{"id":"W4393285750","doi":"10.1109/tmm.2024.3382889","title":"SPACE: Self-Supervised Dual Preference Enhancing Network for Multimodal Recommendation","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Key Research and Development Projects of Shaanxi Province; Fundamental Research Funds for the Central Universities; State Key Laboratory of Integrated Services Networks; National Natural Science Foundation of China","keywords":"Computer science; Preference; Modality (human–computer interaction); Recommender system; Artificial intelligence; Dual (grammatical number); Space (punctuation); Machine learning; Representation (politics); Task (project management); Information retrieval; Human–computer interaction; Natural language processing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001026408,0.0009650022,0.001102864,0.000902595,0.0004156243,0.0005349702,0.001581693,0.00102951,0.001831413],"category_scores_gemma":[0.002678773,0.0004073352,0.0008863304,0.001094374,0.0005157716,0.001526219,0.0009055246,0.001100182,0.0007481488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007133271,"about_ca_system_score_gemma":0.00052268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007514709,"about_ca_topic_score_gemma":0.01162774,"domain_scores_codex":[0.999358,0.0002011043,0.00002657661,0.0001980581,0.0001455729,0.00007068863],"domain_scores_gemma":[0.9989716,0.0004478274,0.0001017478,0.0001501679,0.0002705147,0.00005814159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005481078,0.0004214097,0.006421709,0.0001726052,0.0002486224,0.0001668797,0.0002048609,0.5197784,0.00907319,0.00764924,0.0073698,0.4479452],"study_design_scores_gemma":[0.000006421254,0.00004250961,0.0002634684,0.000004234922,0.00001392908,0.000025541,0.000008344384,0.9972622,0.0006933133,0.001381377,0.0002924326,0.000006257831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04578673,0.0005811082,0.9501089,0.0002217903,0.00004823893,0.0000700255,0.0002685207,0.0008623275,0.002052194],"genre_scores_gemma":[0.8261384,0.0004768687,0.1640774,0.0003778662,0.0001359764,0.0002146259,0.0008475556,0.00009038178,0.007640967],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007514709,"threshold_uncertainty_score":0.01494193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03291627563722623,"score_gpt":0.2738679133519815,"score_spread":0.2409516377147553,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}