Papers with projector

3 papers
Query-based Cross-Modal Projector Bolstering Mamba Multimodal LLM (2024.findings-emnlp)

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Challenge: Existing models that capture multiple modalities with a single input length are unable to handle this computational burden.
Approach: They propose a query-based cross-modal projector that compresses visual tokens based on input through the cross-attention mechanism.
Outcome: The proposed projector reduces the need for manually designing the 2D scan order of original image features when converting them into an input sequence for Mamba LLMs.
Activating Distributed Visual Region within LLMs for Efficient and Effective Vision-Language Training and Inference (2025.acl-long)

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Challenge: Existing Large Vision-Language Models (LVLMs) learn visual capacity through visual instruction tuning.
Approach: They propose a method for LVLMs to be trained by selective layers tuning . they propose removing non-critical layers outside the visual region .
Outcome: The proposed approach preserves nearly 99% of visual performance and improves textual task results while reducing training time.
The Dominance of Text Space: Unveiling the Asymmetric Nature of Cross-Modal Alignment in Large Language Models (2026.acl-long)

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Challenge: Existing methods for cross-modal alignment assume a symmetric interaction between visual and textual modalities, implying that both spaces adapt to each other.
Approach: They propose a method that regularizes the projector to maintain the geometric structure of the text embedding space via spectral filtering.
Outcome: The proposed method preserves the LLM’s inherent linguistic capabilities and reduces object hallucination significantly better than standard fine-tuning methods.

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