Overview
This checkpoint is fine-tuned on top of Qwen3-VL with ArrowRL, one of the RL baselines compared in the CRPO paper.
Video large language models (Video LLMs) often answer video questions through shortcuts such as single-frame cues and language priors rather than by tracking spatiotemporal dynamics. The CRPO paper studies this problem and compares against multiple RL baselines, of which this checkpoint is one.
Resources
Evaluation
The model is evaluated on DyBench, a paired counterfactual video benchmark with 3,014 videos covering reversible dynamics, moving direction, and event sequence, together with standard video-QA benchmarks (Video-MME, TempCompass, MVBench, TimeBlind). See the paper for full numbers and comparison with CRPO.