Datasets:
File size: 1,541 Bytes
f5975d9 46289cd f5975d9 725d16b f5975d9 725d16b f5975d9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | cff-version: 1.2.0
message: "If you use this dataset, please cite as below."
title: "NExT-CF: A Counterfactual Entity-Removal Benchmark for Video Question Answering"
authors:
- name: "Anonymous Authors (submission under review)"
year: 2026
version: "1.0.0"
license: "CC-BY-NC-SA-4.0"
type: dataset
abstract: >
NExT-CF is a benchmark of 570 counterfactually edited videos derived from NExT-QA,
used to probe whether Video Question Answering models rely on visual evidence
or language priors. Each video has a target entity removed via SAM3 segmentation
and DiffuEraser diffusion inpainting, with the corresponding QA pairs carried
over from NExT-QA.
keywords:
- video question answering
- counterfactual
- benchmark
- diagnostic benchmark
- visual grounding
- evidence reliance
- diffusion inpainting
references:
- type: conference-paper
authors:
- family-names: Xiao
given-names: Junbin
- family-names: Shang
given-names: Xindi
- family-names: Yao
given-names: Angela
- family-names: Chua
given-names: Tat-Seng
title: "NExT-QA: Next Phase of Question-Answering to Explaining Temporal Actions"
conference:
name: "IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"
year: 2021
start: 9777
end: 9786
notes: "arXiv:2105.08276; project repo: https://github.com/doc-doc/NExT-QA"
notes: >
NeurIPS 2026 Evaluations & Datasets track submission (under review).
Author identities will be added upon acceptance.
|