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From the 1 of 20 linked papers with an AI index.

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20242026
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20 papers

cs.CV2026

Cortical-SSM: A Deep State Space Model for Motor Imagery Decoding from EEG Signals

Shuntaro Suzuki, Shunya Nagashima, Komei Sugiura

The paper introduces Cortical-SSM, a deep state space model that decodes motor imagery EEG signals by integrating temporal, spatial, and frequency information, achieving higher acc…

cs.CV2026

Stitch4D: Sparse Multi-Location 4D Urban Reconstruction via Spatio-Temporal Interpolation

Hina Kogure, Kei Katsumata, Taiki Miyanishi +1

Dynamic urban environments are often captured by cameras placed at spatially separated locations with little or no view overlap. However, most existing 4D reconstruction methods as…

cs.CV2026

Rigel: Self-Distilled Score Adaptation for Image and Video Captioning Evaluation

Shuitsu Koyama, Kazuki Matsuda, Yuiga Wada +3

Automatic evaluation of image and video captioning is essential for benchmarking multimodal systems, although standard evaluation metrics show limited alignment with human judgment…

cs.CV2026

MLLM-as-a-Judge Exhibits Model Preference Bias

Shuitsu Koyama, Yuiga Wada, Daichi Yashima +1

Automatic evaluation using multimodal large language models (MLLMs), commonly referred to as MLLM-as-a-Judge, has been widely used to measure model performance. If such MLLM-as-a-J…

cs.CV2026

ZINA: Multimodal Fine-grained Hallucination Detection and Editing

Yuiga Wada, Kazuki Matsuda, Komei Sugiura +1

Multimodal Large Language Models (MLLMs) often generate hallucinations, where the output deviates from the visual content. Given that these hallucinations can take diverse forms, d…

cs.RO2026

HiFlow: Tokenization-Free Scale-Wise Autoregressive Policy Learning via Flow Matching

Daichi Yashima, Koki Seno, Shuhei Kurita +2

Coarse-to-fine autoregressive modeling has recently shown strong promise for visuomotor policy learning, combining the inference efficiency of autoregressive methods with the globa…