Measuring the Creativity Potential of LLM Agents
Trying to answer the question of "Can LLM agents discover?" through the lens of creativity The post Measuring the Creativity Potential of LLM Agents appeared first on Towards Data Science.
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How to Use a PINN for a Navier-Stokes Inverse Problem
A from-scratch PyTorch build that recovers blood flow, viscosity, and wall shear stress in a narrowed artery from 40 noisy velocity readings The post How to Use a PINN for a Navier-Stokes Inverse Problem appeared first…
Geometry-Aware Adaptation for Pretrained Models
arXiv:2307.12226v3 Announce Type: replace Abstract: Machine learning models -- including prominent zero-shot models -- are often trained on datasets whose labels are only a small proportion of a larger label space. Such…
Initial condition recovery in nonlinear damped viscous photoacoustic tomography using a convolutional neural network-guided gradient-free optimization framework
arXiv:2610.01015v1 Announce Type: cross Abstract: Photoacoustic tomography (PAT) is a hybrid imaging modality that combines high optical contrast with high ultrasonic resolution for biomedical imaging applications. In…
TOAST: Stochastic Robot Action Tokenization for Autoregressive Vision-Language-Action Models
arXiv:2610.00899v1 Announce Type: cross Abstract: Autoregressive Vision-Language-Action models often represent continuous robot actions as discrete token sequences, enabling action prediction with standard next-token…
Managing Context and Communication in Distributed Agentic UAV Swarms
arXiv:2610.01569v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV) swarms increasingly rely on language-model agents to provide adaptive mission-level reasoning in uncertain environments. Fully distributed…
ibUMAP: Coherent and Scalable Field Evaluation for UMAP Optimization
arXiv:2610.01445v1 Announce Type: new Abstract: UMAP achieves scalable layout optimization through stochastic negative sampling. However, this stochasticity can lead to unstable embeddings across reruns and downstream…
SeedFlood: A Step Toward Scalable Decentralized Fine-Tuning of LLMs
arXiv:2602.18181v2 Announce Type: replace Abstract: This work presents SeedFlood, a new approach to decentralized LLM fine-tuning designed to scale across large models, large collaborations, and complex network…
Beyond Affine Transformations: A Soft Dominance Layer for Coordinate-Wise Neural Computation
arXiv:2610.00563v1 Announce Type: new Abstract: This paper presents a preliminary study of an alternative to the affine transformation underlying conventional neural-network layers. In the proposed Soft Dominance Layer,…
A Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with Autoencoders
arXiv:2610.01949v1 Announce Type: cross Abstract: Ransomware has emerged as a major cybersecurity threat, with incidents increasing in frequency and impact across critical sectors. These attacks are typically launched…
EP-Flow: Disordered Crystal Structure Prediction without Site-Level Annotations
arXiv:2610.01315v1 Announce Type: new Abstract: Generative models have made rapid progress in ordered crystal structure prediction, yet many functional materials are intrinsically disordered, with substitutional mixing,…
PACT: End-to-End Learning of Human Pose, Contacts, and Forces from Video
arXiv:2610.00451v1 Announce Type: cross Abstract: Human motion, environmental contacts, and interaction forces are governed by common physical laws, yet existing approaches typically separate visual pose reconstruction…
The hidden advantage of mask resampling: a theory of masked autoencoders
arXiv:2610.01578v1 Announce Type: cross Abstract: Why can masked prediction learn useful representations that unmasked reconstruction misses? We study this question in a high-dimensional model of a masked autoencoder…
Designing for Interpretation Uncertainty: Architecture and Principles for Topological Learning Analytics Dashboards
arXiv:2610.01749v1 Announce Type: cross Abstract: Topological Data Analysis (TDA) offers novel methods for understanding temporal dynamics in complex systems, yet its application in information systems design faces a…
Coupling Perception and Reasoning in Federated Multimodal Graph Foundation Models
arXiv:2610.00277v1 Announce Type: new Abstract: Federated multimodal graph foundation models (GFMs) aim to adapt pretrained multimodal models to decentralized graph data, where each client owns a private multimodal…
One Mastery Threshold Does Not Fit All Knowledge Tracing Models
arXiv:2610.00095v1 Announce Type: new Abstract: Tutoring systems use mastery thresholds to decide when students can stop practicing and advance, but the same numerical threshold can lead to very different decisions when…
Degree-Corrected Joint Matrix Factorization for Multilayer Community Detection
arXiv:2610.01361v1 Announce Type: cross Abstract: Multilayer networks allow the modeling of interactions between the same entities across different contexts, such as temporal observations, varying settings, or…
Model validation in machine learning: A scenario-based guide from hold-out splits to nested group cross-validation in biomedical and applied research
arXiv:2610.01284v1 Announce Type: new Abstract: Model validation estimates the performance of a complete learning procedure on new data. However, an invalid split can produce an optimistic and stable result. This…
Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks
arXiv:2610.00841v1 Announce Type: cross Abstract: For quantum machine learning, the exact boundary between classical and quantum advantage is still poorly understood. Direct comparison between quantum neural networks…
When Do Biological Reasoning Models Use Their Biological Inputs?
arXiv:2610.00898v1 Announce Type: new Abstract: Biological reasoning models use post-training to connect LLMs to biological foundation model representations and biological text. Their benchmark accuracy is taken as…
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