Evian: Towards Explainable Visual Instruction-tuning Data Auditing (2026.findings-acl)
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| Challenge: | Existing data filtering methods rely on coarse-grained scores that lack granularity to identify nuanced semantic flaws. |
| Approach: | They propose a "Decomposition-then-Evaluation" paradigm that breaks model responses into constituent cognitive components. |
| Outcome: | The proposed model outperforms models trained on larger datasets in three key areas . the authors show that Logical Coherence is the most critical factor in data quality evaluation . |
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| Challenge: | Recent studies have focused on the compositionality of vision-language models (VLMs) however, the performance of GVLMs in multimodal compositional reasoning remains under-explored. |
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