Concept Flow Models use hierarchical concept-driven decision trees to mitigate information leakage in concept bottleneck models while matching their predictive performance.
Contrastive localized language-image pre-training
4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4representative citing papers
Proposes Adaptive Tail-Head Alignment (ATHA) that breaks alignment for low-similarity 'tail tokens' in CLIP to boost source-free cross-domain few-shot learning.
ROGLE introduces automated pseudo region-sentence pairs via RSM and multi-granular learning to boost fine-grained alignment in text-based person search, plus the P-VLG benchmark with over 100k annotated regions.
A multimodal RAG framework with ColPali retrieval and task-specific reasoning variants reports 32.6% relative improvement over prior RAG baselines on DesignQA, but the gain is inflated by test-set-fitted routing and an oracle baseline.
citing papers explorer
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Concept Flow Models: Anchoring Concept-Based Reasoning with Hierarchical Bottlenecks
Concept Flow Models use hierarchical concept-driven decision trees to mitigate information leakage in concept bottleneck models while matching their predictive performance.
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Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning
Proposes Adaptive Tail-Head Alignment (ATHA) that breaks alignment for low-similarity 'tail tokens' in CLIP to boost source-free cross-domain few-shot learning.
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ROGLE: Robust Global-Local Alignment with Automated Region Supervision for Text-Based Person Search
ROGLE introduces automated pseudo region-sentence pairs via RSM and multi-granular learning to boost fine-grained alignment in text-based person search, plus the P-VLG benchmark with over 100k annotated regions.
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MCERF: Advancing Multimodal LLM Evaluation of Engineering Documentation with Enhanced Retrieval
A multimodal RAG framework with ColPali retrieval and task-specific reasoning variants reports 32.6% relative improvement over prior RAG baselines on DesignQA, but the gain is inflated by test-set-fitted routing and an oracle baseline.