VeRVE uses a shared MLLM backbone with contrastive alignment and LoRA training to surpass other MLLM methods on zero-shot video retrieval while enabling competitive moment retrieval and state-of-the-art composed retrieval without further training.
Repre- sentation learning with contrastive predictive coding
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.CV 2years
2026 2verdicts
UNVERDICTED 2roles
method 1polarities
use method 1representative citing papers
ID-Sim is a new similarity metric that aims to capture human selective sensitivity to identities by training on curated real and generative synthetic data and validating against human annotations on recognition, retrieval, and generative tasks.
citing papers explorer
-
ID-Sim: An Identity-Focused Similarity Metric
ID-Sim is a new similarity metric that aims to capture human selective sensitivity to identities by training on curated real and generative synthetic data and validating against human annotations on recognition, retrieval, and generative tasks.