新闻
The Low Frequency Trap: Video Language Models Fail at Simple Event Bookkeeping
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers found that video language models like Gemini 3.6 Flash fail to count events reliably in videos, especially frequent or numerous events, despite appearing accurate on final answers.
- 为何重要
- Engineers building video understanding systems should care, particularly those relying on models for temporal reasoning or event tracking in production applications.
- 注意
- Higher sampling rates and different prompts show modest improvements in raw accuracy but do not fix the underlying problem of faithful event recovery from video sequences.
收听本摘要
- language model
- rag
- benchmark
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