model releases

What’s new in BigQuery: Powering the Agentic Era

Succeeding in the agentic era requires a transformation in your data strategy: moving from human-scale to agent-first workloads, evolving from reactive intelligence to proactive action, and shifting f

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What’s new in Cloud Run at Next ‘26

DGX agent

From vibe-coded and large-scale apps to AI models and agents, Cloud Run delivers on-demand compute with zero overhead and pay-per-use pricing for all of your workloads. Last year, the number of extern

model-releasesgoogle-cloud-ai

22 Apr 2026

What’s new in GKE at Next ‘26

This week at Google Cloud Next ‘26, we are sharing the evolution of Google Kubernetes Engine (GKE), delivering leading performance, efficiency, security, and scale for your most demanding and complex

What’s new in the Agentic Data Cloud: Powering the System of Action

Companies are shifting from gen AI that simply answers questions to autonomous agents that perceive, reason, and act on their behalf. Attempting to scale these agents on legacy stacks exposes structur

What’s new with compute: Scaling core and agentic workloads

At Google Cloud Next, we’re announcing a range of compute capabilities to enable your core general purpose and AI workloads for the agentic world with higher performance and lower costs. Why it matter

What’s new with the Cross-Cloud Network at Next ‘26

While generative AI sparked a revolution, the true paradigm shift is the rapid evolution from standalone AI models to multi-agent autonomous systems. In this new era, the network transcends basic conn

What’s next in Google AI infrastructure: Scaling for the agentic era

AI is evolving from answering questions to reasoning and taking action. Companies who want to lead in today’s agentic era require computing infrastructure designed and optimized for these new requirem

When and What to Ask: AskBench and Rubric-Guided RLVR for LLM Clarification

arXiv:2602.11199v2 Announce Type: replace Abstract: Large language models (LLMs) often respond even when prompts omit critical details or include misleading information, leading to hallucinations or r

When Safety Fails Before the Answer: Benchmarking Harmful Behavior Detection in Reasoning Chains

arXiv:2604.19001v1 Announce Type: new Abstract: Large reasoning models (LRMs) produce complex, multi-step reasoning traces, yet safety evaluation remains focused on final outputs, overlooking how harm

... which keeps things confusing, since it raises an important new question https://x.com/simonw/status/2046798283700617267

model-releasessimon-willison--x

... which keeps things confusing, since it raises an important new question https://x.com/simonw/status/2046798283700617267 @TheAmolAvasare If I sign up for a new $20/month account today and roll the

Why Does Self-Distillation (Sometimes) Degrade the Reasoning Capability of LLMs?

arXiv:2603.24472v2 Announce Type: replace Abstract: Self-distillation has emerged as an effective post-training paradigm for LLMs, often improving performance while shortening reasoning traces. Howeve

With Gemini Enterprise Agent Platform, Google brings agentic development and control under one roof

model-releasessiliconangle

Google Cloud is taking a massive leap toward building the autonomous enterprise with the launch of the Gemini Enterprise Agent Platform, an evolution of the existing Vertex AI platform that becomes it

Workspace agents can work across tools—pulling context from docs, email, chats, code, and systems, and taking approved actions like updating…

Workspace agents can work across tools—pulling context from docs, email, chats, code, and systems, and taking approved actions like updating @Linear issues, creating docs, or sending messages. In @Sla

model-releasesopenai--x

Wrote up Anthropic's self-own about Claude Code pricing from this afternoon on my blog - it turned out they'd reversed course just as I hit …

model-releasessimon-willison--x

Wrote up Anthropic's self-own about Claude Code pricing from this afternoon on my blog - it turned out they'd reversed course just as I hit publish, so I've tried to update it to reflect the current s

X launches Custom Timelines, a Grok-powered feature letting users pin any of over 75 topics to their home tab, in early access to Premium subscribers on iOS (Nikita Bier/@nikitabier)

Nikita Bier / @nikitabier: X launches Custom Timelines, a Grok-powered feature letting users pin any of over 75 topics to their home tab, in early access to Premium subscribers on iOS — Ladies and gen

model-releasestechmeme

Xiaomi's MiMo-V2.5 and MiMo-V2.5-Pro are both now available in Hermes Agent through Nous Portal and OpenRouter! Just `hermes update`!

model-releasesnous-research--x

Xiaomi's MiMo-V2.5 and MiMo-V2.5-Pro are both now available in Hermes Agent through Nous Portal and OpenRouter! Just `hermes update`! Xiaomi MiMo-V2.5 Series: Pushing Open-Source Agents Forward 🔸 MiMo

Xpertbench: Expert Level Tasks with Rubrics-Based Evaluation

model-releasesarxiv-cs-ai

arXiv:2604.02368v4 Announce Type: replace Abstract: As Large Language Models (LLMs) exhibit plateauing performance on conventional benchmarks, a pivotal challenge persists: evaluating their proficienc

ZC-Swish: Stabilizing Deep BN-Free Networks for Edge and Micro-Batch Applications

arXiv:2604.19453v1 Announce Type: new Abstract: Batch Normalization (BN) is a cornerstone of deep learning, yet it fundamentally breaks down in micro-batch regimes (e.g., 3D medical imaging) and non-I

A Benchmark Study of Segmentation Models and Adaptation Strategies for Landslide Detection from Satellite Imagery

arXiv:2604.16663v1 Announce Type: new Abstract: Landslide detection from high resolution satellite imagery is a critical task for disaster response and risk assessment, yet the relative effectiveness

A Comparative Evaluation of Geometric Accuracy in NeRF and Gaussian Splatting

arXiv:2604.18205v1 Announce Type: new Abstract: Recent advances in neural rendering have introduced numerous 3D scene representations. Although standard computer vision metrics evaluate the visual qua

A Note on TurboQuant and the Earlier DRIVE/EDEN Line of Work

arXiv:2604.18555v1 Announce Type: new Abstract: This note clarifies the relationship between the recent TurboQuant work and the earlier DRIVE (NeurIPS 2021) and EDEN (ICML 2022) schemes. DRIVE is a 1-

A Probabilistic Consensus-Driven Approach for Robust Counterfactual Explanations

arXiv:2604.17494v1 Announce Type: new Abstract: Counterfactual explanations (CFEs) are essential for interpreting black-box models, yet they often become invalid when models are slightly changed. Exis

A Real-World Grasping-in-Clutter Performance Evaluation Benchmark for Robotic Food Waste Sorting

model-releasesarxiv-cs-ro

arXiv:2602.18835v2 Announce Type: replace Abstract: Food waste management is critical for sustainability, yet inorganic contaminants hinder recycling potential. Robotic automation accelerates sorting

A Survey of Spatial Memory Representations for Efficient Robot Navigation

arXiv:2604.16482v1 Announce Type: new Abstract: As vision-based robots navigate larger environments, their spatial memory grows without bound, eventually exhausting computational resources, particular

A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era

arXiv:2604.16586v1 Announce Type: new Abstract: Molecular property prediction integrates quantum chemistry, cheminformatics, and deep learning to connect molecular structure with physicochemical and b

A Transformer and Prototype-based Interpretable Model for Contextual Sarcasm Detection

arXiv:2503.11838v2 Announce Type: replace Abstract: Sarcasm detection, with its figurative nature, poses unique challenges for affective systems designed to perform sentiment analysis. While these sys

Abstain-R1: Calibrated Abstention and Post-Refusal Clarification via Verifiable RL

arXiv:2604.17073v1 Announce Type: new Abstract: Reinforcement fine-tuning improves the reasoning ability of large language models, but it can also encourage them to answer unanswerable queries by gues

Adaptive Forensic Feature Refinement via Intrinsic Importance Perception

arXiv:2604.16879v1 Announce Type: new Abstract: With the rapid development of generative models and multimodal content editing technologies, the key challenge faced by synthetic image detection (SID)

Adaptive Local Frequency Filtering for Fourier-Encoded Implicit Neural Representations

arXiv:2604.02846v2 Announce Type: replace Abstract: Fourier-encoded implicit neural representations (INRs) have shown strong capability in modeling continuous signals from discrete samples. However, c

Adaptive Text Anonymization: Learning Privacy-Utility Trade-offs via Prompt Optimization

arXiv:2602.20743v2 Announce Type: replace Abstract: Anonymizing textual documents is a highly context-sensitive problem: the appropriate balance between privacy protection and utility preservation var

Adversarial Humanities Benchmark: Results on Stylistic Robustness in Frontier Model Safety

arXiv:2604.18487v1 Announce Type: new Abstract: The Adversarial Humanities Benchmark (AHB) evaluates whether model safety refusals survive a shift away from familiar harmful prompt forms. Starting fro

Adverse-to-the-eXtreme Panoptic Segmentation: URVIS 2026 Study and Benchmark

arXiv:2604.16984v1 Announce Type: new Abstract: This paper presents the report of the URVIS 2026 challenge on adverse-to-extreme panoptic segmentation. As the first challenge of its kind, it attracted

AeroRAG: Structured Multimodal Retrieval-Augmented LLM for Fine-Grained Aerial Visual Reasoning

arXiv:2604.17889v1 Announce Type: new Abstract: Despite recent progress in multimodal large language models (MLLMs), reliable visual question answering in aerial scenes remains challenging. In such sc

AeroScene: Progressive Scene Synthesis for Aerial Robotics

model-releasesarxiv-cs-ro

arXiv:2603.23224v2 Announce Type: replace Abstract: Generative models have shown substantial impact across multiple domains, their potential for scene synthesis remains underexplored in robotics. This

After users reported Claude Code appeared to be removed from Anthropic's Pro plan, Anthropic says it's 'running a small test on ~2% of new prosumer signups' (Ed Zitron/Ed Zitron's Where's Your Ed At)

Ed Zitron / Ed Zitron's Where's Your Ed At: After users reported Claude Code appeared to be removed from Anthropic's Pro plan, Anthropic says it's “running a small test on ~2% of new prosumer signups”

model-releasestechmeme

Agentic Large Language Models for Training-Free Neuro-Radiological Image Analysis

arXiv:2604.16729v1 Announce Type: new Abstract: State-of-the-art large language models (LLMs) show high performance in general visual question answering. However, a fundamental limitation remains: cur

Agentic Risk-Aware Set-Based Engineering Design

arXiv:2604.16687v1 Announce Type: cross Abstract: This paper introduces a multi-agent framework guided by Large Language Models (LLMs) to assist in the early stages of engineering design, a phase ofte

AIM 2025 Rip Current Segmentation (RipSeg) Challenge Report

arXiv:2508.13401v3 Announce Type: replace Abstract: This report presents an overview of the AIM 2025 RipSeg Challenge, a competition designed to advance techniques for automatic rip current segmentati

[AINews] Moonshot Kimi K2.6: the world's leading Open Model refreshes to catch up to Opus 4.6 (ahead of DeepSeek v4?)

model-releaseslatent-space

Moonshot's Kimi K2.6 represents a significant update to their open-source language model, positioning it to compete with Anthropic's Claude Opus 4.6 and potentially ahead of DeepSeek v4. The refresh a

Alexandria: A Multi-Domain Dialectal Arabic Machine Translation Dataset for Culturally Inclusive and Linguistically Diverse LLMs

arXiv:2601.13099v2 Announce Type: replace Abstract: Arabic is a highly diglossic language where most daily communication occurs in regional dialects rather than Modern Standard Arabic (MSA). Despite t

Althea: Human-AI Collaboration for Fact-Checking and Critical Reasoning

arXiv:2602.11161v2 Announce Type: replace-cross Abstract: The web's information ecosystem demands fact-checking systems that are both scalable and epistemically trustworthy. Automated approaches offer

An Integrated Deep-Learning Framework for Peptide-Protein Interaction Prediction and Target-Conditioned Peptide Generation with ConGA-PePPI and TC-PepGen

arXiv:2604.18467v1 Announce Type: new Abstract: Motivation: Peptide-protein interactions (PepPIs) are central to cellular regulation and peptide therapeutics, but experimental characterization remains

An Interpretable Framework Applying Protein Words to Predict Protein-Small Molecule Complementary Pairing Rules

arXiv:2604.16550v1 Announce Type: new Abstract: Despite the high accuracy of 'black box' deep learning models, drug discovery still relies on protein-ligand interaction principles and heuristics. To i

An Uncertainty-Aware Loss Function Incorporating Fuzzy Logic: Application to MRI Brain Image Segmentation

arXiv:2604.16490v1 Announce Type: new Abstract: Accurate brain image segmentation, particularly for distinguishing various tissues from magnetic resonance imaging (MRI) images, plays a pivotal role in

AnchorMem: Anchored Facts with Associative Contexts for Building Memory in Large Language Models

arXiv:2604.17377v1 Announce Type: new Abstract: While large language models have achieved remarkable performance in complex tasks, they still need a memory system to utilize historical experience in l

Anthropic gets $5B investment from Amazon, will use it to buy Amazon chips

model-releasesars-technica

Amazon announced a 5 billion investment in Anthropic, with up to 20 billion more tied to commercial milestones. Anthropic committed to spending over $100 billion on AWS technologies over the next deca

AntiPaSTO: Self-Supervised Honesty Steering via Anti-Parallel Representations

arXiv:2601.07473v4 Announce Type: replace Abstract: As models grow more capable, humans cannot reliably verify what they say. Scalable steering requires methods that are internal, self-supervised, and

Are We Using the Right Benchmark: An Evaluation Framework for Visual Token Compression Methods

arXiv:2510.07143v3 Announce Type: replace Abstract: Recent efforts to accelerate inference in Multimodal Large Language Models (MLLMs) have largely focused on visual token compression. The effectivene