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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AI Research
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…
Emergent Object Binding Has a Finite Spatial Horizon
arXiv:2610.00006v1 Announce Type: cross Abstract: Pretrained Vision Transformers encode whether two image patches belong to the same object. This IsSameObject signal is decodable from frozen patch embeddings at high…
Supervise What Decides Success: Criterion-Aligned Auxiliary Losses for Latent World-Model Planning
arXiv:2610.01224v1 Announce Type: new Abstract: Latent world models plan by scoring candidate action sequences with distances in latent space. However, task success is judged by physical quantities, which we call the…
AnyJev Technical Report
arXiv:2610.00831v1 Announce Type: new Abstract: A typed decision is a choice among a fixed set of options, returned as a probability rather than as text. Systems that need typed decisions today use models trained for…
Permutation-Robust Decision Modeling with Candidate-Independent Block-Causal Attention
arXiv:2610.01601v1 Announce Type: new Abstract: Decision models often score a variable-sized set of candidate actions encoded in a single sequence. This setting is increasingly relevant for System 1 components inside…
Signal-Noise Factorization Isolates Nuisance Variation into Removable Subspaces
arXiv:2610.00751v1 Announce Type: new Abstract: Recent theoretical work identified fundamental properties of representation geometry that shape inference ability of deep neural networks. These include signal-noise…
A Large Scale Investigation of Scaling Limits in Chemical Language Models
arXiv:2508.13408v3 Announce Type: replace Abstract: Chemical Language Models (CLMs) are increasingly used in de novo drug design, driven by recent growth in model scale, compute, and dataset size. However, the…
Crossing the Cyber Divide: Sim-to-Sim and Sim-to-Real Transfer for RL Agents
arXiv:2610.00759v1 Announce Type: cross Abstract: Cyber attack agents are typically trained and evaluated within a single simulator, making it unclear whether learned policies transfer beyond the environments in which…
Learning the identity: a case study of how SGD selects among functional decompositions
arXiv:2610.00615v1 Announce Type: new Abstract: One might think that learning the identity function with a deep linear residual network is trivial - the path along residual connections already implements the identity,…
Deep Learning for Anomaly Detection in Railway Systems: A Structured Survey
arXiv:2610.00363v1 Announce Type: new Abstract: Ensuring safe and reliable operation of modern railway systems increasingly relies on data-driven monitoring and intelligent fault detection. Deep learning has emerged as…
BranchIP: Learning Adaptive Equivariant Computation for Interatomic Potentials
arXiv:2610.02013v1 Announce Type: new Abstract: Equivariant machine learning interatomic potentials (MLIPs) have revolutionized atomistic modeling, but accurate treatment of complex materials and molecular systems…
Let the Heads Talk: Beyond Diagonal Graph Attention
arXiv:2610.01494v1 Announce Type: new Abstract: Sheaf Neural Networks generalize scalar-weighted message passing by replacing scalar edge weights with linear transport maps between local feature spaces. Yet the role of…
STATERA: Hidden Mass Estimation via Zero-Shot Sim-to-Real Kinematics using Frozen Temporal Tubelets
arXiv:2610.00003v1 Announce Type: cross Abstract: Vision models pretrained for frame-level appearance often struggle to infer hidden physical properties from motion. We study center-of-mass (CoM) localization for…
Refusal Localizes, the Damage Relocates: Safety Layers Under Few-Sample Fine-Tuning
arXiv:2610.00320v1 Announce Type: cross Abstract: Fine-tuning adapts aligned large language models (LLMs) to downstream tasks, but a few dozen harmful examples can remove their refusal of harmful requests. Prior work…
LESS: Lightweight Evolutionary Supernet Search in Minutes
arXiv:2610.01468v1 Announce Type: cross Abstract: Low-cost NAS must both explore high-performing architectures and identify them reliably, yet reducing evaluation cost often weakens the fidelity of candidate…
SyntheticHLS: Building Diverse Synthetic High-Level Synthesis Datasets using LLMs
arXiv:2610.00106v1 Announce Type: cross Abstract: Deep learning and large language models (LLMs) are rapidly gaining adoption in semiconductor design, driving demand for training datasets. Most efforts focus on hardware…
One Basis to Animate Them All: Gaussian Blendshape Distillation for Real-Time Avatars
arXiv:2610.02207v1 Announce Type: cross Abstract: 3D Gaussian avatars support fast rendering, however, their real-time animation is often challenged by the costly neural inference. We address this bottleneck and show…
Fractional Laplace Neural Operators: Exact Architectures, an Expressivity Frontier at Criticality, and Certified Stability for Memory-Driven Network Dynamics
arXiv:2610.00515v1 Announce Type: cross Abstract: Neural operators learn maps between function spaces, while hereditary network dynamics are described by Volterra resolvents with non-rational Laplace symbols. We…
Nonparametric Distribution Matching for Self-Supervised Whole-Slide Image Condensation
arXiv:2610.00678v1 Announce Type: cross Abstract: Histological whole-slide images (WSIs) are central to computational pathology but pose severe computational challenges due to their extremely high resolution, often…
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