University of Potsdam

The work presents pm4aa, a pipeline that extracts object-centric event logs from GitHub repositories via PyStack't, maps commits to SE tasks with a Conventional Commits regular expression, partitions 589 users into eight roles with a priority-ordered rule classifier, applies object-centric, imperative (BPMN), and declarative (DECLARE) process mining per role, has an LLM generate process descriptions, and synthesizes a LangGraph multi-agent application through IBM BOB; on the Commitizen project (November 2017 to November 2025, 21,488 events, 4,813 objects) it produced five role agents, three smoke tests routed correctly, and a ten-participant user study rated knowledge schema, operational clarity, and human engagement at a median of 4, accountability at 3, and autonomy at only 2.

The work presents pm4aa, a pipeline that extracts object-centric event logs from GitHub repositories via PyStack't, maps commits to SE tasks with a Conventional Commits regular expression, partitions 589 users into eight roles with a priority-ordered rule classifier, applies object-centric, imperative (BPMN), and declarative (DECLARE) process mining per role, has an LLM generate process descriptions, and synthesizes a LangGraph multi-agent application through IBM BOB; on the Commitizen project (November 2017 to November 2025, 21,488 events, 4,813 objects) it produced five role agents, three smoke tests routed correctly, and a ten-participant user study rated knowledge schema, operational clarity, and human engagement at a median of 4, accountability at 3, and autonomy at only 2.

The work continues the self-supervised objective of the general video world model V-JEPA 2 on roughly 62 hours of unlabelled vocal-tract real-time MRI to obtain a frozen Arti-JEPA encoder, and evaluates it on phoneme prediction, fluent-versus-disfluent classification, and pre/post-glossectomy transfer, finding that a temporal video prior clearly beats per-frame image encoders, that latent prediction is at least as strong as pixel reconstruction, that domain adaptation roughly doubles cross-domain Cohen's kappa for phonemes but helps binary stuttering detection only marginally, and that phoneme signal remains partly decodable after surgery.

The work continues the self-supervised objective of the general video world model V-JEPA 2 on roughly 62 hours of unlabelled vocal-tract real-time MRI to obtain a frozen Arti-JEPA encoder, and evaluates it on phoneme prediction, fluent-versus-disfluent classification, and pre/post-glossectomy transfer, finding that a temporal video prior clearly beats per-frame image encoders, that latent prediction is at least as strong as pixel reconstruction, that domain adaptation roughly doubles cross-domain Cohen's kappa for phonemes but helps binary stuttering detection only marginally, and that phoneme signal remains partly decodable after surgery.