A fixed-image, multi-task evaluation framework aims to detect data contamination in multimodal LLMs, but its judge is unvalidated and possibly self-referential, and the claimed harm to generalization is not supported by the reported averages.
Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.AI 1years
2025 1verdicts
REJECT 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Reasoning Multimodal Large Language Model: Data Contamination and Dynamic Evaluation
A fixed-image, multi-task evaluation framework aims to detect data contamination in multimodal LLMs, but its judge is unvalidated and possibly self-referential, and the claimed harm to generalization is not supported by the reported averages.