Try npm i -g cline on Cline!👀
Try npm i -g cline on Cline!👀Cline: Qwen3.8-Max is now available in ClinePass, a subscription for ~5x discounted access.Use it on Cline CLI w/ $4.99 special…
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Bring any idea to life with Imagine
Bring any idea to life with ImagineArt Muse: Used Grok Imagine’s reference feature to bring my ideas to life.Created a reference character first, then a reference…
Beautiful art from Imagine
Beautiful art from ImagineArt Muse: Happy Tuesday! Wishing you all a wonderful day ahead.
An SLM trained on $8 ESP32-S3
Article URL: https://github.com/Carloscodix/qapla Comments URL: https://news.ycombinator.com/item?id=49178464 Points: 12 # Comments: 3
My favorite piece of merch other than the (not a) flamethrower
My favorite piece of merch other than the (not a) flamethrowerJonah Katz: The SpaceX mug with Mars on it which terraforms green when hot water is…
Quo Vadis, World Modeling?
Continually improving agents require dynamic interaction feedback beyond static supervision, yet direct real-environment interaction is costly, slow, unsafe, and hard to parallelize. World modeling offers a…
ExplainBench: Evaluating Code Explanations from Agents
Large Language Model (LLM) agents have seen rapid adoption in software engineering. As agents take a greater role in the actual generation of code, they are…
Knowledge-Geometry Decoupling: Refreshable Pretrained Transfer for Streaming Recommendation
Industrial recommenders increasingly adopt the pretrain-then-transfer paradigm, yet behavioral distribution drift raises two questions: what to learn from behavior sequences, and how to transfer the learned…
PAST-Bench: Benchmarking the Foundations of Recursive Self-Improvement in Personal Agents
Recursive self-improvement requires agents to turn accumulated experience into better future behavior. Personal AI agents offer a concrete setting for studying this capability because they retain…
Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate
arXiv:2412.11257v4 Announce Type: replace Abstract: For many complex simulation tasks spanning areas such as healthcare, engineering, and finance, Monte Carlo (MC) methods are invaluable due to…
Tight Information Complexity of the Coin Problem in the Broadcast Model
arXiv:2608.02776v1 Announce Type: cross Abstract: We study distributed testing of $mathrm{Ber}(alpha)$ versus $mathrm{Ber}(beta)$ in the broadcast, or shared-blackboard, model. For protocols with constant advantage, we characterise…
Particle-based Generalised Stochastic Optimisation
arXiv:2608.02844v1 Announce Type: new Abstract: We develop a class of diffusion-based stochastic particle optimisation methods for loss functions with intractable gradients. Specifically, we consider problems in…
DAIF: A Data-Driven Intermediate Fusion Framework for Multimodal Supervised Learning via Approximate Message Passing
arXiv:2608.02769v1 Announce Type: cross Abstract: Multimodal supervised learning seeks to leverage multiple heterogeneous data sources to improve predictive performance. A central challenge is determining the fusion…
A PAC-Bayes Approach for Controlling Unknown Linear Discrete-time Systems
arXiv:2605.10493v3 Announce Type: replace-cross Abstract: This paper presents a PAC-Bayes framework for learning controllers for unknown stochastic linear discrete-time systems, where the system parameters are drawn…
Rex: A Family of Reversible Exponential (Stochastic) Runge-Kutta Solvers
arXiv:2502.08834v5 Announce Type: replace-cross Abstract: Deep generative models based on neural differential equations have become state-of-the-art for many generation tasks. These models rely on ODE/SDE solvers…
Neural network realization of binary refinement iterates via a two-chart atlas selector
arXiv:2608.02624v1 Announce Type: cross Abstract: Refinement operators generate many functions used in wavelet constructions, subdivision schemes, and geometric modeling. Their finite iterates can develop rapidly increasing…
Causal Inference with Unstructured Outcomes
arXiv:2608.03085v1 Announce Type: new Abstract: Causal inference has traditionally centered on scalar outcomes: whether a patient recovers, how much a worker earns, or how many visits…
Minimax-Optimal Semiparametric Contextual Dynamic Pricing with Multimodal Revenue
arXiv:2608.03142v1 Announce Type: new Abstract: We study contextual dynamic pricing with arbitrary covariate sequences and bounded, possibly nonbinary purchase quantities. Demand follows a semiparametric surplus-index model…
Conformal risk control for model-form uncertainty in parametric non-intrusive reduced-order models
arXiv:2608.03360v1 Announce Type: new Abstract: Non-intrusive reduced-order models (NIROMs) have become a standard tool for approximating parametric partial differential equations from computer design of experiments while…
Should the Boundary Term Be Learned in Reflected Diffusion? Conormal Trace and Reflection Masking
arXiv:2608.03469v1 Announce Type: new Abstract: We study score learning for reflected diffusion on bounded domains. Reflection keeps trajectories feasible but does not ensure that the learned…
Information-Geometric Forward Policy Training in GFlowNets
arXiv:2608.03967v1 Announce Type: new Abstract: Generative Flow Networks (GFlowNets) have emerged as a flexible framework for amortised inference over discrete and mixed discrete-continuous objects, requiring only…
Robust Low-Tubal-Rank Tensor Completion under Cross-Concentrated Sampling
arXiv:2608.03928v1 Announce Type: new Abstract: Tensor cross-concentrated sampling (t-CCS) bridges entrywise sampling and t-CUR slice-wise sampling by observing entries only within selected horizontal and lateral slices.…
PRISMA: Improving the Accuracy-Latency Frontier of Diffusion-based PDE Solvers Using Physics-Informed Spectral Attention
arXiv:2512.01370v2 Announce Type: replace-cross Abstract: Diffusion-based solvers for partial differential equations (PDEs) are often bottle-necked by slow gradient-based test-time optimization routines that use PDE residuals for…
Convergence analysis of controlled particle systems arising in deep learning: from finite to infinite sample size
arXiv:2404.05185v4 Announce Type: replace-cross Abstract: This paper deals with a class of neural SDEs and studies the limiting behavior of the associated sampled optimal control problems…