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Not All Errors Are Equal: Consequence-Aware Reasoning Compute Allocation

arXiv:2606.04402v1 Announce Type: new Abstract: Modern reasoning models can allocate different amounts of test-time computation, such as thinking tokens, model calls, or compute budget, to different t

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Model Releases

@nvidia @nebiustf More info on the new Nemotron 3 Ultra: https://x.com/NVIDIAAI/status/2062521325076299981?s=20

DGX agent

@nvidia @nebiustf More info on the new Nemotron 3 Ultra: https://x.com/NVIDIAAI/status/2062521325076299981?s=20 Today we're shipping Nemotron 3 Ultra. A 550B MoE frontier-intelligence open model built

model-releasesnous-research--x

4 Jun 2026

@nvidia @nebiustf Setup guide: http://hermes-agent.nousresearch.com/docs/guides/run-nemotron-3-ultra-free Sign up for Nous Portal: http://po…

model-releasesnous-research--x

This is a setup guide for running Nemotron-3 Ultra, NVIDIA's open-source language model, through Nous Research's platform. The guide directs users to sign up for the Nous Portal and access documentati

NVIDIA Nemotron 3 Ultra is on Fireworks, day zero. Nemotron Ultra is an open model for frontier reasoning and orchestration in long-running …

model-releasesfireworks-ai--x

NVIDIA Nemotron 3 Ultra is on Fireworks, day zero. Nemotron Ultra is an open model for frontier reasoning and orchestration in long-running autonomous agents. Think use cases like coding agents, deep

NVIDIA Nemotron 3 Ultra now available on Amazon SageMaker JumpStart

model-releasesaws-ml-blog

The search results primarily discuss the Nemotron 3 Nano Omni model rather than Nemotron 3 Ultra. However, I found a recent NVIDIA blog post reference that indicates Nemotron 3 Ultra is available thro

NVIDIA Nemotron 3 Ultra Powers Faster, More Efficient Reasoning for Long-Running Agents

model-releasesnvidia-developer

NVIDIA's Nemotron 3 Ultra is a 550B-parameter Mixture-of-Experts model with 55B active parameters, optimized for orchestrating complex, long-running agent workflows by combining frontier reasoning and

NVIDIA Nemotron 3.5 Content Safety Now Available on Vultr

Deploy NVIDIA Nemotron 3.5 Content Safety on Vultr Cloud GPU with Day Zero support for multimodal AI moderation, custom policy enforcement, multilingual safety workflows, and scalable enterprise AI go

model-releasesvultr

NVIDIA’s Nemotron 3 Ultra is available on Ollama’s cloud! Try it 👇 Claude Code: ollama launch claude --model nemotron-3-ultra:cloud Hermes …

NVIDIA’s Nemotron 3 Ultra is available on Ollama’s cloud! Try it 👇 Claude Code: ollama launch claude --model nemotron-3-ultra:cloud Hermes Agent: ollama launch hermes --model nemotron-3-ultra:cloud Op

model-releasesollama--x

OckBench: Measuring the Efficiency of LLM Reasoning

arXiv:2511.05722v3 Announce Type: replace-cross Abstract: Large language models (LLMs) such as GPT-5 and Gemini 3 have pushed the frontier of automated reasoning and code generation. Yet current bench

Offroad launches with $7M to automate identity security with AI agents

model-releasessiliconangle

Offroad Inc. launched today with 7 million in funding to build what it calls an agentic identity security team, using artificial intelligence agents to investigate and remediate access risks across hu

ollama run gemma4:12b Gemma 4 12B is updated on Ollama, and available across all platforms! Try it on: Claude Code ollama launch claude --mo…

ollama run gemma4:12b Gemma 4 12B is updated on Ollama, and available across all platforms! Try it on: Claude Code ollama launch claude --model gemma4:12b Hermes Agent ollama launch hermes --model gem

model-releasesollama--x

On the Relationship Between CoCoA and ADMM for Distributed Empirical Risk Minimization

arXiv:2502.00470v3 Announce Type: replace-cross Abstract: Distributed empirical risk minimization (ERM) is often studied through two influential yet seemingly separate families of methods: CoCoA-type

On TV Tokyo’s WBS (@wbs_tvtokyo) tonight I’ll be discussing Sakana AI’s upcoming 1T parameter model project, supported by METI’s GENIAC init…

model-releasesdavid-ha--x

On TV Tokyo’s WBS (@wbs_tvtokyo) tonight I’ll be discussing Sakana AI’s upcoming 1T parameter model project, supported by METI’s GENIAC initiative. We are scaling up to build Japan’s first 1T paramete

Online Skill Learning for Web Agents via State-Grounded Dynamic Retrieval

arXiv:2606.04391v1 Announce Type: new Abstract: Language agents increasingly rely on reusable skills to improve multi-step web automation across related tasks. A growing line of work studies online sk

Optical-Guided Neural Collapse for SAR Few-Shot Class Incremental Learning

arXiv:2606.04528v1 Announce Type: cross Abstract: Few-shot class-incremental learning (FSCIL) in synthetic aperture radar imagery presents unique challenges due to severe data scarcity and SAR-specifi

Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a m…

model-releasesboris-cherny--x

Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor. It’s happening faster than we thought

Our team is at CVPR 2026 if you want to come say hi :)

model-releasesjerry-liu--x

Our team is at CVPR 2026 if you want to come say hi :) We're presenting ParseBench at CVPR 2026! ParseBench is the most comprehensive document understanding benchmark for VLMs. ✅ It contains 2k pages

Outstanding paper on long-horizon agents. (bookmark it) Similar to humans, how do you make agents persist on a difficult task, and how is th…

Outstanding paper on long-horizon agents. (bookmark it) Similar to humans, how do you make agents persist on a difficult task, and how is that useful? And which models today work well on this? This ne

model-releasesdair-ai--x

Parameter-Efficient Fine-Tuning with Learnable Rank

arXiv:2606.04325v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) is a popular parameter-efficient fine-tuning (PEFT) method that restricts weight updates to low-rank adapters, introducing a

PE-MHL: Physics-Encoded Modular Hybrid Layers for Scalable Learning of Complex Systems

arXiv:2606.04290v1 Announce Type: new Abstract: Hybrid models that combine physics-based and data-driven components have shown strong potential for achieving accuracy and interpretability in control a

PersistBench: When Should Long-Term Memories Be Forgotten by LLMs?

arXiv:2602.01146v2 Announce Type: replace Abstract: Conversational assistants are increasingly integrating long-term memory with large language models (LLMs). This persistence of memories, e.g., the u

Physics-Informed Video Generation via Mixture-of-Experts Latent Alignment

arXiv:2606.04737v1 Announce Type: new Abstract: Large-scale video generation models have made remarkable progress in semantic consistency and visual quality, producing videos that are increasingly coh

Plan, Watch, Recover: A Benchmark and Architectures for Proactive Procedural Assistance

arXiv:2606.04970v1 Announce Type: cross Abstract: We envision a proactive multi-modal assistant system which gives users real-time step-by-step guidance on a procedural task, autonomously deciding ext

PoliticsBench: Benchmarking Political Values in Large Language Models with Multi-Turn Roleplay

arXiv:2603.23841v2 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) are increasingly used as primary sources of information, their potential for political bias may impact thei

Prompt-Level Distillation: A Non-Parametric Alternative to Model Fine-Tuning for Efficient Reasoning

arXiv:2602.21103v2 Announce Type: replace Abstract: Advanced reasoning typically requires Chain-of-Thought prompting, which is accurate but incurs prohibitive latency and substantial test-time inferen

Proof-Carrying Agent Actions: Model-Agnostic Runtime Governance for Heterogeneous Agent Systems

arXiv:2606.04104v1 Announce Type: cross Abstract: Agent systems execute through runtimes with very different control points: local coding tools, framework SDKs, managed agent platforms, API gateways,

Provably Reduced Sample Cost in Prior-Guided Hyperparameter Optimization

arXiv:2606.04866v1 Announce Type: new Abstract: Large-scale hyperparameter optimization (HPO) in automated machine learning (AutoML) consumes substantial computational resources, raising growing conce

Pseudospectral Bounds for Transient Amplification in Coupled Gradient Descent

arXiv:2606.04031v1 Announce Type: new Abstract: Coupled gradient descent--where the update of one parameter block depends on another--underlies bilevel optimization, two-time-scale stochastic approxim

Pulled the trigger today and switched 100% of Lindy traffic to DeepSeek v4, churning from Anthropic models. Saves us millions of $ and we're…

model-releasesclem-delangue--x

Pulled the trigger today and switched 100% of Lindy traffic to DeepSeek v4, churning from Anthropic models. Saves us millions of $ and we're actually seeing an *increase* in performance on many core u

QO-Bench: Diagnosing Query-Operator-Preserving Retrieval over Typed Event Tuples

arXiv:2606.04646v1 Announce Type: cross Abstract: Many real-world questions over business, legal, and scientific corpora are natural-language versions of database-style queries over records latent in

QPredSGG: Hybrid Quantum Predicate Learning for Long-Tailed Scene Graph Generation

arXiv:2606.04689v1 Announce Type: cross Abstract: Scene Graph Generation (SGG) requires relational reasoning over objects and their interactions, but performance is often limited by severe long-tail p

Quantum entanglement provides a competitive advantage in adversarial games

arXiv:2603.10289v2 Announce Type: replace-cross Abstract: Whether uniquely quantum resources confer advantages in fully classical, competitive environments remains an open question. Competitive zero-s

QuBLAST: A Framework for Quantizing Large Language Models with Block-Level Compression Approach and Activation Scaling Strategy

arXiv:2606.04620v1 Announce Type: cross Abstract: LLMs have become the state-of-the-art algorithms for solving NLP tasks. However, they typically come at huge computational and memory costs, thus maki

RAMPART: Registry-based Agentic Memory with Priority-Aware Runtime Transformation

arXiv:2606.04628v1 Announce Type: new Abstract: RAMPART is a compile-time memory model and pure in-RAM block registry for LLM-based agents. Context assembly is a programmable runtime operation where c

RAVQ-HoloNet: Rate-Adaptive Vector-Quantized Hologram Compression

arXiv:2511.21035v2 Announce Type: replace Abstract: Holography offers significant potential for AR/VR applications. However, its adoption is limited by the high demand for data compression. Existing d

Reasoning over Boundaries: Enhancing Specification Alignment via Test-time Deliberation

arXiv:2509.14760v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly applied in diverse real-world scenarios, each governed by bespoke behavioral and safety specifications

Revisiting Vul-RAG: Reproducibility and Replicability of RAG-based Vulnerability Detection with Open-Weight Models

arXiv:2606.04739v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong potential for automated software vulnerability detection, particularly in retrieval-augmented generatio

RIDE: An Open Dataset and Benchmark for Train Delay Prediction

arXiv:2606.05070v1 Announce Type: new Abstract: Train delay prediction is an important problem for both passengers and railway operators, yet progress in the field remains difficult to assess due to t

Robotics startup Generalist, which released its GEN-1 model to complete short physical tasks in April, raised 400M led by Radical Ventures at a 2B valuation (Dina Bass/Bloomberg)

Dina Bass / Bloomberg: Robotics startup Generalist, which released its GEN-1 model to complete short physical tasks in April, raised 400M led by Radical Ventures at a 2B valuation — The company raised

model-releasestechmeme

Robust Multi-view Clustering against Imperfect Information

arXiv:2606.04343v1 Announce Type: new Abstract: Real-world multi-view data always suffer from imperfect information problem, where the view-specific observations are absent (i.e., Incomplete Views, IV

Rollout-Level Advantage-Prioritized Experience Replay for GRPO

arXiv:2606.04560v1 Announce Type: cross Abstract: Reinforcement learning from verifiable rewards with GRPO is a standard approach for post-training reasoning LLMs. It remains sample inefficient. Each

Safety by narrow control has shown to fail many times. Need more transparency on the absolute frontier, and openness close behind.

model-releasesclem-delangue--x

Safety by narrow control has shown to fail many times. Need more transparency on the absolute frontier, and openness close behind. I found another API that offers claude-oceanus-v1-p the pricing and t

Safety Under Scaffolding: How Evaluation Conditions Shape Measured Safety

arXiv:2603.10044v2 Announce Type: replace-cross Abstract: A safety score earned on a benchmark need not predict how the same model behaves once it is wrapped in an agentic scaffold the benchmark never

SAM 3D: 3Dfy Anything in Images

arXiv:2511.16624v2 Announce Type: replace-cross Abstract: We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single i

Scaling AI Agents: A Step-by-Step Guide to Deploying ADK on GKE Autopilot

model-releasesgoogle-cloud-ai

While building AI agents locally using Google’s Agent Development Kit (ADK) is an excellent way to prototype, production-ready agents require a robust, scalable infrastructure. For developers looking

Scene-Centric Unsupervised Video Panoptic Segmentation

arXiv:2606.04925v1 Announce Type: new Abstract: Video panoptic segmentation (VPS) aims to jointly detect, segment, and track all objects while partitioning the video into semantically consistent regio

Self-Evolving Deep Research via Joint Generation and Evaluation

arXiv:2606.04507v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become increasingly adopted in daily applications, with deep research standing out as a particularly important capab

Shifting the Breaking Point of Flow Matching for Multi-Instance Editing

arXiv:2602.08749v3 Announce Type: replace Abstract: Flow matching models have recently emerged as an efficient alternative to diffusion, especially for text-guided image generation and editing, offeri