Search: “model-releases”

Claude Sonnet 5 is now available in Devin Desktop and Devin CLI. Sonnet 5 pairs frontier-level coding performance with a more affordable pri…

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Claude Sonnet 5 has been integrated into Devin Desktop and Devin CLI, offering advanced coding capabilities at a more competitive price point than previous models. This release represents an update to

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Claude Sonnet 5 is now available in Perplexity for Pro and Max subscribers. You can also select it as an orchestrator model in Computer.

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Claude Sonnet 5 is now available for use in Perplexity, accessible to Pro and Max tier subscribers. Users can also select Claude Sonnet 5 as an orchestrator model within Perplexity's Computer feature,

model-releasesperplexity--x

30 Jun 2026

Claude Sonnet 5 now available on Vercel AI Gateway

model-releasesvercel-blog

Claude Sonnet 5 is now accessible through Vercel's AI Gateway, enabling developers to integrate Anthropic's latest language model into their applications via Vercel's unified API platform. This integr

CLOSER-VLN: Closed-Loop Self-Verified Retrieval-Augmented Reasoning for Aerial Vision-Language Navigation

arXiv:2606.28397v1 Announce Type: cross Abstract: Vision-language navigation (VLN) has recently advanced with large language and multimodal models, enabling agents to follow natural-language instructi

Closing the Activation-Cone Blind Spot: Response-Time Probing and Unified Defense

arXiv:2606.29441v1 Announce Type: cross Abstract: Inference-time safety methods for large language models have proliferated, yet no systematic comparison exists. We evaluate five defense paradigms (no

CLQT: A Closed-Loop, Cost-Aware, Strategy-Consistent Benchmark for Diagnostic Evaluation of LLM Portfolio-Management Agents

arXiv:2606.29771v1 Announce Type: new Abstract: LLM agents are increasingly cast as autonomous portfolio managers, and benchmarks have moved from financial question-answering to sequential trading. Ye

Cognitive World Models for Process-Level Social Influence Evaluation

arXiv:2606.29495v1 Announce Type: new Abstract: Social influence dialogue changes user behavior by altering internal cognitive states. The central evaluation question is whether the user's beliefs, de

CoGS: Compositional Dynamic Human-Object Scenes Gaussian Splatting from Monocular Video

arXiv:2606.28820v1 Announce Type: new Abstract: Reconstructing dynamic human--object interaction scenes from monocular video is difficult because the human, manipulated object, and background obey dif

COHORT: Collaborative Orchestration for Hardening via Offensive Replay on Emulated Topologies

arXiv:2606.30479v1 Announce Type: cross Abstract: Mitigating an observed adversary in an enterprise network typically takes weeks of expert work: an analyst derives a mitigation tailored to that adver

Collective cooperation without individual fidelity in LLM agents

arXiv:2606.30454v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as agents in simulations of social systems, yet it remains unclear when their behavior can be inter

ComMem: Complementary Memory Systems for Test-Time Adaptation of Vision-Language Models

arXiv:2606.28719v1 Announce Type: new Abstract: Test-time adaptation (TTA) of vision-language models (VLMs) is essential for their robust deployment in dynamic, real-world environments. However, exist

Compositional Dynamics in Learning and Mechanics

arXiv:2606.28984v1 Announce Type: cross Abstract: We give a single compositional setting in which gradient-based learning and Hamiltonian-style mechanics appear as functorial semantics. The syntax is

Compressed Sensing for Capability Localization in Large Language Models

arXiv:2603.03335v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit a wide range of capabilities, including mathematical reasoning, code generation, and linguistic behaviors. We s

Conversational analytics in BigQuery brings trusted agentic reasoning to everyone

model-releasesgoogle-cloud-ai

Businesses run on fast decisions, but the teams who hold the answers are often buried under a backlog of routine requests, leaving users waiting in line for insights they need now. Today, we are bring

Conversational Query Engine for Mixed-Modality Heterogeneous Enterprise Data Sources

arXiv:2606.28370v1 Announce Type: cross Abstract: Enterprise business intelligence queries span structured warehouses and unstructured document repositories -- modalities with fundamentally different

Cool new paper from NVIDIA. Looks like agentic coding is moving into hardware design. HORIZON treats hardware design as repository-level cod…

Cool new paper from NVIDIA. Looks like agentic coding is moving into hardware design. HORIZON treats hardware design as repository-level code evolution. A Markdown harness becomes a project pack with

model-releasesdair-ai--x

Core dump epidemiology: fixing an 18-year-old bug

This article describes OpenAI's investigation and resolution of a longstanding bug in their data infrastructure that had persisted for 18 years, likely related to how core dumps (system memory snapsho

model-releasesopenai

CORTEX: High-Quality Cross-Domain Organization of Web-Scale Corpora through Ontological Corpus Graph

arXiv:2606.30175v1 Announce Type: new Abstract: The continuous evolution of large language models drives escalating demands on data scale and quality, and as different training stages impose increasin

CoSPlan: Corrective Sequential Planning via Scene Graph Incremental Updates

arXiv:2512.10342v3 Announce Type: replace Abstract: Vision Language Models (VLMs) have shown promising planning capabilities, yet their success remains confined to the text domain, leaving visual deci

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

arXiv:2511.02734v3 Announce Type: replace Abstract: Current evaluations of Large Language Model (LLM) agents primarily emphasize task completion, often overlooking resource efficiency and adaptability

Counterfactual Residual Data Augmentation for Regression

arXiv:2606.28460v1 Announce Type: cross Abstract: Data-driven modeling in real-world regression tasks often suffers from limited training samples, high collection costs, and noisy observations. Inspir

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark

arXiv:2606.30027v1 Announce Type: new Abstract: Color Fundus Photography (CFP) offers a low-cost and non-invasive route for ischemic heart disease (IHD) screening, but current studies are limited by s

Cross-Temporal Sinhala OCR: Page-Level Adaptation and Diachronic Analysis

arXiv:2606.29378v1 Announce Type: new Abstract: Sinhala is a morphologically rich abugida spoken by roughly 16 million people in Sri Lanka, and to date, there are no publicly available real-world data

CubifyGS: Object-Centric 3D Gaussian Splatting for Lifelong Dynamic Scene Maintenance

model-releasesarxiv-cs-ro

arXiv:2606.28720v1 Announce Type: new Abstract: Lifelong scene mapping under rigid object rearrangement remains a fundamental challenge in robotics. While 3D Gaussian Splatting (3DGS) enables high-fid

Curvature-Weighted Gradient Diversity: A Noise Measure for Geometry-Adaptive SGD Schedules

model-releasesarxiv-cs-lg

arXiv:2606.30455v1 Announce Type: new Abstract: The standard convergence analysis of mini-batch stochastic gradient descent (SGD) models gradient noise using a single variance term that treats all par

Customized Generative AI Agent for Transportation Engineering Practice: A Development and Continued Pre-training Guideline

arXiv:2606.29014v1 Announce Type: new Abstract: Recent advancements in generative artificial intelligence (AI) and large language models (LLMs) have shown significant promise in automating complex rea

CylindTrack: Depth-Aware Cylindrical Motion Modeling for Panoramic Multi-Object Tracking

arXiv:2606.30097v1 Announce Type: new Abstract: Multi-Object Tracking (MOT) is a core capability for embodied perception, and panoramic cameras are attractive for embodied systems because their 360{eg

Data and Evaluation Closed-Loop for Model Capability Enhancement

arXiv:2606.28471v1 Announce Type: new Abstract: Model capability is the central variable in LLM pre-training, yet is never observed directly: data shapes it prospectively, while evaluation reveals it

Data-Driven Energy-Based Learning via Gibbs Measures on Hierarchical Structures

model-releasesarxiv-cs-lg

arXiv:2606.30064v1 Announce Type: new Abstract: We introduce a data-driven probabilistic framework for learning systems based on Gibbs measures on hierarchical structures. Unlike standard empirical ri

Database Context Compression for Text-to-SQL on Real-World Large Databases

arXiv:2606.28601v1 Announce Type: cross Abstract: Recent progress in Text-to-SQL has been driven by stronger language models and prompting strategies, yet performance on real enterprise benchmarks suc

DataComp-VLM: Improved Open Datasets for Vision-Language Models

arXiv:2606.28551v1 Announce Type: cross Abstract: Building performant Vision-Language Models (VLMs) requires carefully curating large-scale training datasets, yet the community lacks systematic benchm

Defeat Devices in AI Systems

arXiv:2606.28863v1 Announce Type: cross Abstract: AI systems increasingly exhibit behavior that differs systematically between evaluation and deployment contexts. Alignment faking, sandbagging, benchm

Demonstration-Free Robotic Control via LLM Agents

arXiv:2601.20334v2 Announce Type: replace-cross Abstract: Robotic manipulation has increasingly adopted vision-language-action (VLA) models, which achieve strong performance but typically require task

Detecting Clinical Hallucinations in LVLMs via Counterfactual Visual Grounding Uncertainty

arXiv:2606.28520v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) are increasingly used for clinical image understanding, yet they remain vulnerable to hallucinations--producing t

DIA-HARM: Dialectal Disparities in Harmful Content Detection Across 50 English Dialects

arXiv:2604.05318v2 Announce Type: replace Abstract: Harmful content detectors, particularly disinformation classifiers, are predominantly developed and evaluated on Standard American English (SAE), le

Diagnosing and Mitigating Retrieval Bottlenecks in LLM-Based Cold-Start Recommendation

model-releasesarxiv-cs-lg

arXiv:2606.29947v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as rerankers in recommender systems, with the expectation that semantic understanding will help in

DialogPII: A multilingual dataset of synthetic dialog transcripts to detect personal information

arXiv:2606.30312v1 Announce Type: new Abstract: Conversational data collected in domains such as healthcare or social sciences is a valuable resource for research and automated analysis. However, resp

Diff-Based Code Corruption using LLMs for Large-Scale Bugfix Benchmarking

arXiv:2606.29088v1 Announce Type: cross Abstract: There are various benchmarks to evaluate bugfixing capabilities of Large Language Models. However, most widespread benchmarks do not fully reflect rea

Digitizing Coaching Intelligence: An Agentic Framework for Holistic Athlete Profiling using VLM and RAG

arXiv:2606.28570v1 Announce Type: cross Abstract: Athlete assessment is a critical process for tracking physical progress and identifying elite talent. However, during mass recruitment drives, traditi

DiscoGen: Procedural Generation of Algorithm Discovery Tasks in Machine Learning

arXiv:2603.17863v2 Announce Type: replace-cross Abstract: Automating the development of machine learning algorithms has the potential to unlock new breakthroughs. However, our ability to improve and e

DistilledGemma: Balanced Efficiency-Accuracy for Person-Place Relation Extraction from Multilingual Historical Articles

arXiv:2606.29130v1 Announce Type: new Abstract: We present DistilledGemma, an efficient and accurate system for the HIPE-2026 shared task on person-place relation extraction from multilingual historic

Diversity is the Strength of the AI Crowd

arXiv:2606.29661v1 Announce Type: new Abstract: Top AI forecasting systems are approaching superforecaster-level accuracy on future world events, but still rely primarily on off-the-shelf LLMs combine

DLR: Zero-Inference-Cost Latent Residuals for Low-Rank Pre-Training

arXiv:2606.28932v1 Announce Type: cross Abstract: Large language models have driven recent progress in language and multimodal AI, yet pre-training them at scale is prohibitively expensive. Low-rank p

DNA Language Models: An Assessment of Pre-Training for Fine-Tuning Tasks

arXiv:2606.30140v1 Announce Type: cross Abstract: Recent breakthroughs in foundation models and Large Language Models (LLMs) have introduced new opportunities for studying and decoding genomic sequenc

Dockerless: Environment-Free Program Verifier for Coding Agents

arXiv:2606.28436v1 Announce Type: cross Abstract: Program verifiers play a central role in training coding agents, including selecting trajectories for supervised fine-tuning (SFT) and providing rewar

Does Verbose Chain-of-Thought Really Help? In-Distribution Evidence that Content, Not Length, Matters

arXiv:2606.30128v1 Announce Type: new Abstract: Chain-of-thought (CoT) prompting improves LLM reasoning, but the source is contested: do the intermediate steps help because they carry useful semantic

Domain-Informed Multi-View Self-Distillation for Astronomical Light-Curve Representation Learning with JEPA

arXiv:2606.28446v1 Announce Type: cross Abstract: Light curves describe temporal variations in the brightness of celestial objects. Learning robust representations of light curves is essential for lar

DR-GS: Physically-Based Deformable and Relightable 2D Gaussians

arXiv:2606.29379v1 Announce Type: cross Abstract: Gaussian splatting (GS) has garnered significant attention in VR/AR and digital content creation due to its explicit parameterization and efficient re