{"id":"W4410637878","doi":"10.1145/3701716.3715863","title":"Graph Machine Learning under Distribution Shifts: Adaptation, Generalization and Extension to LLM","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Instituto de Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México; National Key Research and Development Program of China; Microsoft Research Asia; Weill Cornell Medical College; Tsinghua University; Beijing National Research Center For Information Science And Technology; Microsoft Research; National Natural Science Foundation of China; Universitas Brawijaya; York University; Institute for Catastrophic Loss Reduction","keywords":"Computer science; Extension (predicate logic); Generalization; Graph; Adaptation (eye); Theoretical computer science; Artificial intelligence; Machine learning; Mathematics; Programming language; Psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003796845,0.001080232,0.001392129,0.001383768,0.0005559834,0.00110061,0.002907834,0.001941738,0.002716773],"category_scores_gemma":[0.02040434,0.0005018581,0.001446823,0.001777984,0.001869513,0.003280438,0.002737769,0.004349833,0.001037084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001666017,"about_ca_system_score_gemma":0.0009877303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005028271,"about_ca_topic_score_gemma":0.004548911,"domain_scores_codex":[0.9985624,0.0006936541,0.00004957991,0.0003900197,0.0001915042,0.0001127259],"domain_scores_gemma":[0.9920626,0.005275446,0.0005089549,0.001266557,0.0006656318,0.0002207992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001441841,0.0001802602,0.004477528,0.000351415,0.000156283,0.0003409439,0.0005197407,0.622801,0.00280781,0.1500041,0.01678366,0.2014331],"study_design_scores_gemma":[0.000007985653,0.00001987943,0.0003530069,0.00001971139,0.00001296398,0.00004322161,0.00002733507,0.9143901,0.0002333621,0.0832888,0.001592916,0.00001072677],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01972208,0.001584551,0.9728804,0.001738834,0.0001651183,0.00007053226,0.0002486607,0.001042731,0.002547004],"genre_scores_gemma":[0.7204952,0.00443327,0.25654,0.003121884,0.001357006,0.0005438144,0.001711696,0.0009082457,0.01088887],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005028271,"threshold_uncertainty_score":0.02007985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01289816893168876,"score_gpt":0.2492417734022997,"score_spread":0.2363436044706109,"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."}}