# Video Question Answering on ANetQA (oe)

Source: [Video Question Answering on ANetQA (oe)](<https://www.sota2.com/research/sota/video-question-answering-on-anetqa-oe>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-26T05:30:10.547Z

Evaluation of Video Question Answering models on the ANetQA (oe) dataset, measured using accuracy.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Video Question Answering |
| Dataset (including any stated split) | ANetQA (oe) |
| Metric | Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 9 of 9 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Accuracy](<https://www.sota2.com/research/sota/video-question-answering-on-anetqa-oe.md?metric=Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| LLAVA-OV | 56.6 | Not recorded | 68fa76001e209131cea6ad69 |
| LLaVA-Video | 56.5 | Not recorded | 68fa76001e209131cea6ad69 |
| LLaVA-NeXT-INST-IT | 55.2 | Not recorded | 68fa76001e209131cea6ad69 |
| LLaVA-NeXT | 53.8 | Not recorded | 68fa76001e209131cea6ad69 |
| LLaVA-NeXT-INST-IT | 53.7 | Not recorded | 68fa76001e209131cea6ad69 |
| LLaVA-Next-Video | 53.5 | Not recorded | 68fa76001e209131cea6ad69 |
| VideoLLaMA2 | 50.2 | Not recorded | 68fa76001e209131cea6ad69 |
| DeepStack-L | 49.3 | Not recorded | 68fa76001e209131cea6ad69 |
| Video-ChatGPT | 35.2 | Not recorded | 68fa76001e209131cea6ad69 |

### LLAVA-OV

Accuracy: 56.6. Result ID: 699409883a6c3148491a9413.

[Reporting paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa756f1e209131cea67e58.md>)

[Implementation](<https://llava-vl.github.io/blog/llava-onevision>)

Recorded evaluation configuration: {"LLM":"Qwen2-7B","Vision Encoder":"SigLIP-SO400M"}. This record does not assert independent reproduction.

### LLaVA-Video

Accuracy: 56.5. Result ID: 699409883a6c3148491a9414.

[Reporting paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa7a561e209131cea82934.md>)

[Implementation](<https://llava-vl.github.io/blog/llava-video>)

Recorded evaluation configuration: {"LLM":"Qwen2-7B","Vision Encoder":"SigLIP-SO400M"}. This record does not assert independent reproduction.

### LLaVA-NeXT-INST-IT

Accuracy: 55.2. Result ID: 699409883a6c3148491a9417.

[Reporting paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

[Implementation](<https://inst-it.github.io/>)

Recorded evaluation configuration: {"LLM":"Qwen2-7B","Vision Encoder":"SigLIP-SO400"}. This record does not assert independent reproduction.

### LLaVA-NeXT

Accuracy: 53.8. Result ID: 699409883a6c3148491a9415.

[Reporting paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

Recorded evaluation configuration: {"LLM":"Vicuna-7B","Vision Encoder":"CLIP-ViT-Large","baseline":true}. This record does not assert independent reproduction.

### LLaVA-NeXT-INST-IT

Accuracy: 53.7. Result ID: 699409883a6c3148491a9416.

[Reporting paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

[Implementation](<https://inst-it.github.io/>)

Recorded evaluation configuration: {"LLM":"Vicuna-7B","Vision Encoder":"CLIP-ViT-Large"}. This record does not assert independent reproduction.

### LLaVA-Next-Video

Accuracy: 53.5. Result ID: 699409883a6c3148491a9412.

[Reporting paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

Recorded evaluation configuration: {"LLM":"Vicuna-7B","Vision Encoder":"CLIP-ViT-Large"}. This record does not assert independent reproduction.

### VideoLLaMA2

Accuracy: 50.2. Result ID: 699409883a6c3148491a9411.

[Reporting paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa75761e209131cea681dd.md>)

[Implementation](<https://github.com/DAMO-NLP-SG/VideoLLaMA2>)

Recorded evaluation configuration: {"LLM":"Vicuna-7B","Vision Encoder":"CLIP-ViT-Large"}. This record does not assert independent reproduction.

### DeepStack-L

Accuracy: 49.3. Result ID: 699409883a6c3148491a940f.

[Reporting paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa738e1e209131cea5d313.md>)

[Implementation](<https://deepstack-vl.github.io/>)

Recorded evaluation configuration: {"LLM":"Vicuna-7B","Vision Encoder":"CLIP-ViT-Large"}. This record does not assert independent reproduction.

### Video-ChatGPT

Accuracy: 35.2. Result ID: 699409883a6c3148491a9410.

[Reporting paper](<https://www.sota2.com/research/paper/68fa76001e209131cea6ad69.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa73841e209131cea5ce32.md>)

[Implementation](<https://github.com/mbzuai-oryx/Video-ChatGPT>)

Recorded evaluation configuration: {"LLM":"Vicuna-7B","Vision Encoder":"CLIP-ViT-Large"}. This record does not assert independent reproduction.

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