{"id":"2511.03325","title":"SurgViVQA: Temporally-Grounded Video Question Answering for Surgical Scene Understanding","url":"https://codeofpaper.com/paper/2511.03325","arxiv_url":"https://arxiv.org/abs/2511.03325","published":"2025-11-05","code":"official","best":{"full_name":"madratak/SurgViVQA","url":"https://github.com/madratak/SurgViVQA","tier":"official","stars":8,"license":null,"framework":null,"language":"Python","last_commit":"2025-11-06T08:17:53"},"most_starred_community":null,"implementations":[{"full_name":"madratak/SurgViVQA","url":"https://github.com/madratak/SurgViVQA","tier":"official","stars":8,"license":null,"framework":null,"language":"Python","last_commit":"2025-11-06T08:17:53"}],"possible_matches":0}