AwareVLN introduces a structural reasoning module and automatic data engine with progress division to equip VLN agents with self-awareness of agent state and task progress, outperforming prior methods on Habitat datasets.
Chain-of-thought prompting elicits reasoning in large lan- guage models.Advances in neural information processing systems, 35:24824–24837
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Test-time constrained optimization incorporates priors into pre-trained multiview transformers via self-supervised losses and penalty terms to improve 3D reconstruction accuracy.
AITP is a new multimodal large language model that uses multimodal chain-of-thought and retrieval-augmented generation of legal knowledge to achieve state-of-the-art results on traffic accident responsibility allocation and related tasks, supported by the DecaTARA benchmark of 67,941 videos.
SQI uses axiomatic constraints, hierarchical decomposition, and counterfactual verification to align linguistic reasoning with visual perception in frozen VLMs, achieving second place on the DataCV 2026 illusion challenge.
citing papers explorer
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AwareVLN: Reasoning with Self-awareness for Vision-Language Navigation
AwareVLN introduces a structural reasoning module and automatic data engine with progress division to equip VLN agents with self-awareness of agent state and task progress, outperforming prior methods on Habitat datasets.
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Learning 3D Reconstruction with Priors in Test Time
Test-time constrained optimization incorporates priors into pre-trained multiview transformers via self-supervised losses and penalty terms to improve 3D reconstruction accuracy.
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AITP: Traffic Accident Responsibility Allocation via Multimodal Large Language Models
AITP is a new multimodal large language model that uses multimodal chain-of-thought and retrieval-augmented generation of legal knowledge to achieve state-of-the-art results on traffic accident responsibility allocation and related tasks, supported by the DecaTARA benchmark of 67,941 videos.
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Beyond Shortcuts: Mitigating Visual Illusions in Frozen VLMs via Qualitative Reasoning
SQI uses axiomatic constraints, hierarchical decomposition, and counterfactual verification to align linguistic reasoning with visual perception in frozen VLMs, achieving second place on the DataCV 2026 illusion challenge.