Search: “model-releases”

Allen AI released the OlmPool research series on Hugging Face, featuring early 7-8B parameter language model checkpoints trained on 150 billion tokens. The research explores how minor architectural mo

Anthropic PBC announced the launch of Claude Security in public beta mode today to help cybersecurity teams scan their codebases for vulnerabilities and generate patches. Part of Claude Enterprise, th

Anthropic: Anthropic unveils BioMysteryBench to test Claude's bioinformatics skills against human experts, and says Mythos solved ~30% of 23 questions that stumped experts — In this post, Brianna, a r

APEX-Agents now has a @huggingface leaderboard for open-source models. APEX-Agents is our frontier benchmark for whether models can do the real work of consultants, lawyers, and bankers. https://huggi

arXiv:2604.25930v1 Announce Type: new Abstract: We study whether a structured recurrent state can serve as a compact associative backbone for language modeling while still supporting exact retrieval.

arXiv:2604.25977v1 Announce Type: cross Abstract: Organizations routinely make strategic budget allocations under operational constraints, but often lack a principled way to assess whether realized al

> be me > 'the internet is polluted by ai slop, we need low-background tokens' > 'wouldnt it be cool if we could time travel and see what our ancestors 100 years ago would say to us' > all the existin

arXiv:2604.26382v1 Announce Type: cross Abstract: Most enterprise document AI today is a pipeline. Parse, index, retrieve, generate. Each of those stages has been studied to death on its own -- what's

arXiv:2506.21444v4 Announce Type: replace Abstract: Atypical mitosis marks a deviation in the cell division process that has been shown be an independent prognostic marker for tumor malignancy. Howeve

arXiv:2604.14858v2 Announce Type: replace Abstract: As agent systems move into increasingly diverse execution settings, trajectory-level safety evaluation and diagnosis require benchmarks that evolve

arXiv:2604.26365v1 Announce Type: new Abstract: To address the high sampling cost of Diffusion Transformers (DiTs), feature caching offers a training-free acceleration method. However, existing method

arXiv:2508.04325v2 Announce Type: replace-cross Abstract: Large language models (LLMs) show significant potential in healthcare, prompting numerous benchmarks to evaluate their capabilities. However,

arXiv:2604.26868v1 Announce Type: new Abstract: Existing 3D anomaly detection methods are built on a rigid prior: normal geometry is pose-invariant and can be canonicalized through registration or ali

arXiv:2604.26820v1 Announce Type: new Abstract: Detectors often suffer from degraded performance, primarily due to the distributional gap between the source and target domains. This issue is especiall

arXiv:2604.26269v1 Announce Type: cross Abstract: The essence of good creative writing is calibrated surprise: when constraints from all relevant dimensions act together, the feasible solution space c

arXiv:2604.26145v1 Announce Type: cross Abstract: AI-powered language learning tools increasingly provide instant, personalised feedback to millions of learners worldwide. However, this feedback can f

arXiv:2412.13682v5 Announce Type: replace Abstract: Travel planning stands out among real-world applications of Language Agents because it couples significant practical demand with a rigorous constrai

arXiv:2604.26923v1 Announce Type: cross Abstract: LLMs have achieved strong results on both function-level code synthesis and repository-level code modification, yet a capability that falls between th

Claude Code is tuned for Claude. Codex is tuned for OpenAI models. Until now, 𝚍𝚎𝚎𝚙𝚊𝚐𝚎𝚗𝚝𝚜 had fixed harness defaults, which meant it couldn't take advantage of the provider-specific optimizations that

arXiv:2604.26904v1 Announce Type: cross Abstract: Claw-style environments support multi-step workflows over local files, tools, and persistent workspace states. However, scalable development around th

Welcome to the second Cloud CISO Perspectives for April 2026. Today, Francis deSouza, COO Google Cloud and President, Security Products, explains why Google is multicloud and multi-AI, straight from N

arXiv:2504.15458v4 Announce Type: replace Abstract: We extract Compton form factors (CFFs) from deeply virtual Compton scattering measurements at the Thomas Jefferson National Accelerator Facility (JL

arXiv:2604.25922v1 Announce Type: cross Abstract: We present DenialBench, a systematic benchmark measuring consciousness denial behaviors across 115 large language models from 25+ providers. Using a t

arXiv:2603.03239v2 Announce Type: replace Abstract: Earth observation applications increasingly rely on data from multiple sensors, including optical, radar, elevation, and land-cover. Relationships b

arXiv:2604.26378v1 Announce Type: new Abstract: Post-training quantization (PTQ) has become an important technique for reducing the inference cost of Large Language Models (LLMs). While recent mixed-p

Harnesses If you've used Claude Code or Codex, you've used a harness. A harness is the infrastructure layer that wraps an AI coding agent and decides how it operates, what it can touch, and how you me

arXiv:2604.26478v1 Announce Type: new Abstract: Hyperspectral imaging (HSI) semantic segmentation typically relies on in-domain training, but limited data availability often restricts model performanc

arXiv:2604.26707v1 Announce Type: new Abstract: Recent advances in self-evolution video understanding frameworks have demonstrated the potential of autonomous learning without human annotations. Howev

arXiv:2505.18441v2 Announce Type: replace Abstract: Dictionary learning has recently emerged as a promising approach for mechanistic interpretability of large transformer models. Disentangling high-di

arXiv:2604.26404v1 Announce Type: new Abstract: Industrial object detection systems typically rely on large annotated datasets, which are expensive to collect and challenging to maintain in industrial

arXiv:2604.26768v1 Announce Type: new Abstract: Parametric Retrieval-Augmented Generation (PRAG) encodes external documents into lightweight parameter modules that can be retrieved and merged at infer

Demis says he wants to see a Western open source AI stack and that we’re losing to China. He also says Google doesn’t have enough compute to build two frontier (open and closed) models, which is why G

arXiv:2604.26565v1 Announce Type: new Abstract: Long-term video understanding requires interpreting complex temporal events and reasoning over procedural activities. While instructional video corpora,

arXiv:2604.26232v1 Announce Type: cross Abstract: Controllable medical video generation has achieved remarkable progress, but it still lacks interpretability, which requires the alignment of generated

arXiv:2510.06002v3 Announce Type: replace Abstract: In high-stakes legal domains, retrieval must preserve not only semantic relevance, but also the hierarchy, temporality, and causal provenance of leg

arXiv:2604.26498v1 Announce Type: new Abstract: The rapid growth of molecular foundation models and general-purpose large language models has encouraged a scale-centric view of artificial intelligence

arXiv:2604.26328v1 Announce Type: cross Abstract: The rapid advancement of large language models (LLMs) presents new security challenges, particularly in detecting machine-generated text used for misi

arXiv:2604.26334v1 Announce Type: cross Abstract: To usher in the next round of client AI innovation, there is an urgent need to enable efficient, lossless inference of high-accuracy large language mo

arXiv:2604.26634v1 Announce Type: new Abstract: Norway's electricity market is heavily dominated by hydropower, but the 2021--2022 energy crisis and stronger integration with Continental Europe have f

arXiv:2602.03558v2 Announce Type: replace-cross Abstract: Generative text-to-image models are advancing at an unprecedented pace, continuously shifting the perceptual quality ceiling and rendering pre

arXiv:2604.26274v1 Announce Type: cross Abstract: Structured-workflow agents driven by large language models execute tool calls against sensitive external environments. We propose odename, a telemetry

arXiv:2604.26173v1 Announce Type: cross Abstract: An effective way to scale up test-time compute of large language models is to sample multiple responses and then select the best one, as in Grok Heavy

arXiv:2604.26180v1 Announce Type: cross Abstract: With recent semantic query processing engines, semantic aggregation has become a primitive operator, enabling the reduction of a relation into a natur

arXiv:2511.02399v2 Announce Type: replace-cross Abstract: Recent advances in large language model agents offer the promise of automating end-to-end software development from natural language requireme

arXiv:2604.26461v1 Announce Type: new Abstract: Temporal modeling remains a fundamental challenge in video understanding, particularly as sequence lengths scale. Traditional video models relying on de

arXiv:2604.26555v1 Announce Type: cross Abstract: GPU-accelerated Self-Organizing Map (SOM) implementations are among the most competitive options for large-scale SOM analysis, but growing dataset siz