When Energy and Information Revolutions Meet 2D Janus

Kavli Affiliate: Long Zhang | First 5 Authors: Long Zhang, Long Zhang, , , | Summary: The depletion of energy sources, worsening environmental issues, and the quantum limitations of integrated circuits for information storage in the post-Moore era, are pressing global concerns. Fortunately, two-dimensional (2D) Janus materials, possessing broken spatial symmetry, with emerging pressure-dependent and […]


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LFD: Layer Fused Decoding to Exploit External Knowledge in Retrieval-Augmented Generation

Kavli Affiliate: Long Zhang | First 5 Authors: Yang Sun, Yang Sun, , , | Summary: Retrieval-augmented generation (RAG) incorporates external knowledge into large language models (LLMs), improving their adaptability to downstream tasks and enabling information updates. Surprisingly, recent empirical evidence demonstrates that injecting noise into retrieved relevant documents paradoxically facilitates exploitation of external knowledge […]


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Copas-Jackson-type bounds for publication bias over a general class of selection models

Kavli Affiliate: Yi Zhou | First 5 Authors: Taojun Hu, Taojun Hu, , , | Summary: Publication bias (PB) is one of the most vital threats to the accuracy of meta-analysis. Adjustment or sensitivity analysis based on selection models, which describe the probability of a study being published, provide a more objective evaluation of PB […]


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Rectified Robust Policy Optimization for Model-Uncertain Constrained Reinforcement Learning without Strong Duality

Kavli Affiliate: Yi Zhou | First 5 Authors: Shaocong Ma, Shaocong Ma, , , | Summary: The goal of robust constrained reinforcement learning (RL) is to optimize an agent’s performance under the worst-case model uncertainty while satisfying safety or resource constraints. In this paper, we demonstrate that strong duality does not generally hold in robust […]


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Bridging the Gap in Ophthalmic AI: MM-Retinal-Reason Dataset and OphthaReason Model toward Dynamic Multimodal Reasoning

Kavli Affiliate: Yi Zhou | First 5 Authors: Ruiqi Wu, Ruiqi Wu, , , | Summary: Multimodal large language models (MLLMs) have recently demonstrated remarkable reasoning abilities with reinforcement learning paradigm. Although several multimodal reasoning models have been explored in the medical domain, most of them focus exclusively on basic reasoning, which refers to shallow […]


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CSTEapp: An interactive R-Shiny application of the covariate-specific treatment effect curve for visualizing individualized treatment rule

Kavli Affiliate: Yi Zhou | First 5 Authors: , , , , | Summary: In precision medicine, deriving the individualized treatment rule (ITR) is crucial for recommending the optimal treatment based on patients’ baseline covariates. The covariate-specific treatment effect (CSTE) curve presents a graphical method to visualize an ITR within a causal inference framework. Recent […]


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Schrödingerization for quantum linear systems problems

Kavli Affiliate: Long Zhang | First 5 Authors: Yin Yang, Yin Yang, , , | Summary: We develop a quantum algorithm for linear algebraic equations Ax=b from the perspective of Schr"odingerization-form problems, which are characterized by a system of linear convection equations in one higher dimension. When A is positive definite, the solution x can […]


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Episodic Memory Representation for Long-form Video Understanding

Kavli Affiliate: Long Zhang | First 5 Authors: Yun Wang, Yun Wang, , , | Summary: Video Large Language Models (Video-LLMs) excel at general video understanding but struggle with long-form videos due to context window limits. Consequently, recent approaches focus on keyframe retrieval, condensing lengthy videos into a small set of informative frames. Despite their […]


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Uncertainty-aware Cross-training for Semi-supervised Medical Image Segmentation

Kavli Affiliate: Yi Zhou | First 5 Authors: Kaiwen Huang, Kaiwen Huang, , , | Summary: Semi-supervised learning has gained considerable popularity in medical image segmentation tasks due to its capability to reduce reliance on expert-examined annotations. Several mean-teacher (MT) based semi-supervised methods utilize consistency regularization to effectively leverage valuable information from unlabeled data. However, […]


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Compass-Thinker-7B Technical Report

Kavli Affiliate: Long Zhang | First 5 Authors: Anxiang Zeng, Anxiang Zeng, , , | Summary: Recent R1-Zero-like research further demonstrates that reasoning extension has given large language models (LLMs) unprecedented reasoning capabilities, and Reinforcement Learning is the core technology to elicit its complex reasoning. However, conducting RL experiments directly on hyperscale models involves high […]


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