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arXiv:2605.22622v1 Announce Type: new Abstract: Wasserstein Policy Optimization (WPO) is a recently proposed reinforcement learning algorithm that leverages Wasserstein gradient flows to optimize stoc

arXiv:2605.22390v1 Announce Type: new Abstract: Accurate wind power forecasting requires reliable uncertainty quantification, yet most existing methods report a single predictive uncertainty that conf

Noah Berman / The Wire China: A profile of TP-Link, whose share of the US consumer router market grew from 10% to 60%+ between 2019 and 2025, as it seeks to rebut national security concerns — When Jef

arXiv:2605.21528v1 Announce Type: new Abstract: Accurate and reproducible disease risk prediction remains challenging due to heterogeneous features, limited samples, and severe class imbalance. This s

arXiv:2602.05304v2 Announce Type: replace Abstract: Stochastic variance-reduced algorithms such as Stochastic Average Gradient (SAG) and SAGA, and their deterministic counterparts like the Incremental

arXiv:2411.08126v2 Announce Type: replace-cross Abstract: We study offline dynamic pricing when historical data provide incomplete coverage of the price space such that some candidate prices, includin

arXiv:2605.21916v1 Announce Type: cross Abstract: Dynamic link prediction is important for modeling evolving interactions in complex systems, including social, communication, financial, and transporta

Gary Marcus expressed concern about what he perceived as extreme desperation among those involved in IPO (Initial Public Offering) markets, characterizing their behavior as the most desperate he had w

arXiv:2605.22711v1 Announce Type: new Abstract: Markov Decision Processes (MDPs) often exhibit significant redundancy due to symmetries and shared structure across state-goal pairs in real-world Goal-

Active Graph is the best, most 'correct' knowledge/context engine I've come across so far (and I've tried or at least researched most of them.) babyagi has ~200 citations, but 0 papers... i just publi

// Adapt the Interface, Not the Model // I am fascinated by the results across my cheap-model-plus-good-harness builds. This new paper also shows good signs of the code-as-agent-harness thesis. The id

arXiv:2605.22275v1 Announce Type: new Abstract: Kernel methods are typically formulated under the assumption of exact, noise-free access to the Gram matrix. However, in emerging settings such as quant

arXiv:2605.21534v1 Announce Type: cross Abstract: Kolmogorov-Arnold Networks (KANs) approximate multivariate functions using learnable univariate edge functions, typically parameterized by B-spline ba

Added a DeepSeek Sparse Attention (DSA) from-scratch implementation to my LLMs-from-scratch repo thanks to an awesome new reader contrib. With motivation, overview, and GPT-style model reference imple

arXiv:2605.22111v1 Announce Type: new Abstract: Accurate modeling of aerodynamic loads is essential for understanding and predicting the responses of complex structural systems. However, these models

Agents shouldn’t have direct visibility into env vars or credentials that can expose sensitive systems and data. Keeping secrets outside the agent’s context helps secure the env while still allowing a

arXiv:2605.21610v1 Announce Type: new Abstract: Antibody design methods condition on antigen structure to generate complementarity-determining regions (CDR), yet a systematic evaluation of baseline me

Latent Space reports on a rebranding or reorganization where Model Labs have been renamed or converted into Agent Labs, reflecting a shift in focus toward AI agent development and capabilities. This c

arXiv:2605.22155v1 Announce Type: new Abstract: Symbolic methods are generally not considered competitive with strong modern learners on realistic supervised tasks. We evaluate Algebraic Machine Learn

arXiv:2511.10619v2 Announce Type: replace Abstract: The improving multi-armed bandits problem is a formal model for allocating effort under uncertainty, motivated by scenarios such as investing resear

arXiv:2605.21646v1 Announce Type: new Abstract: Prototype-based explanations offer an intuitive, example-based approach to support the interpretability of machine learning black box classifiers but of

Also applies to selling b2b saas Spoke with a late-30s girlfriend in Dallas who went on a date last night with a late-50s bachelor from NYC. They were introduced via another matchmaker. She said the v

Gary Marcus humorously describes riding an airport monorail as an example of a geofenced autonomous vehicle, highlighting how existing transportation systems already operate with limited autonomy with

arXiv:2605.22432v1 Announce Type: new Abstract: Modern deep learning commonly relies on AdamW with prescribed learning rate schedules, but recent works challenge both components: Schedule-Free optimiz

an elaboration of the Paul Graham reference: Literally one of the most important essays could read, if you want to have a *productive* disagreements about anything, on X or anywhere else, is @paulg’s

arXiv:2509.09088v3 Announce Type: replace Abstract: We study the Riemannian geometry of the Deep Linear Network (DLN) as a foundation for a thermodynamic description of the learning process. The main

arXiv:2605.21968v1 Announce Type: new Abstract: Optimization is essential in deep learning. The foundational method upon which most optimizers are built is momentum-based stochastic gradient descent.

And just like that, it’s completely VANISHED from the media. A sitting congressman, Ted Lieu, said on the record the Epstein files are being blocked because they show Trump raped and threatened to kil

another of the dudes going after me (Theo) is perhaps paid by OpenAI 🙄 He doesn’t work for them, but he likely has or has had some paid partnership with them, because they’ve invited him onto their ca

arXiv:2605.22222v1 Announce Type: new Abstract: Partial differential equation (PDE) foundation models are pretrained networks that forecast how physical fields like velocity and pressure evolve from a

Natalie Lung / Bloomberg: As the US House probes Airbnb's use of Chinese AI models, CEO Brian Chesky says the company is not sharing data with Chinese firms and uses open-source models — Airbnb Inc. C

arXiv:2605.22372v1 Announce Type: new Abstract: Vision Transformers (ViTs) face severe computational bottlenecks due to the quadratic complexity of self-attention at high resolutions. Existing token r

arXiv:2605.21615v1 Announce Type: cross Abstract: Existing binary corpora typically capture only one or two axes of binary variation: they either provide cross-compiler builds without a temporal axis,

AsymFLUX.2-klein-9B is a pixel-space text-to-image model finetuned from FLUX.2-klein-base-9B using the AsymFlow method. The model is noted for producing sharp textures with strong adherence and compos

arXiv:2605.22416v1 Announce Type: new Abstract: Hybrid language models like Jamba mix attention layers with State Space Models (SSMs), creating two memory cache types with opposite profiles: Key-Value

arXiv:2510.16590v2 Announce Type: replace Abstract: Applications of machine learning in chemistry are often limited by the scarcity and expense of labeled data, restricting traditional supervised meth

arXiv:2512.21132v2 Announce Type: replace-cross Abstract: As large language models (LLMs) see wide adoption in software engineering, the reliable assessment of the correctness and security of LLM-gene

arXiv:2605.22262v1 Announce Type: cross Abstract: Audio context determines which sound components and sources are relevant and which can be perceived as irrelevant (noise) by listeners. For example, t

arXiv:2605.21560v1 Announce Type: new Abstract: Deploying neural networks on microcontroller units (MCUs) is critical for edge intelligence but remains challenging due to tight memory, storage, and co

b9294 is a llama.cpp release that includes improvements to OpenCL kernels for AMD Adreno GPUs, specifically generalizing MoE (Mixture of Experts) kernel implementations. The release provides pre-built

b9296 is a build release of llama.cpp , the C/C++ implementation for efficient large language model inference. As an intermediate build in the llama.cpp release cycle, it likely includes recent bug fi

The search results show information about llama.cpp releases but don't contain specific details about build b9297. Based on the context and numbering (b9297 is a recent build after b9294), b9297 is li

arXiv:2605.22191v1 Announce Type: new Abstract: Bandit convex optimization (BCO) is a fundamental online learning framework with partial feedback, where the learner observes only the loss incurred at

arXiv:2605.22611v1 Announce Type: new Abstract: Antimicrobial stewardship (AMS) is critical in pediatric intensive care units (PICUs), where diagnostic uncertainty often drives broad-spectrum antibiot

arXiv:2603.02938v2 Announce Type: replace Abstract: Graph-based tasks in the zero-shot setting remain a significant challenge due to data scarcity and the inability of traditional Graph Neural Network

arXiv:2605.21820v1 Announce Type: new Abstract: Self-driving laboratories or autonomous experimentation are emerging as transformative platforms for accelerating scientific discovery. Bayesian optimiz