Author

Da Li

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Jul 2026

SHIFT: Self-reconstruction Harnesses Implicit Fine-grained Thinking for Retrieval

This work proposes SHIFT, a retrieval training framework based on LLMs that transfers LLMs into reasoning-efficient retrievers with residual projection and task-oriented bidirectional attention aggregation in the latent space, and alleviates the mismatch between contrastive learning and implicit reasoning using fine-grained next-token-prediction-based reconstruction.

Yuxiao Luo, Da Li, Mingjie Zhang et al. · arXiv.org · 0 citations

Jul 2026

Can LVLMs Uncover the Truth Behind Visual Illusions? An Analysis of Perceptual and Reasoning Capabilities

This work constructed Illusion-Reasoning, a benchmark of illusion images collected from the real world, incorporating diverse annotated question-answer pairs, and shows that the reasoning capabilities of a wide range of LVLMs are not as advanced as claimed.

Liang Zhao, Jiaqing Lyu, Kexin Tang et al. · arXiv.org · 0 citations