[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-ai-violence-detector-learns-to-distrust-bad-audio":10,"sections":34},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":24,"tags":25,"sources":29,"feedback":33,"feedback_at":22,"cost_usd":33,"total_tokens":33},4212,"ai-violence-detector-learns-to-distrust-bad-audio","AI Violence Detector Learns to Distrust Bad Audio","A new model called AViS-Mamba lets the visual stream actively reshape how audio is processed, rather than blindly fusing both signals together.","A research team has built a violence-detection model that tells its audio encoder when not to trust itself.\n\nMost audiovisual AI systems extract visual and audio features separately, then blend them at the end. AViS-Mamba flips that order. At every layer of the audio encoder, a compact visual representation injects a modulation vector that reshapes the encoder's internal temporal operators in real time. A routing gate then controls how hard that visual signal pushes. The result: when audio is noisy, dubbed, or missing entirely, the model leans on vision; when audio is clean and informative, it uses it. On two benchmarks - NTU-CCTV and DVD - the model hit 88.59% and 75.74% accuracy, claiming state-of-the-art results on both.\n\nThe practical payoff is resilience. Surveillance footage is exactly the environment where audio fails most often - wind, crowds, distance, and cheap microphones all degrade the signal. A system that degrades gracefully under those conditions is more useful than one optimized only for clean lab recordings. The paper's layer-wise analysis also shows the model doesn't apply one global policy; it adjusts its audio reliance differently at different depths, which suggests the architecture is doing something structurally interesting rather than just learning a simple on-off switch.\n\nThe researchers also introduce Adaptive AV-InfoNCE, a contrastive loss that learns the relative weight between audio-to-video and video-to-audio alignment rather than treating both directions equally - a small but telling sign that fixed assumptions about modality balance keep causing headaches in multimodal research.","[\"ai\",\"computer-vision\",\"surveillance\",\"multimodal\"]","2026-07-07T04:00:00.000Z","2026-07-07T20:05:06.887Z","2026-07-07T20:05:09.888Z","published",null,[],"ai",[24,26,27,28],"computer-vision","surveillance","multimodal",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2604.03329",0,{"sections":35},[36,40,45,50,55,60,65,70,75,79,84,88,93,98],{"name":37,"slug":24,"count":38,"latest_published_at":39},"AI",2590,"2026-07-16T04:00:00.000Z",{"name":41,"slug":42,"count":43,"latest_published_at":44},"Security","security",294,"2026-07-15T19:59:48.000Z",{"name":46,"slug":47,"count":48,"latest_published_at":49},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":51,"slug":52,"count":53,"latest_published_at":54},"Policy","policy",158,"2026-07-16T00:02:48.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Hardware","hardware",122,"2026-07-14T19:46:26.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":64},"Consumer Tech","consumer-tech",93,"2026-07-13T13:20:48.000Z",{"name":66,"slug":67,"count":68,"latest_published_at":69},"Software","software",70,"2026-07-13T19:52:25.000Z",{"name":71,"slug":72,"count":73,"latest_published_at":74},"Science","science",66,"2026-07-10T10:29:37.000Z",{"name":76,"slug":77,"count":78,"latest_published_at":18},"Dev Tools","dev-tools",59,{"name":80,"slug":81,"count":82,"latest_published_at":83},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":85,"slug":86,"count":82,"latest_published_at":87},"Startups","startups","2026-06-29T20:55:50.000Z",{"name":89,"slug":90,"count":91,"latest_published_at":92},"General","general",29,"2026-07-10T22:28:58.000Z",{"name":94,"slug":95,"count":96,"latest_published_at":97},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":99,"slug":100,"count":101,"latest_published_at":102},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]