b10675
Vulkan: add hoisting support for row IDs and expert count in shaders (#26686) vulkan: add hoisting support for row IDs and expert count in shaders use hoisted row ids in coopmat2 vulkan: address revie
Knowledge catalogue
Vulkan: add hoisting support for row IDs and expert count in shaders (#26686) vulkan: add hoisting support for row IDs and expert count in shaders use hoisted row ids in coopmat2 vulkan: address revie
ggml : fix conv_transpose_2d for multiple batches (#26132) ggml : fix conv_transpose_2d for multiple batches ggml_compute_forward_conv_transpose_2d_impl only computed the first batch (ne[3] of the des
bench: add --tensor-read-lazy (#27881) bench: add --tensor-read-lazy rm the alias rename to LLAMA_LAZY_MODE_* Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestation
arXiv:2601.17173v2 Announce Type: replace-cross Abstract: Question answering systems are typically evaluated on factual correctness, yet many real-world applications-such as education and career guida
arXiv:2504.09409v2 Announce Type: replace-cross Abstract: In this paper, we study nonconvex constrained stochastic zeroth-order optimization problems, for which we have access to exact information of
arXiv:2608.27334v1 Announce Type: new Abstract: Industrial sites contain large volumes of read-only telemetry, but few benchmarks specify how to compile these records into executable multi-turn agent
arXiv:2608.26544v1 Announce Type: new Abstract: We present Chart2SVG, a multimodal large language model that converts static raster charts into structurally organized, semantically enriched SVGs that
arXiv:2608.26192v1 Announce Type: cross Abstract: How documents are segmented into retrievable chunks and how those chunks are embedded strongly affect Retrieval-Augmented Generation (RAG) quality, ye
arXiv:2608.26383v1 Announce Type: new Abstract: Autonomous robots performing laboratory tasks depend on 3D reconstruction pipelines that can turn raw camera streams into actionable object representati
arXiv:2608.27380v1 Announce Type: new Abstract: AI-generated text detection is commonly framed as a binary document-level judgment about whether a text is human-written or machine-generated. This fram
arXiv:2608.26346v1 Announce Type: cross Abstract: We investigate whether AI-generated impulsive sounds can be distinguished from real ones through group delay analysis. Our central finding is that AI-
arXiv:2608.27226v1 Announce Type: new Abstract: We introduce a self-supervised framework for learning joint visuospatial representations from RGB-D observations. While modern vision foundation models
arXiv:2608.26674v1 Announce Type: cross Abstract: As large language models are increasingly deployed to simulate diverse human characters, ensuring persona fidelity, defined as the extent to which an
arXiv:2608.26546v1 Announce Type: new Abstract: Autonomous agents are increasingly adopted to complete complex, multi-tool workflows in real-world settings. However, existing benchmarks typically sepa
arXiv:2608.26556v1 Announce Type: cross Abstract: A looped transformer performs inference by iterating a weight-tied map, making its computation a dynamical process whose cost is set by the resulting
arXiv:2608.26154v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into digital health platforms to generate summaries of complex medical data. Although t
arXiv:2608.26759v1 Announce Type: cross Abstract: Dense warehouses often contain single-lane aisles, dead ends, and tree-like guidepaths that leave little room for idle agents to wait without blocking
arXiv:2608.27384v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are increasingly promising for robotic manipulation, yet their real-world deployment remains bottlenecked by high in
arXiv:2608.26744v1 Announce Type: new Abstract: Zero-shot classification needs efficient label retrieval and fine-grained visual reasoning, yet discriminative and generative vision-language models fai
arXiv:2603.09773v2 Announce Type: replace-cross Abstract: We establish global universal approximation theorems for non-anticipative and general path-dependent functionals on spaces of piecewise linear
arXiv:2608.26585v1 Announce Type: new Abstract: Discrete diffusion models have become a strong, widely adopted class of generators for sequence data, and steering them toward a downstream reward at in
arXiv:2604.02324v2 Announce Type: replace-cross Abstract: Language models (LMs) are increasingly extended with new learnable vocabulary tokens for domain-specific tasks, such as Semantic-ID tokens in
As in actual physical heat. How are people coping with the heat that running a decent inference rig pumps out? I've got dual 5060 Ti GPUs and a relatively modest CPU (Intel 14 Core Ultra 5 245KF Deskt
arXiv:2608.26237v1 Announce Type: cross Abstract: Capture-the-Flag (CTF) benchmarks are widely used to assess the offensive security capabilities of autonomous language-model agents. Evaluations rely
arXiv:2603.18161v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are used by over a billion people globally, most often to assist with writing. In this work, we demonstrate that
I dont know about others, but Nvidia seem to close the lid on older GPUs since they want to push their new technology. Llama and team has been the to go places for older GPUs like V100s. Knowing how N
arXiv:2608.26582v1 Announce Type: cross Abstract: Self-evolving language models have recently emerged as a promising path toward superintelligence, with the advantage of reducing the cost of human sup
Just a rumour of a bug is enough to find a security exploit these days Anil Madhavapeddy is a professor of computer science at Cambridge and a core maintainer of the OCaml compiler. In this somewhat a
just had a quick look at microduck_rl the codebase is very elegant, i’d recommend reading the agent.md since it contains quite a few fun quirks for reward modeling like head tracking too tight impairs
arXiv:2608.27395v1 Announce Type: cross Abstract: Video carries the temporal structure of the physical world, yet learning representations from it has remained computationally expensive: prevailing se
arXiv:2608.27113v1 Announce Type: cross Abstract: Motivated by theoretical problems in deep learning, we conjecture that post-composing a fixed number of pairwise distinct nonconstant polynomials with
arXiv:2608.26925v1 Announce Type: new Abstract: In many low-resource settings, even just eliciting speech for data collection is difficult. One promising approach has been to ask speakers to describe
arXiv:2608.26545v1 Announce Type: new Abstract: Robot policies deployed in the wild should have the capability to continually learn new tasks without forgetting existing behaviors. A common approach t
arXiv:2608.26149v1 Announce Type: new Abstract: Multi-table learning remains a major challenge in machine learning for healthcare and other complex information systems. Relational data combine several
arXiv:2607.10591v2 Announce Type: replace Abstract: Non-binary bottom-up constituency parsing commonly uses arity-specific reductions such as (extsc{Reduce-}X#k), which jointly specify the mother labe
arXiv:2601.20650v3 Announce Type: replace Abstract: Vast-horizon, repetitive workflows are common in daily routines, e.g., processing expense reports from a stack of receipts, organising a collection
Patrick Skinner tweets that the U.S. government is “broken” and urges citizens to reject and denounce what he calls “garbage” and its supporters. He emphasizes collective action as necessary to avoid
arXiv:2608.26180v1 Announce Type: cross Abstract: Shopping assistants are shifting from ranked product lists toward structured decision support, where systems must synthesize shopper context, product
arXiv:2608.26658v1 Announce Type: cross Abstract: Generative retrieval has demonstrated strong performance by directly generating product semantic identifiers (SIDs). Extending this paradigm to image
arXiv:2608.27427v1 Announce Type: cross Abstract: Large language model (LLM) agents in governed organizations must let the persona (instructions, tone, self-presentation) evolve freely, while keeping
arXiv:2608.26549v1 Announce Type: cross Abstract: While Physics-Informed Neural Networks (PINNs) have emerged as a transformative paradigm for solving complex differential equations, their reliance on
arXiv:2504.12588v4 Announce Type: replace-cross Abstract: Transformers have attained outstanding performance across various modalities, owing to their simple but powerful scaled-dot-product (SDP) atte
arXiv:2608.26735v1 Announce Type: new Abstract: Specializing large language models to vertical domains improves domain-specific behavior but often degrades general capabilities such as reasoning, codi
arXiv:2608.27101v1 Announce Type: new Abstract: Ontology learning from text remains challenging despite significant progress in Large Language Models (LLMs), which can hallucinate domain terms, produc
arXiv:2608.27394v1 Announce Type: new Abstract: Retrieved scientific literature can serve as inspiration for both human and AI scientists. Inspiration can take different forms: prior work may directly
arXiv:2608.27358v1 Announce Type: cross Abstract: Influential public discourse shapes public beliefs and can also mislead, not only through what is stated, but also through how information is framed,
Their last version 7.14 was released just a month ago. llama.cpp PR(waiting for approval) for Version 10.0 https://github.com/ggml-org/llama.cpp/pull/27803 Hope this version comes with more boost & im
arXiv:2608.26156v1 Announce Type: new Abstract: Retail intelligence often relies on monitoring popular, high-velocity products, potentially biasing economic indicators by ignoring the 'long tail' of n
arXiv:2608.26437v1 Announce Type: new Abstract: Graph neural networks (GNNs) can exhibit unfair behavior even when sensitive attributes are excluded from node features, because graph topology and mess
arXiv:2608.27282v1 Announce Type: cross Abstract: Most single-stage 3D object detectors complete different tasks with the same extracted features. Nevertheless, it is impossible to project features in
arXiv:2608.26613v1 Announce Type: new Abstract: This study provides a comprehensive benchmarking of conventional machine learning (ML), ensemble learning, deep neural networks, recurrent architectures
Post rédigé avec l'aide de GLM5.3 flash Contexte : formateur professionnel d'adultes en France, j'utilise des agents LLM au quotidien et le français qu'ils produisent est mon critère n°1, avant les be
The interns said they'd work late this week. Our MCP and I are just helping The smart home turned into a hobby. Apps, hubs, connectors that break with every firmware update. You gave the robot vacuum
The most popular use case for Claude Tag by far -- on-call. Learn about how we drive Anthropic's on-call with Tag and set it up yourself so you don't get woken up by an alert at 3am that Claude could
arXiv:2608.27182v1 Announce Type: new Abstract: LLM agents are increasingly applied to anomaly detection and root-cause analysis in time-series observations collected from real-world systems; however,
arXiv:2608.27456v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can interpret a street view, but urban agency depends on whether such local evidence remains useful after the a
arXiv:2608.26155v1 Announce Type: cross Abstract: Multimodal large language models have advanced rapidly, yet most remain English-centric, as scaling multilingual multimodal instruction tuning is limi
arXiv:2608.26895v1 Announce Type: cross Abstract: Agentic recommender systems ground each decision of a large language model (LLM) in a persistent memory of the user, and in existing agents that memor
arXiv:2608.26385v1 Announce Type: cross Abstract: Volume-based accuracy rewards retrieval-augmented generation (RAG) systems for guessing: a system that answers everything outscores one that declines
GLM-5.3 uses the same base model as GLM-5.2 — every gain comes from post-training. Compared with GLM-5.2, it is much better at complex coding and long-horizon tasks: Stronger Coding: GLM-5.3 is the mo