Not All Synthetic Data Is Yours to Learn From
arXiv:2605.31126v1 Announce Type: cross Abstract: Can a language model improve from plain text sampled from itself, with no prompts, no teacher, no verifier, and no reward model? Yes, but only when th
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arXiv:2605.31126v1 Announce Type: cross Abstract: Can a language model improve from plain text sampled from itself, with no prompts, no teacher, no verifier, and no reward model? Yes, but only when th
Not those Matts Create compositing mattes in seconds with Aleph 2.0 Mattes let you isolate a subject from its background so you can composite, color or apply effects to just one part of your shot. 1.
arXiv:2602.21013v2 Announce Type: replace Abstract: Many dexterous manipulation tasks are non-markovian in nature, yet little attention has been paid to this fact in the recent upsurge of the vision-l
arXiv:2605.31116v1 Announce Type: new Abstract: Recent perception-free end-to-end (E2E) autonomous driving methods bypass explicit perception outputs by compressing dense image patch tokens into compa
arXiv:2605.30393v1 Announce Type: cross Abstract: Public numeric benchmarks appear in pretraining, so an evaluation that conditions on a date may be measuring memorized recall rather than out-of-sampl
arXiv:2605.31572v1 Announce Type: new Abstract: Reasoning is essential for autonomous driving (AD) in long-tail scenarios, where vehicles must apply commonsense knowledge, understand spatial relations
The NVIDIA AI Cloud ecosystem is accelerating the global buildout of AI factory infrastructure. Partners are expanding capacity to meet growing demand from enterprises, startups, nations, AI labs and
Nvidia announced development of a 550 billion parameter language model, positioning itself as a leading open-source AI research organization competing with traditional academic and independent labs. T
Nvidia Corp. today introduced a system-on-chip designed to power Windows laptops and compact desktops. RTX Spark, as the processor is called, will roll out alongside Windows upgrades that will make th
NVIDIA DSX OS is an open source, modular software platform designed for operating and scaling multi-tenant AI factories. It provides foundational technologies for building and operating AI factories,
As factories move from isolated automation to plant-wide intelligence, manufacturers need AI systems that can connect live machine signals, quality systems, work instructions and operational alerts in
Not content with just providing the infrastructure for the next generation of artificial intelligence agents, Nvidia Corp. is also providing the tools for developers to build them. At Nvidia GTC Taipe
Maximilian Schreiner / The Decoder: Nvidia launches Nemotron 3 Ultra, a 550B-parameter MoE open model; Artificial Analysis: it's the smartest open US model but trails the Chinese model Kimi K2.6 — It
Personal agents are exploding in popularity, with open source projects like OpenClaw and Hermes seeing rapid adoption by AI developer communities on GitHub. Built to adapt to individual preferences an
Nvidia Corp. said early Monday at the Computex conference in Taipei that it’s gearing up the production of its forthcoming Vera Rubin platform, which is set to become the foundation of a new generatio
Cosmos3-Super-Image2Video is a 64B model for temporally coherent image-to-video generation . NVIDIA's Cosmos platform is designed to accelerate Physical AI development by enabling machines to understa
Cosmos3-Super-Text2Image is a 64 billion parameter omnimodal world model capable of generating high-quality images from text inputs as part of NVIDIA's Cosmos 3 foundation model platform. The model is
NVIDIA Vera is a purpose-built CPU for agentic AI and reinforcement learning, delivering twice the efficiency and 50% faster performance than traditional rack-scale CPUs. The processor helps AI factor
arXiv:2510.07651v2 Announce Type: replace-cross Abstract: Large language models (LLMs) with extended context windows enable powerful applications but impose significant memory overhead, as caching all
arXiv:2605.30778v1 Announce Type: new Abstract: Long-horizon planning for non-prehensile robot manipulation is challenging due to underactuated and discontinuous interactions. We propose a hierarchica
arXiv:2605.06235v2 Announce Type: replace-cross Abstract: Retrieval benchmarks are increasingly saturating, but we argue that efficient search is far from a solved problem. We identify a class of quer
arXiv:2507.05488v2 Announce Type: replace Abstract: We present OLG++, a semantic extension of the Obligation Logic Graph (OLG) for modeling regulatory and legal rules in municipal and interjurisdictio
arXiv:2605.30969v1 Announce Type: new Abstract: Text-based human motion editing aims to modify existing motion sequences according to natural language instructions while maintaining the consistency of
arXiv:2605.30519v1 Announce Type: new Abstract: Autoregressive (AR) video generation extends videos by producing latent chunks sequentially, but scaling to long videos requires repeated access to a gr
arXiv:2605.30544v1 Announce Type: new Abstract: Visual monitoring systems that rely on cloud-based AI inference expose raw image data to external services, creating fundamental tensions with the data-
arXiv:2605.31460v1 Announce Type: new Abstract: Reasoning-based robotic policies using large language and vision-language models achieve strong semantic planning capabilities but mostly suffer from a
arXiv:2605.31500v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) are bottlenecked by sparse, irregular memory access. Popular frameworks such as DGL and PyTorch Geometric support general
arXiv:2605.31090v1 Announce Type: cross Abstract: Mislabeled samples in training datasets severely degrade the performance of deep networks, as overparameterized models tend to memorize erroneous labe
arXiv:2501.12020v2 Announce Type: replace Abstract: Face recognition systems (FRS) exhibit significant accuracy differences based on the user's gender. Since such a gender gap reduces the trustworthin
arXiv:2605.30790v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) supplements a language model's input with retrieved documents, yet most RAG pipelines inherit retrieval component
arXiv:2602.18333v2 Announce Type: replace-cross Abstract: Despite the remarkable practical success of transformer-based language models, recent work has raised concerns about their ability to perform
arXiv:1709.08894v3 Announce Type: replace-cross Abstract: Since their invention, generative adversarial networks (GANs) have become a popular approach for learning to model a distribution of real (unl
arXiv:2605.31518v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) decompose neural network activations into interpretable features, but many learned features never activate, a problem called
arXiv:2605.31142v1 Announce Type: cross Abstract: Large-scale multilingual text embedding models play crucial role in both research and industry, yet their behavior in language-specific, multi-task se
Artificial intelligence adoption has brought hardware back in style, with Dell Technologies Inc. having an astounding week. The hardware firm saw an 88% jump in revenue and its stock closed up at 33%
One of the big reasons for the current lack of patriotism and pride in our nation’s history is that about 40 years ago our most prominent storytellers in Hollywood just basically stopped telling stori
One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organization to help customize solutions, such as building and tunin
This article analyzes the diverging performance trajectories between open-source and closed-source AI models, suggesting they follow different exponential growth curves rather than converging paths. T
Open models! Introducing MiniMax M3: The First Open-Weights Model to Combine Three Frontier Capabilities - Coding & Agentic Frontier: 59.0% SWE-Bench Pro, 66.0% Terminal Bench 2.1, 34.8% SWE-fficiency
OpenAI frontier models and Codex are now generally available on AWS, giving enterprises a new path to build with OpenAI through the AWS environments, controls, and procurement workflows they already u
OpenAI frontier models and Codex are now generally available on AWS, giving enterprises a new way to build on Amazon Bedrock with OpenAI through the security, compliance, and governance workflows they
OpenAI frontier models GPT-5.5 and GPT-5.4, and Codex, the OpenAI coding agent, are now generally available on Amazon Bedrock. AWS customers can access these latest OpenAI models through the same Amaz
arXiv:2605.30792v1 Announce Type: cross Abstract: Speech translation systems increasingly span speech-to-text translation (S2TT), speech-to-speech translation (S2ST), offline translation, and streamin
arXiv:2512.14366v2 Announce Type: replace Abstract: Implicit Neural Representations (INRs) based on vanilla Multi-Layer Perceptrons (MLPs) are widely believed to be incapable of representing high-freq
arXiv:2605.30736v1 Announce Type: cross Abstract: The rapid development of large language models, each with distinct capabilities and inference costs, raises a practical deployment question: given an
arXiv:2506.12060v2 Announce Type: replace-cross Abstract: Cybersecurity organizations are adapting to GenAI integration through modified frameworks and hybrid operational processes, with success influ
OpenAI outlines its positions on AI policy priorities and explains its approach to political engagement and advocacy efforts. The document likely covers key regulatory areas OpenAI supports, such as s
arXiv:2512.00919v2 Announce Type: replace-cross Abstract: We address the problem of causal effect estimation in the presence of hidden confounders using nonparametric instrumental variable (IV) regres
arXiv:2510.10544v3 Announce Type: replace-cross Abstract: We derive a novel PAC-Bayesian generalization bound for reinforcement learning that explicitly accounts for Markov dependencies in the data, t
arXiv:2605.30758v1 Announce Type: new Abstract: Pairwise preference data is widely used in language-model evaluation and alignment, often for model ranking, reward modeling, or preference optimization
Aaron Holmes / The Information: Palo Alto Networks says Mythos found 24+ critical bugs using $1M+ in tokens; Anthropic subsidizes Mythos but some companies plan to boost their Mythos budgets — When Pa
arXiv:2601.22296v2 Announce Type: replace-cross Abstract: Reservoir Computing (RC) has established itself as an efficient paradigm for temporal processing. However, its scalability remains severely co
arXiv:2605.30991v1 Announce Type: cross Abstract: Inference-time reward alignment steers pretrained diffusion and flow-based generative models to satisfy user-specified rewards without retraining. Rec
arXiv:2602.06902v2 Announce Type: replace Abstract: In this paper, we study dynamic regret in unconstrained online convex optimization (OCO) with movement costs. Specifically, we generalize the standa
arXiv:2602.07721v3 Announce Type: replace-cross Abstract: KV-cache retrieval is essential for long-context LLM inference, yet existing methods struggle with distribution drift and high latency at scal
arXiv:2601.11702v3 Announce Type: replace-cross Abstract: AI compliance is becoming increasingly critical as AI systems grow more powerful and pervasive. Yet the rapid expansion of AI policies creates
arXiv:2605.30880v1 Announce Type: cross Abstract: Text-agent environments are typically modeled as partially observable Markov decision processes (POMDPs), assuming that the simulator's latent state a
arXiv:2605.31029v1 Announce Type: new Abstract: Video-language models can process only a limited number of frames, making frame selection a key bottleneck for efficient video captioning. Most captioni
arXiv:2601.13704v3 Announce Type: replace-cross Abstract: In speech machine learning, neural network models are typically designed by choosing an architecture with fixed layer sizes and structure. The
arXiv:2605.31513v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have demonstrated strong general multimodal capability and are increasingly deployed in downstream systems. This tr