AI Video Papers2026
Turns live video into reusable textual memory and timely responses by training a streaming video LLM to proactively generate time-grounded captions and event summaries. Key components: Proactive Hierarchical Caption Memory (PHCM) for multi-scale records and Proactive State Transition Learning (PSTL) to balance response timing; trained on the OneStreamer-1M streaming dataset.
AI Model2026
Provides calibrated probabilistic decisions (yes/no, 2–256 choice, 0–5 score) in one forward pass, with an optional adaptive-thinking mode that invokes Gemma‑4 when System 1 is uncertain; supports text+image, 256K context and vLLM serving, but adaptive thinking is much slower.
AI Video Papers2026
Introduces LoHi, a training-free, single-pass method that mixes dense low-resolution video streams with sparse high-resolution frames to improve long-video vision-language model accuracy under strict token budgets while cutting front-end decoding latency.