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Academic · 1 min

On the Cone Effect and Modality Gap in Medical Vision-Language Embeddings

arXiv:2603.17246v1 Announce Type: new Abstract: Vision-Language Models (VLMs) exhibit a characteristic "cone effect" in which nonlinear encoders map embeddings into highly concentrated regions of the …

David Restrepo, Miguel L Martins, Chenwei Wu, Luis Filipe Nakayama, Diego M Lopez, Stergios Christodoulidis, Maria Vakalopoulou, Enzo Ferrante

11 views Mar 19

Academic · 1 min

Binary Latent Protein Fitness Landscapes for Quantum Annealing Optimization

arXiv:2603.17247v1 Announce Type: new Abstract: We propose Q-BIOLAT, a framework for modeling and optimizing protein fitness landscapes in binary latent spaces. Starting from protein sequences, …

Truong-Son Hy

21 views Mar 19

Academic · 1 min

Pathology-Aware Multi-View Contrastive Learning for Patient-Independent ECG Reconstruction

arXiv:2603.17248v1 Announce Type: new Abstract: Reconstructing a 12-lead electrocardiogram (ECG) from a reduced lead set is an ill-posed inverse problem due to anatomical variability. Standard …

Youssef Youssef, Jitin Singla

12 views Mar 19

Academic · 1 min

Variational Rectification Inference for Learning with Noisy Labels

arXiv:2603.17255v1 Announce Type: new Abstract: Label noise has been broadly observed in real-world datasets. To mitigate the negative impact of overfitting to label noise for …

Haoliang Sun, Qi Wei, Lei Feng, Yupeng Hu, Fan Liu, Hehe Fan, Yilong Yin

11 views Mar 19

Academic · 1 min

Classifier Pooling for Modern Ordinal Classification

arXiv:2603.17278v1 Announce Type: new Abstract: Ordinal data is widely prevalent in clinical and other domains, yet there is a lack of both modern, machine-learning based …

Noam H. Rotenberg, Andreia V. Faria, Brian Caffo

17 views Mar 19

Academic · 1 min

WINFlowNets: Warm-up Integrated Networks Training of Generative Flow Networks for Robotics and Machine Fault Adaptation

arXiv:2603.17301v1 Announce Type: new Abstract: Generative Flow Networks for continuous scenarios (CFlowNets) have shown promise in solving sequential decision-making tasks by learning stochastic policies using …

Zahin Sufiyan, Shadan Golestan, Yoshihiro Mitsuka, Shotaro Miwa, Osmar Zaiane

12 views Mar 19

Academic · 1 min

Learning Permutation Distributions via Reflected Diffusion on Ranks

arXiv:2603.17353v1 Announce Type: new Abstract: The finite symmetric group S_n provides a natural domain for permutations, yet learning probability distributions on S_n is challenging due …

Sizhuang He, Yangtian Zhang, Shiyang Zhang, David van Dijk

10 views Mar 19

Academic · 1 min

Beyond Outliers: A Data-Free Layer-wise Mixed-Precision Quantization Approach Driven by Numerical and Structural Dual-Sensitivity

arXiv:2603.17354v1 Announce Type: new Abstract: Layer-wise mixed-precision quantization (LMPQ) enables effective compression under extreme low-bit settings by allocating higher precision to sensitive layers. However, existing …

Hengyuan Zhang, Xinrong Chen, Zunhai Su, Xiao Liang, Jing Xiong, Wendong Xu, He Xiao, Chaofan Tao, Wei Zhang, Ruobing Xie, Lei Jiang, Hayden Kwok-Hay So, Ngai Wong

10 views Mar 19

Academic · 1 min

Variational Kernel Design for Internal Noise: Gaussian Chaos Noise, Representation Compatibility, and Reliable Deep Learning

arXiv:2603.17365v1 Announce Type: new Abstract: Internal noise in deep networks is usually inherited from heuristics such as dropout, hard masking, or additive perturbation. We ask …

Ziran Liu

15 views Mar 19

Academic · 1 min

Efficient Exploration at Scale

arXiv:2603.17378v1 Announce Type: new Abstract: We develop an online learning algorithm that dramatically improves the data efficiency of reinforcement learning from human feedback (RLHF). Our …

Seyed Mohammad Asghari, Chris Chute, Vikranth Dwaracherla, Xiuyuan Lu, Mehdi Jafarnia, Victor Minden, Zheng Wen, Benjamin Van Roy

13 views Mar 19

Academic · 1 min

SCALE:Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction

arXiv:2603.17380v1 Announce Type: new Abstract: Virtual cell models aim to enable in silico experimentation by predicting how cells respond to genetic, chemical, or cytokine perturbations …

Shuizhou Chen, Lang Yu, Kedu Jin, Songming Zhang, Hao Wu, Wenxuan Huang, Sheng Xu, Quan Qian, Qin Chen, Lei Bai, Siqi Sun, Zhangyang Gao

24 views Mar 19

Academic · 1 min

Cohomological Obstructions to Global Counterfactuals: A Sheaf-Theoretic Foundation for Generative Causal Models

arXiv:2603.17384v1 Announce Type: new Abstract: Current continuous generative models (e.g., Diffusion Models, Flow Matching) implicitly assume that locally consistent causal mechanisms naturally yield globally coherent …

Rui Wu, Hong Xie, Yongjun Li

11 views Mar 19

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Articles

On the Cone Effect and Modality Gap in Medical Vision-Language Embeddings

Binary Latent Protein Fitness Landscapes for Quantum Annealing Optimization

Pathology-Aware Multi-View Contrastive Learning for Patient-Independent ECG Reconstruction

Variational Rectification Inference for Learning with Noisy Labels

Classifier Pooling for Modern Ordinal Classification

WINFlowNets: Warm-up Integrated Networks Training of Generative Flow Networks for Robotics and Machine Fault Adaptation

Learning Permutation Distributions via Reflected Diffusion on Ranks

Beyond Outliers: A Data-Free Layer-wise Mixed-Precision Quantization Approach Driven by Numerical and Structural Dual-Sensitivity

Variational Kernel Design for Internal Noise: Gaussian Chaos Noise, Representation Compatibility, and Reliable Deep Learning

Efficient Exploration at Scale

SCALE:Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction

Cohomological Obstructions to Global Counterfactuals: A Sheaf-Theoretic Foundation for Generative Causal Models

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