SkyNative introduces an encoder-free architecture using raw patch tokens and modality-specific parameters in a unified autoregressive model to improve image-grounded reasoning in remote sensing vision-language tasks.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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UNVERDICTED 3representative citing papers
DeltaPrompts generates 200k synthetic high-divergence reasoning prompts to escape zero-delta saturation in multimodal distillation, yielding up to 15% relative gains on chart, document, and perception benchmarks across multiple settings.
ArgLLMs build argumentation frameworks from LLMs to support explainable and contestable formal reasoning for claim verification.
citing papers explorer
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SkyNative: A Native Multimodal Framework for Remote Sensing Visual Evidence Reasoning
SkyNative introduces an encoder-free architecture using raw patch tokens and modality-specific parameters in a unified autoregressive model to improve image-grounded reasoning in remote sensing vision-language tasks.
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DeltaPrompts: Escaping the Zero-Delta Trap in Multimodal Distillation
DeltaPrompts generates 200k synthetic high-divergence reasoning prompts to escape zero-delta saturation in multimodal distillation, yielding up to 15% relative gains on chart, document, and perception benchmarks across multiple settings.
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Argumentative Large Language Models for Explainable and Contestable Claim Verification
ArgLLMs build argumentation frameworks from LLMs to support explainable and contestable formal reasoning for claim verification.