{"passport":{"slug":"hybrid-ltr-based-system-via-social-context-embedding","display_name":"Hybrid LTR-based System via Social Context Embedding","model_type":"null","parameter_count":null,"context_window":null,"claimed_developer":"Stack Overflow","confirmed_developer":null,"developer_confirmed_at":null,"developer_source":null,"first_appeared_at":"2026-03-15T12:31:09.139534+00:00","first_appeared_on":"rss_pipeline","status":"confirmed","availability":null,"deployment_status":"not_deployed","availability_scope":null,"gate":1,"eu_ai_act":null,"regulatory_status":{},"open_source":null,"weights_available":null,"license":null,"provenance_chain":[],"parent_model":null,"model_family":null,"superseded_by":null,"supersedes":[],"recommended_replacement":null,"product_links":null},"events":[{"event_type":"first_appearance","event_date":"2026-03-15T12:31:09.139534+00:00","title":"First recorded in AI news","detail":"A new recommender system is proposed to help software developers find solutions to their bugs by leveraging the crowd-sourced Q&A data available on Stack Overflow. The system uses deep learning techniques to construct a Learning-to-Rank (LTR) model based on the social context and features of Stack Overflow, and achieves nearly 78% correct solutions when recommending the 10 best answers for each question.","source_url":"https://arxiv.org/abs/2603.07229","source_name":"ArXiv AI"}],"delta":{"days_unattributed":116,"claimed_developer":"Stack Overflow","confirmed_developer":null,"match":false}}