Recent advances in multimodal large language models have increased interest in interaction paradigms for video understanding. The evolution from offline to streaming and proactive interaction has grad
Proactive video understanding should include asking for missing information under uncertainty, and the AskStream benchmark reveals current models struggle with this decision.
Recent advances in multimodal large language models have increased interest in interaction paradigms for video understanding. The evolution from offline to streaming and proactive interaction has gradually shifted models from passive responders toward more proactive agents that can decide when to answer. However, existing proactive paradigms typically assume that the information required to answer a query is complete, leaving models to only wait or answer. In the real world, however, information is often incomplete due to uncertainty from either the video or the user. In proactive paradigms, such uncertainty can cause the model to wait forever or generate highly hallucinatory responses. We…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
AskStream: When and What to Ask Proactively under Uncertainty in Streaming Video Understanding was first seen on Hugging Face · Daily papers on Oct 30, 2026. Since then it has appeared in 38 checks on 4 different days. Its best position was #22 of 30, reached on Oct 30, 07:28 UTC. It dropped off the list after Nov 2, 07:28 UTC.
Position on Hugging Face · Daily papers at every check (lower is better).
Best rank per day (UTC).
Platform metric as reported by Hugging Face.
Archived daily, weekly and monthly lists that include this entry.
Not at the moment. It was last on the list on Nov 2, 07:28 UTC, after 4 days of trending.
#22 on Hugging Face · Daily papers, on Oct 30, 07:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 30, 2026 and has been on the list on 4 days (38 checks) since.