TREC 2025 Proceedings

gpt

Submission Details

Organization
ncsu-las
Track
Adhoc Video Search
Task
Video Search Task
Date
2025-07-27

Run Description

Is this run manual or automatic?
automatic
Describe the retrieval model used.
We extract SigLIP2-base-patch16-naflex embeddings at 1 keyframe per second. Each user query is expanded to 100 variants using GPT-4.1-mini, and their text embeddings are averaged into a single query vector. Initial retrieval is done directly using SigLIP similarity, returning the top 2,500 candidates. Each candidate shot is then evaluated 3 times using GPT-4.1-mini, and the scores are averaged. The final results are re-ranked based on these aggregated judgments, and the top 1,000 are submitted.
Describe any external resources used.
Our runs use the SigLIP2-base-patch16-naflex embedding model and gpt-4.1-mini LVLM model.
Training type:
D

Evaluation Files

Paper