Knowledge catalogue
arXiv:2610.03825v1 Announce Type: cross Abstract: A benchmark score compares a system output against a reference, and methodological attention falls almost entirely on the first term. We measure the s
arXiv:2603.02348v2 Announce Type: replace Abstract: An agent meets a model as served: through an endpoint with a price card, a shared cache and other tenants, or on whatever hardware a self-hosted mod
arXiv:2610.06213v1 Announce Type: new Abstract: We study the sampling allocation of LinUCB in the small-gap regime, where the reward gaps are of order at most n^{-1/2} over the decision horizon n. Thi
arXiv:2610.04403v1 Announce Type: cross Abstract: Post-training quantization to the GGUF format's mixed-precision K-quants is commonly how open-weight language models reach consumer hardware, yet its
arXiv:2610.06387v1 Announce Type: new Abstract: Large language models (LLMs) have achieved substantial performance gains through increases in model size, training data, and computational resources. Ho
Tool: Scrimshaw Jukebox I wanted to see if Claude Opus 5.5 could compose music, so I tried this: I want you to write some computer game music for me. First design simple text based format for the musi
arXiv:2610.04003v1 Announce Type: cross Abstract: Few-Shot Class-Incremental Learning (FSCIL) requires models to continuously learn new classes from limited samples while retaining prior knowledge, un
arXiv:2610.04269v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed in tool-augmented environments, but their reliance on external inputs makes them highly vuln
arXiv:2610.05141v1 Announce Type: new Abstract: Controlling the camera relative to a moving subject in an existing video is challenging: behaviors such as maintaining a frontal view require the camera
arXiv:2610.06605v1 Announce Type: new Abstract: Transformers asked to multiply multi-digit numbers in a single forward pass often fail, and interpretability studies of pretrained language models find
arXiv:2610.04690v1 Announce Type: cross Abstract: Self-supervised learning (SSL) is standard for speech representation learning, but mainstream models are designed around single-speaker audio, limitin
arXiv:2610.04893v1 Announce Type: new Abstract: Industrial Internet of Things (IIoT) systems generate high-dimensional sensor telemetry from interconnected components, where faults can propagate acros
arXiv:2610.03076v1 Announce Type: cross Abstract: Neural network-based approaches have emerged as efficient alternatives to traditional optimization-based procedures for the calibration of stochastic
Few technology companies can help users to protect and monetize their personal data for artificial intelligence as well as SignSplit PBC, it seems. That explains why it has already secured a massive 1
Mike Wheatley / SiliconANGLE: SignSplit, which offers infrastructure to let people digitally sign datasets, likenesses, and creative works, raised 400M from W Group at a 1B valuation — Few technology
arXiv:2610.06770v1 Announce Type: cross Abstract: Neural solvers for partial differential equations (PDEs) can approach an accurate solution while their parameters grow without bound. In such cases, t
arXiv:2610.04008v1 Announce Type: cross Abstract: Executable Agent Skills combine natural-language instructions and scripts into reusable packages for LLM agents, and revising them requires fixing err
arXiv:2508.01802v2 Announce Type: replace Abstract: Soccer analytics draws on two kinds of information: spatio-temporal data describing where players and the ball are, and event data describing what t
arXiv:2610.05544v1 Announce Type: new Abstract: Real-world deployment of active learning typically forces practitioners to choose an acquisition strategy before any data is labeled. This is a daunting
arXiv:2610.04606v1 Announce Type: new Abstract: We present a 4D Gaussian Splatting framework for the Sparse-View Track of the SIGGRAPH Asia 2026 Volumetric Video Challenge, which requires dynamic scen
arXiv:2610.06413v1 Announce Type: new Abstract: Thinking-enabled vision-language models (VLMs) report ever-higher accuracy on spatial benchmarks, yet final-answer scores cannot reveal whether a correc
arXiv:2610.04413v1 Announce Type: new Abstract: We develop a principled framework for constructing neural networks whose specific parameter realizations admit an explicit algorithmic interpretation. E
arXiv:2610.05664v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) policies increasingly benefit from strong semantic priors provided by large vision-language models (VLMs). However,
arXiv:2610.05977v1 Announce Type: new Abstract: Serving a large language model (LLM) across a fleet of deployments requires several weight-precision operating points. Multi-precision formats serve the
arXiv:2610.04241v1 Announce Type: new Abstract: Fourier Neural Operators (FNOs) offer an efficient paradigm for solving partial differential equations (PDEs). However, FNOs rely on a fixed Fourier bas
For the last few weeks most of my coding has been done locally with Qwen3.8-Flash-Next, so I gave it and Opus 5.5 the same high complexity feature to build on LlamaStash (a complex and large Rust proj
Super excited about this and I know weights are coming (https://huggingface.co/mistralai/Mistral-Large-4.0-1T05-A52B) but just to be fair, you can't be the best open-weight model if you're not open-we
arXiv:2604.01279v2 Announce Type: replace Abstract: We introduce Sven (Singular Value dEsceNt), a new optimization algorithm for neural networks that exploits the natural decomposition of loss functio
We've been building a benchmark out of real concurrency bugs (race conditions, deadlocks, cancellation issues) taken from merged PRs in about 100 Python projects. Each task gets graded by the project'
https://huggingface.co/Dankpaws/Swift1.5-Qwen3.8-Flash-Next-MLX-4.7bpw I've had the 96GB Mac Studio with M5 Ultra for about a week now and wasn't satisfied with the results I was getting from the limi
arXiv:2610.06814v1 Announce Type: new Abstract: World models learn to predict how their environment will evolve, making them an important foundation for general-purpose robotic control. Yet world acti
arXiv:2610.05402v1 Announce Type: new Abstract: A central challenge in continual learning is to acquire new knowledge without forgetting what the model has already learned. This challenge appears in l
That one took some groundwork. Trained and served on our own compute, and RL shows no sign of saturation Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the
The Claude Startups program is expanding to more founders. Members can get a year of Claude Team, API credits, special offers on the tools a startup runs on, and office hours with Anthropic’s Applied
arXiv:2407.21783v3 Announce Type: cross Abstract: Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It i
arXiv:2610.05441v1 Announce Type: cross Abstract: Multiparameter persistent homology is a rapidly developing branch of topological data analysis that improves the robustness of single-parameter persis
arXiv:2610.06610v1 Announce Type: cross Abstract: We study contextual bandits in which a surrogate is observed after the action but before the learner decides whether to acquire the primary outcome th
arXiv:2512.05117v3 Announce Type: replace-cross Abstract: We show that deep neural networks trained across diverse tasks exhibit remarkably similar low-dimensional parametric subspaces. We provide the
arXiv:2507.09200v2 Announce Type: replace Abstract: The rapid proliferation of video in applications such as autonomous driving, surveillance, and sports analytics necessitates robust methods for dyna
arXiv:2610.06156v1 Announce Type: new Abstract: A representation family is a distinct way of extracting features from time series. Ensemble algorithms that combine several representation families rema
arXiv:2610.05182v1 Announce Type: cross Abstract: Infrared image super-resolution is currently led by Mamba-based networks with 26 to 37 million parameters, which are difficult to deploy on the airbor
Today, we are launching a preview of our new model, Mistral Large 4 (ML4), aka le Chonk 🐈. ML4 is a 1T-parameter model with 49B active parameters, trained natively with multimodal capabilities. It is
arXiv:2610.06423v1 Announce Type: new Abstract: Spontaneous movement analysis in preterm infants relies increasingly on markerless pose estimation (PE) to derive clinically relevant motion biomarkers
arXiv:2610.06415v1 Announce Type: new Abstract: Training-free model merging aims to combine multiple fine-tuned models into a single model without further optimization on labeled data. Yet, in transfo
arXiv:2610.04156v1 Announce Type: cross Abstract: LLM agents for clinical text-to-SQL applications reason autonomously over multiple steps but cannot assess whether their own reasoning or outputs can
arXiv:2610.03939v1 Announce Type: new Abstract: Many inference workloads evaluate a trained tree ensemble on row groups that share feature values: discrete-time survival models expand each patient int
arXiv:2610.05684v1 Announce Type: cross Abstract: Modern deep generative models are primarily studied for their ability to generate realistic samples, yet the generative dynamics they learn can also s
arXiv:2610.06744v1 Announce Type: cross Abstract: ufakzeka-karar is an open Turkish decision model with 182,494,466 parameters. Given a Turkish text and questions of a fixed answer type (a choice, a l
arXiv:2610.05932v1 Announce Type: new Abstract: Visual voice cloning requires intelligible, speaker-consistent speech synchronized with visible articulation. However, sequential multimodal conditionin
arXiv:2610.04426v1 Announce Type: cross Abstract: Machine unlearning seeks to remove the influence of designated training data from a trained model without retraining from scratch. Retrain-free method
arXiv:2610.04493v1 Announce Type: cross Abstract: Studying attention through the lens of interacting particle dynamics has shown how token clustering can emerge from the underlying dynamics. We extend
arXiv:2610.04092v1 Announce Type: new Abstract: Generating a boundary representation (B-rep) conditioned on a single image requires faithful reconstruction of geometry, valid topology, and support for
arXiv:2510.01944v2 Announce Type: replace-cross Abstract: We propose a continuous-time formulation of a noisy persistent contrastive divergence (PCD)-like method for maximum likelihood estimation (MLE
arXiv:2610.06831v1 Announce Type: new Abstract: Sliders provide an intuitive interface for continuous image editing. In current generative approaches, however, the slider is simply a rescaling of the
Looks like Unsloth is updating https://huggingface.co/unsloth/Qwen3.8-Flash-Next-GGUF to work with llama.cpp, so hopefully this will resolve the issue of having two different GGUF versions of Qwen Fla
arXiv:2610.06432v1 Announce Type: cross Abstract: Numerous agentic workflows are based on a generator-verifier loop: a generator proposes candidates, a cheap verifier scores them, and the workflow ter
arXiv:2610.05452v1 Announce Type: new Abstract: Accurately estimating judgment reliability is a central challenge in adapting LLM judges to newly verified feedback while preserving previously learned
arXiv:2610.06616v1 Announce Type: new Abstract: The design of a video encoder determines when frames begin to interact and which frame-specific visual evidence remains accessible to the language model
arXiv:2610.04432v1 Announce Type: new Abstract: Building interactive simulators from real-world observations is a promising way to scale embodied data, but current pipelines still rely heavily on manu
arXiv:2610.04911v1 Announce Type: cross Abstract: Existing deep research agents are designed primarily for text- and image-based web sources, while video reasoning systems typically assume that releva