model releases

Bridging What the Model Thinks and How It Speaks: Self-Aware Speech Language Models for Expressive Speech Generation

arXiv:2604.11424v1 Announce Type: new Abstract: Speech Language Models (SLMs) exhibit strong semantic understanding, yet their generated speech often sounds flat and fails to convey expressive intent,

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Bringing people together at AI for the Economy Forum

DGX agent

Google hosted its inaugural AI for the Economy Forum in Washington, D.C., co-hosted with MIT FutureTech, bringing together economists, industry leaders, policymakers, and experts to discuss AI's impac

model-releasesgoogle-ai

14 Apr 2026

C-ReD: A Comprehensive Chinese Benchmark for AI-Generated Text Detection Derived from Real-World Prompts

arXiv:2604.11796v1 Announce Type: cross Abstract: Recently, large language models (LLMs) are capable of generating highly fluent textual content. While they offer significant convenience to humans, th

Camyla: Scaling Autonomous Research in Medical Image Segmentation

arXiv:2604.10696v1 Announce Type: new Abstract: We present Camyla, a system for fully autonomous research within the scientific domain of medical image segmentation. Camyla transforms raw datasets int

Can Large Language Models Infer Causal Relationships from Real-World Text?

arXiv:2505.18931v4 Announce Type: replace Abstract: Understanding and inferring causal relationships from texts is a core aspect of human cognition and is essential for advancing large language models

Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance?

arXiv:2511.21998v2 Announce Type: replace Abstract: Multi-modal Large Language Models (LLM) have advanced conversational abilities but struggle with providing live, interactive step-by-step guidance,

CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation

arXiv:2604.10420v1 Announce Type: new Abstract: Large language models (LLMs) enable waveform-to-text ECG interpretation and interactive clinical questioning, yet most ECG-LLM systems still rely on wea

CARINOX: Inference-time Scaling with Category-Aware Reward-based Initial Noise Optimization and Exploration

arXiv:2509.17458v3 Announce Type: replace-cross Abstract: Text-to-image diffusion models, such as Stable Diffusion, can produce high-quality and diverse images but often fail to achieve compositional

CARO: Chain-of-Analogy Reasoning Optimization for Robust Content Moderation

arXiv:2604.10504v1 Announce Type: new Abstract: Current large language models (LLMs), even those explicitly trained for reasoning, often struggle with ambiguous content moderation cases due to mislead

CArtBench: Evaluating Vision-Language Models on Chinese Art Understanding, Interpretation, and Authenticity

arXiv:2604.11632v1 Announce Type: new Abstract: We introduce CARTBENCH, a museum-grounded benchmark for evaluating vision-language models (VLMs) on Chinese artworks beyond short-form recognition and Q

Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models

arXiv:2503.21380v3 Announce Type: replace Abstract: The rapid advancement of large reasoning models has saturated existing math benchmarks, underscoring the urgent need for more challenging evaluation

ChatCLIDS: Simulating Persuasive AI Dialogues to Promote Closed-Loop Insulin Adoption in Type 1 Diabetes Care

arXiv:2509.00891v3 Announce Type: replace Abstract: Real-world adoption of closed-loop insulin delivery systems (CLIDS) in type 1 diabetes remains low, driven not by technical failure, but by diverse

CheeseBench: Evaluating Large Language Models on Rodent Behavioral Neuroscience Paradigms

arXiv:2604.10825v1 Announce Type: new Abstract: We introduce CheeseBench, a benchmark that evaluates large language models (LLMs) on nine classical behavioral neuroscience paradigms (Morris water maze

ChemPro: A Progressive Chemistry Benchmark for Large Language Models

arXiv:2602.03108v3 Announce Type: replace Abstract: We introduce ChemPro, a progressive benchmark with 4100 natural language question-answer pairs in Chemistry, across 4 coherent sections of difficult

Chrome now lets you turn AI prompts into repeatable ‘Skills’

model-releasesthe-verge-ai

Google is launching a new Chrome workflow feature that allows you to reuse your favorite Gemini commands across multiple webpages. Any AI prompts can now be saved as 'Skills' in the Chrome desktop bro

ClaimDB: A Fact Verification Benchmark over Large Structured Data

arXiv:2601.14698v2 Announce Type: replace Abstract: Real-world fact-checking often involves verifying claims grounded in structured data at scale. Despite substantial progress in fact-verification ben

Class-Adaptive Cooperative Perception for Multi-Class LiDAR-based 3D Object Detection in V2X Systems

arXiv:2604.10305v1 Announce Type: cross Abstract: Cooperative perception allows connected vehicles and roadside infrastructure to share sensor observations, creating a fused scene representation beyon

Claude Code Routines are here! In addition to a schedule, you can now trigger templated agents via GitHub event or API – with our infra & yo…

Claude Code Routines are here! In addition to a schedule, you can now trigger templated agents via GitHub event or API – with our infra & your MCP+repos They've changed how we do docs, backlog mainten

model-releasesthariq--x

ClawVM: Harness-Managed Virtual Memory for Stateful Tool-Using LLM Agents

arXiv:2604.10352v1 Announce Type: new Abstract: Stateful tool-using LLM agents treat the context window as working memory, yet today's agent harnesses manage residency and durability as best-effort, c

CLSGen: A Dual-Head Fine-Tuning Framework for Joint Probabilistic Classification and Verbalized Explanation

arXiv:2604.11801v1 Announce Type: new Abstract: With the recent progress of Large Language Models (LLMs), there is a growing interest in applying these models to solve complex and challenging problems

CocoaBench: Evaluating Unified Digital Agents in the Wild

arXiv:2604.11201v1 Announce Type: cross Abstract: LLM agents now perform strongly in software engineering, deep research, GUI automation, and various other applications, while recent agent scaffolds a

CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification

arXiv:2604.01687v2 Announce Type: replace Abstract: Anthropic proposes the concept of skills for LLM agents to tackle multi-step professional tasks that simple tool invocations cannot address. A tool

CoFusion: Multispectral and Hyperspectral Image Fusion via Spectral Coordinate Attention

arXiv:2604.10584v1 Announce Type: new Abstract: Multispectral and Hyperspectral Image Fusion (MHIF) aims to reconstruct high-resolution images by integrating low-resolution hyperspectral images (LRHSI

Comparative Analysis of Large Language Models in Healthcare

arXiv:2604.10316v1 Announce Type: new Abstract: Background: Large Language Models (LLMs) are transforming artificial intelligence applications in healthcare due to their ability to understand, generat

Competing with AI Scientists: Agent-Driven Approach to Astrophysics Research

arXiv:2604.09621v1 Announce Type: new Abstract: We present an agent-driven approach to the construction of parameter inference pipelines for scientific data analysis. Our method leverages a multi-agen

COMPOSITE-Stem

arXiv:2604.09836v1 Announce Type: new Abstract: AI agents hold growing promise for accelerating scientific discovery; yet, a lack of frontier evaluations hinders adoption into real workflows. Expert-w

Computational Lesions in Multilingual Language Models Separate Shared and Language-specific Brain Alignment

arXiv:2604.10627v1 Announce Type: cross Abstract: How the brain supports language across different languages is a basic question in neuroscience and a useful test for multilingual artificial intellige

Concept Drift Guided LayerNorm Tuning for Efficient Multimodal Metaphor Identification

arXiv:2505.11237v3 Announce Type: replace-cross Abstract: Metaphorical imagination, the ability to connect seemingly unrelated concepts, is fundamental to human cognition and communication. While unde

Conflicts Make Large Reasoning Models Vulnerable to Attacks

arXiv:2604.09750v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) have achieved remarkable performance across diverse domains, yet their decision-making under conflicting objectives rema

Consistency of AI-Generated Exercise Prescriptions: A Repeated Generation Study Using a Large Language Model

arXiv:2604.11287v1 Announce Type: new Abstract: Background: Large language models (LLMs) have been explored as tools for generating personalized exercise prescriptions, yet the consistency of outputs

Context-Aware Semantic Segmentation via Stage-Wise Attention

arXiv:2601.11310v2 Announce Type: replace Abstract: Semantic ultra-high-resolution (UHR) image segmentation is essential in remote sensing applications such as aerial mapping and environmental monitor

CounterBench: Evaluating and Improving Counterfactual Reasoning in Large Language Models

arXiv:2502.11008v2 Announce Type: replace Abstract: Counterfactual reasoning is widely recognized as one of the most challenging and intricate aspects of causality in artificial intelligence. In this

Counting to Four is still a Chore for VLMs

arXiv:2604.10039v1 Announce Type: new Abstract: Vision--language models (VLMs) have achieved impressive performance on complex multimodal reasoning tasks, yet they still fail on simple grounding skill

CPAM: Context-Preserving Adaptive Manipulation for Zero-Shot Real Image Editing

arXiv:2506.18438v2 Announce Type: replace Abstract: Editing natural images using textual descriptions in text-to-image diffusion models remains a significant challenge, particularly in achieving consi

CricBench: A Multilingual Benchmark for Evaluating LLMs in Cricket Analytics

arXiv:2512.21877v3 Announce Type: replace-cross Abstract: Cricket is the second most popular sport worldwide, with billions of fans seeking advanced statistical insights unavailable through standard w

Cross-Validated Cross-Channel Self-Attention and Denoising for Automatic Modulation Classification

arXiv:2604.10054v1 Announce Type: new Abstract: This study addresses a key limitation in deep learning Automatic Modulation Classification (AMC) models, which perform well at high signal-to-noise rati

Cybersecurity Looks Like Proof of Work Now

model-releasessimon-willison

Cybersecurity Looks Like Proof of Work Now The UK's AI Safety Institute recently published Our evaluation of Claude Mythos Preview’s cyber capabilities, their own independent analysis of Claude Mythos

Data-Efficient Semantic Segmentation of 3D Point Clouds via Open-Vocabulary Image Segmentation-based Pseudo-Labeling

arXiv:2604.11007v1 Announce Type: new Abstract: Semantic segmentation of 3D point cloud scenes is a crucial task for various applications. In real-world scenarios, training segmentation models often f

datasette PR #2689: Replace token-based CSRF with Sec-Fetch-Site header protection

model-releasessimon-willison

datasette PR #2689: Replace token-based CSRF with Sec-Fetch-Site header protection Datasette has long protected against CSRF attacks using CSRF tokens, implemented using my asgi-csrf Python library. T

DDO-RM for LLM Preference Optimization: A Minimal Held-Out Benchmark against DPO

arXiv:2604.11119v1 Announce Type: cross Abstract: This paper reorganizes the current manuscript around the DPO versus DDO-RM preference-optimization project and focuses on two parts: the algorithmic v

Dead Cognitions: A Census of Misattributed Insights

arXiv:2604.10288v1 Announce Type: new Abstract: This essay identifies a failure mode of AI chat systems that we term attribution laundering: the model performs substantive cognitive work and then rhet

DecepGPT: Schema-Driven Deception Detection with Multicultural Datasets and Robust Multimodal Learning

arXiv:2603.23916v2 Announce Type: replace-cross Abstract: Multimodal deception detection aims to identify deceptive behavior by analyzing audiovisual cues for forensics and security. In these high-sta

Decompose, Mix, Adapt: A Unified Framework for Parameter-Efficient Neural Network Recombination and Compression

arXiv:2603.27383v2 Announce Type: replace Abstract: Parameter Recombination (PR) methods aim to efficiently compose the weights of a neural network for applications like Parameter-Efficient FineTuning

Decomposing and Reducing Hidden Measurement Error in LLM Evaluation Pipelines

arXiv:2604.11581v1 Announce Type: new Abstract: LLM evaluations drive which models get deployed, which safety standards get adopted, and which research conclusions get published. Yet these scores carr

🚀 deepagents 0.5 release 👉 Async subagents - kick off background tasks on any Agent Protocol backed server while you continue to interact …

model-releasesharrison-chase--x

🚀 deepagents 0.5 release 👉 Async subagents - kick off background tasks on any Agent Protocol backed server while you continue to interact with the main agent. Start multiple background tasks in parall

DeepReviewer 2.0: A Traceable Agentic System for Auditable Scientific Peer Review

arXiv:2604.09590v1 Announce Type: new Abstract: Automated peer review is often framed as generating fluent critique, yet reviewers and area chairs need judgments they can audit: where a concern applie

Degradation-Consistent Paired Training for Robust AI-Generated Image Detection

arXiv:2604.10102v1 Announce Type: cross Abstract: AI-generated image detectors suffer significant performance degradation under real-world image corruptions such as JPEG compression, Gaussian blur, an

Delta Rectified Flow Sampling for Text-to-Image Editing

arXiv:2509.05342v3 Announce Type: replace Abstract: We propose Delta Rectified Flow Sampling (DRFS), a novel inversion-free, path-aware editing framework within rectified flow models for text-to-image