# Ensuring Reliable Participation in Subjective Video Quality Tests Across Platforms

arXiv: https://arxiv.org/abs/2509.20001 · HTML: https://mlsanity.com/paper/2509.20001/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 13 references that are in the map.
- First posted on arXiv 24 Sep 2025.

## Builds on (most cited first, 3 of 3)

- [Quality Control in Crowdsourcing: A Survey of Quality Attributes, Assessment Techniques and Assurance Actions](https://mlsanity.com/paper/1801.02546/) (2018)
- [A crowdsourcing approach to video quality assessment](https://mlsanity.com/paper/2204.06784/) (2022)
- [VCD: A Video Conferencing Dataset for Video Compression](https://mlsanity.com/paper/2309.07376/) (2023)

## Abstract (arXiv)

Subjective video quality assessment (VQA) is the gold standard for measuring end-user experience across communication, streaming, and UGC pipelines. Beyond high-validity lab studies, crowdsourcing offers accurate, reliable, faster, and cheaper evaluation-but suffers from unreliable submissions by workers who ignore instructions or game rewards. Recent tests reveal sophisticated exploits of video metadata and rising use of remote-desktop (RD) connections, both of which bias results. We propose objective and subjective detectors for RD users and compare two mainstream crowdsourcing platforms on their susceptibility and mitigation under realistic test conditions and task designs.