Video-HopChain-8B-Standard-RL

This is the stage-1 checkpoint of Video-HopChain. It is Qwen3-VL-8B-Instruct trained with GRPO on a 105,993-row general video QA mixture (LLaVA-Video 72,421, STAR 11,455, CLEVRER 8,220, NExT-QA 7,549, PerceptionTest 6,348) at 24 frames, taken at step 80. It saw no Video-HopChain data and used no Confidence-Gated Exploration (CGE). It is the "+ standard RL" row of Table 1 in the paper. Use it as the starting point of both second-stage runs, including ngqtrung/Video-HopChain-8B, as a baseline, or to reproduce Table 1.

• Paper: Video-HopChain: Multi-Hop Questions and Confidence-Gated Exploration for Video Reasoning Models (arXiv:2609.25773)
• Final model: ngqtrung/Video-HopChain-8B
• Dataset: ngqtrung/Video-HopChain
• Project page: ngquangtrung57.github.io/video-hopchain-page
• Code: github.com/ngquangtrung57/video-hopchain
• Collection: Video-HopChain

Results

Accuracy in percent, evaluated with lmms-eval at 100 frames per video under one setting for every row: at most 501,760 pixels per frame, a 33,792-token context, and at most 16,384 generated tokens. "In-domain" is the 1,000-question held-out Video-HopChain split.

Model	Video-MME	PerceptionComp	Video-MMMU	Video-Holmes	VCRBench	MMR-V	LongVideo-Reason	VRBench	mean	in-domain
Qwen3-VL-8B-Instruct	64.0	28.1	63.5	40.7	32.0	42.7	72.6	74.7	52.3	13.4
this model (+ standard RL)	65.8	34.3	63.0	47.4	35.9	43.4	76.1	77.6	55.4	13.4
Video-HopChain-8B (final)	69.2	37.4	67.5	48.6	44.9	46.6	78.9	81.0	59.3	23.2

VCRBench is reported on its multiple-choice subset.

Usage

from transformers import AutoProcessor, Qwen3VLForConditionalGeneration

model = Qwen3VLForConditionalGeneration.from_pretrained(
    "ngqtrung/Video-HopChain-8B-Standard-RL", dtype="auto", device_map="auto")
processor = AutoProcessor.from_pretrained("ngqtrung/Video-HopChain-8B-Standard-RL")

The weights are BF16. The model was trained to reason inside <think>...</think> and to put the final answer in <answer>\boxed{...}</answer>, so use the same system prompt as training. It is in the dataset rows.

Citation

@misc{nguyenquang2026videohopchain,
  title         = {Video-HopChain: Multi-Hop Questions and Confidence-Gated Exploration for Video Reasoning Models},
  author        = {Nguyen Quang, Trung and Dong, Yuhao and Sun, Shuo and Liu, Shuai and Tian, Shulin and Yap, Kim-Hui and Liu, Ziwei},
  year          = {2026},
  eprint        = {2609.25773},
  archivePrefix = {arXiv},
  primaryClass  = {cs.CV},
  url           = {https://arxiv.org/abs/2609.25773}
}