{"id":"W4411206941","doi":"10.1109/icsses64899.2025.11009852","title":"Cross-Lingual Summarization for Overseas Applications Using Multilingual Pre-Trained Models and Knowledge Distillation","year":2025,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Automatic summarization; Distillation; Computer science; Natural language processing; Artificial intelligence; Information retrieval; Chromatography; Chemistry","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":[0.001745881,0.002603151,0.001264628,0.002448619,0.001016125,0.002495054,0.001817989,0.001328107,0.0046403],"category_scores_gemma":[0.005811667,0.0005418329,0.001638579,0.002381927,0.0005550761,0.003971008,0.002920771,0.00209121,0.004985741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009145797,"about_ca_system_score_gemma":0.002017497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01003558,"about_ca_topic_score_gemma":0.01853545,"domain_scores_codex":[0.9987627,0.0003605009,0.0001178191,0.0004368816,0.0002170439,0.0001049461],"domain_scores_gemma":[0.9980339,0.000657376,0.0001499395,0.0004758229,0.0005928968,0.0000901142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004206497,0.0002470698,0.001812406,0.0006447016,0.0003003615,0.0006150662,0.0009190497,0.0880722,0.02699383,0.004781031,0.02674007,0.8484536],"study_design_scores_gemma":[0.0000719624,0.0003255843,0.00112095,0.00007775871,0.0002496296,0.0002392708,0.0008683887,0.9154043,0.03259033,0.01416425,0.0347804,0.0001071358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04110764,0.002185509,0.8986046,0.0008065135,0.0004203026,0.000268395,0.003507681,0.04823531,0.004864047],"genre_scores_gemma":[0.3891751,0.001436467,0.5593352,0.0005960941,0.0004098286,0.0004199861,0.03183506,0.003070874,0.01372133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01003558,"threshold_uncertainty_score":0.01995432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0274146814552919,"score_gpt":0.3821695892073129,"score_spread":0.354754907752021,"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."}}