Academic

Academic · 1 min

Shape-informed cardiac mechanics surrogates in data-scarce regimes via geometric encoding and generative augmentation

arXiv:2602.20306v1 Announce Type: new Abstract: High-fidelity computational models of cardiac mechanics provide mechanistic insight into the heart function but are computationally prohibitive for routine clinical …

Davide Carrara, Marc Hirschvogel, Francesca Bonizzoni, Stefano Pagani, Simone Pezzuto, Francesco Regazzoni

8 views Feb 26

Academic · 1 min

In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks

arXiv:2602.20307v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) have demonstrated strong generalization capabilities across diverse datasets and tasks. However, existing foundation models are typically …

Shangqing Xu, Harshavardhan Kamarthi, Haoxin Liu, B. Aditya Prakash

2 views Feb 26

Academic · 1 min

QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models

arXiv:2602.20309v1 Announce Type: new Abstract: Vision-language-action (VLA) models unify perception, language, and control for embodied agents but face significant challenges in practical deployment due to …

Jingxuan Zhang, Yunta Hsieh, Zhongwei Wang, Haokun Lin, Xin Wang, Ziqi Wang, Yingtie Lei, Mi Zhang

2 views Feb 26

Academic · 1 min

CaDrift: A Time-dependent Causal Generator of Drifting Data Streams

arXiv:2602.20329v1 Announce Type: new Abstract: This work presents Causal Drift Generator (CaDrift), a time-dependent synthetic data generator framework based on Structural Causal Models (SCMs). The …

Eduardo V. L. Barboza, Jean Paul Barddal, Robert Sabourin, Rafael M. O. Cruz

6 views Feb 26

Academic · 1 min

Emergent Manifold Separability during Reasoning in Large Language Models

arXiv:2602.20338v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting significantly improves reasoning in Large Language Models, yet the temporal dynamics of the underlying representation geometry remain …

Alexandre Polo, Chanwoo Chun, SueYeon Chung

3 views Feb 26

Academic · 1 min

Hierarchical Molecular Representation Learning via Fragment-Based Self-Supervised Embedding Prediction

arXiv:2602.20344v1 Announce Type: new Abstract: Graph self-supervised learning (GSSL) has demonstrated strong potential for generating expressive graph embeddings without the need for human annotations, making …

Jiele Wu, Haozhe Ma, Zhihan Guo, Thanh Vinh Vo, Tze Yun Leong

5 views Feb 26

Academic · 1 min

Momentum Guidance: Plug-and-Play Guidance for Flow Models

arXiv:2602.20360v1 Announce Type: new Abstract: Flow-based generative models have become a strong framework for high-quality generative modeling, yet pretrained models are rarely used in their …

Runlong Liao, Jian Yu, Baiyu Su, Chi Zhang, Lizhang Chen, Qiang Liu

3 views Feb 26

Academic · 1 min

Quantitative Approximation Rates for Group Equivariant Learning

arXiv:2602.20370v1 Announce Type: new Abstract: The universal approximation theorem establishes that neural networks can approximate any continuous function on a compact set. Later works in …

Jonathan W. Siegel, Snir Hordan, Hannah Lawrence, Ali Syed, Nadav Dym

7 views Feb 26

Academic · 1 min

cc-Shapley: Measuring Multivariate Feature Importance Needs Causal Context

arXiv:2602.20396v1 Announce Type: new Abstract: Explainable artificial intelligence promises to yield insights into relevant features, thereby enabling humans to examine and scrutinize machine learning models …

J\"org Martin, Stefan Haufe

5 views Feb 26

Academic · 1 min

GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training

arXiv:2602.20399v1 Announce Type: new Abstract: Neural simulators promise efficient surrogates for physics simulation, but scaling them is bottlenecked by the prohibitive cost of generating high-fidelity …

Haixu Wu, Minghao Guo, Zongyi Li, Zhiyang Dou, Mingsheng Long, Kaiming He, Wojciech Matusik

3 views Feb 26

Academic · 1 min

Three Concrete Challenges and Two Hopes for the Safety of Unsupervised Elicitation

arXiv:2602.20400v1 Announce Type: new Abstract: To steer language models towards truthful outputs on tasks which are beyond human capability, previous work has suggested training models …

Callum Canavan, Aditya Shrivastava, Allison Qi, Jonathan Michala, Fabien Roger

3 views Feb 26

Academic · 1 min

Wasserstein Distributionally Robust Online Learning

arXiv:2602.20403v1 Announce Type: new Abstract: We study distributionally robust online learning, where a risk-averse learner updates decisions sequentially to guard against worst-case distributions drawn from …

Guixian Chen, Salar Fattahi, Soroosh Shafiee

8 views Feb 26

Something extraordinary is coming.

Shape-informed cardiac mechanics surrogates in data-scarce regimes via geometric encoding and generative augmentation

In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks

QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models

CaDrift: A Time-dependent Causal Generator of Drifting Data Streams

Emergent Manifold Separability during Reasoning in Large Language Models

Hierarchical Molecular Representation Learning via Fragment-Based Self-Supervised Embedding Prediction

Momentum Guidance: Plug-and-Play Guidance for Flow Models

Quantitative Approximation Rates for Group Equivariant Learning

cc-Shapley: Measuring Multivariate Feature Importance Needs Causal Context

GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training

Three Concrete Challenges and Two Hopes for the Safety of Unsupervised Elicitation

Wasserstein Distributionally Robust Online Learning

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