Comparative Analysis of Language Models in the Understanding of Short Videos: A Multimodal Approach for Disinformation Detection - Mori, Adriel L. V.; Lima, Eliomar Araújo; Graciano-Neto, Valdemar V.; Barbosa, Jacson R.; Carvalho, Rogerio Rodrigues; Galvão Filho, Arlindo R. (Anais do Simpósio Brasileiro de Banco de Dados (SBBD); 2026: Anais do XLI Simpósio Brasileiro de Bancos de DadosDO - 10.5753/sbbd.2026.249221, 2026)
Short-form videos are increasingly used to spread political disinformation, but multimodal benchmarks for Brazilian Portuguese remain limited. This study evaluates whether structured multimodal evidence improves zero-shot LLM-based detection in Brazilian political videos. We combine CLIP keyframe summarization, Whisper transcription, and pyannote-audio diarization to build prompts from auditory and visual evidence. We benchmark 12 LLMs on 119 videos from the 2022–2024 Brazilian electoral cycles, comparing audio-only and multimodal settings for veracity and taxonomy classification. Results show that gemma2-9b achieves the best veracity performance (macro-F 1 = 0.764), while gemma3-12b leads taxonomy classification (macro-F 1 = 0.518).