive_order":3,"of":18,"metrics":{"Hit Ratio":"25.88","Recall":"15.64","nDCG":"7.66"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"FREEDOM (ResNet50+ Sentence Bert)","rank_in_archive_order":4,"of":18,"metrics":{"Hit Ratio":"23.59","Recall":"15.58","nDCG":"7.57"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"NGCF-M (CLIP)","rank_in_archive_order":5,"of":18,"metrics":{"Hit Ratio":"24.85","Recall":"14.99","nDCG":"7.43"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"NGCF-M (ResNet50+ Sentence Bert)","rank_in_archive_order":6,"of":18,"metrics":{"Hit Ratio":"24.04","Recall":"14.35","nDCG":"7.14"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"LightGCN","rank_in_archive_order":7,"of":18,"metrics":{"Hit Ratio":"23.95","Recall":"13.99","nDCG":"6.93"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"BM3 (ALIGN)","rank_in_archive_order":8,"of":18,"metrics":{"Hit Ratio":"23.40","Recall":"13.84","nDCG":"6.75"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"BM3 (ResNet50+ Sentence Bert)","rank_in_archive_order":9,"of":18,"metrics":{"Hit Ratio":"22.5","Recall":"13.13","nDCG":"6.42"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"GRCN (CLIP)","rank_in_archive_order":10,"of":18,"metrics":{"Hit Ratio":"22.32","Recall":"13.10","nDCG":"6.47"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"VBPR (ResNet50+ Sentence Bert)","rank_in_archive_order":11,"of":18,"metrics":{"Hit Ratio":"22.01","Recall":"12.83","nDCG":"6.18"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"VBPR (CLIP)","rank_in_archive_order":12,"of":18,"metrics":{"Hit Ratio":"22.10","Recall":"12.78","nDCG":"6.23"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"GRCN (ResNet50+ Sentence Bert)","rank_in_archive_order":13,"of":18,"metrics":{"Hit Ratio":"21.20","Recall":"12.31","nDCG":"6.08"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"DGCF","rank_in_archive_order":14,"of":18,"metrics":{"Hit Ratio":"20.89","Recall":"12.19","nDCG":"5.89"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"SGL","rank_in_archive_order":15,"of":18,"metrics":{"Hit Ratio":"20.49","Recall":"11.85","nDCG":"5.89"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"ItemKNN","rank_in_archive_order":16,"of":18,"metrics":{"Hit Ratio":"20.33","Recall":"11.35","nDCG":"5.76"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"BPRMF","rank_in_archive_order":17,"of":18,"metrics":{"Hit Ratio":"19.70","Recall":"11.28","nDCG":"5.35"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-office","task":"Multimodal Recommendation","dataset":"Amazon Office Products","model":"NGCF","rank_in_archive_order":18,"of":18,"metrics":{"Hit Ratio":"19.62","Recall":"11.05","nDCG":"5.45"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"FREEDOM (MMFashion + Sentence Bert)","rank_in_archive_order":1,"of":18,"metrics":{"Hit Ratio":"20.70","Recall":"13.73","nDCG":"7.10"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"FREEDOM (ResNet50 + Sentence Bert)","rank_in_archive_order":2,"of":18,"metrics":{"Hit Ratio":"20.64","Recall":"13.67","nDCG":"7.04"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"LATTICE (ALIGN)","rank_in_archive_order":3,"of":18,"metrics":{"Hit Ratio":"19.27","Recall":"12.73","nDCG":"6.64"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"LATTICE (ResNet50 + Sentence Bert)","rank_in_archive_order":4,"of":18,"metrics":{"Hit Ratio":"18.95","Recall":"12.42","nDCG":"6.45"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"NGCF-M (ALIGN)","rank_in_archive_order":5,"of":18,"metrics":{"Hit Ratio":"17.16","Recall":"11.12","nDCG":"5.80"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"VBPR (ALIGN)","rank_in_archive_order":6,"of":18,"metrics":{"Hit Ratio":"16.86","Recall":"11.06","nDCG":"5.85"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"NGCF-M (ResNet50 + Sentence Bert)","rank_in_archive_order":7,"of":18,"metrics":{"Hit Ratio":"16.73","Recall":"10.85","nDCG":"5.73"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"VBPR (ResNet50 + Sentence Bert)","rank_in_archive_order":8,"of":18,"metrics":{"Hit Ratio":"16.54","Recall":"10.83","nDCG":"5.70"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"SGL","rank_in_archive_order":9,"of":18,"metrics":{"Hit Ratio":"16.68","Recall":"10.76","nDCG":"5.93"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"LightGCN","rank_in_archive_order":10,"of":18,"metrics":{"Hit Ratio":"16.63","Recall":"10.59","nDCG":"5.58"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"BM3 (ALIGN)","rank_in_archive_order":11,"of":18,"metrics":{"Hit Ratio":"15.78","Recall":"10.07","nDCG":"5.24"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"BM3 (ResNet50 + Sentence Bert)","rank_in_archive_order":12,"of":18,"metrics":{"Hit Ratio":"15.56","Recall":"9.94","nDCG":"5.14"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"GRCN (ALIGN)","rank_in_archive_order":13,"of":18,"metrics":{"Hit Ratio":"15.35","Recall":"9.94","nDCG":"5.07"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"GRCN (ResNet50 + Sentence Bert)","rank_in_archive_order":14,"of":18,"metrics":{"Hit Ratio":"15.00","Recall":"9.67","nDCG":"9.675.07"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"BPRMF","rank_in_archive_order":15,"of":18,"metrics":{"Hit Ratio":"14.75","Recall":"9.51","nDCG":"5.02"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"DGCF","rank_in_archive_order":16,"of":18,"metrics":{"Hit Ratio":"14.71","Recall":"9.43","nDCG":"5.12"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"NGCF","rank_in_archive_order":17,"of":18,"metrics":{"Hit Ratio":"14.44","Recall":"9.24","nDCG":"4.87"},"uses_additional_data":false},{"leaderboard":"/sota/multimodal-recommendation-on-amazon-toys","task":"Multimodal Recommendation","dataset":"Amazon Toys & Games","model":"ItemKNN","rank_in_archive_order":18,"of":18,"metrics":{"Hit Ratio":"11.06","Recall":"6.97","nDCG":"3.91"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}