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Fovea-4B is an open-weight 4B vision model that brings Jev-style typed decision contracts to images, leading ImageJev-style tasks with 80.6 chance-corrected accuracy and strong calibration (ECE 0.035), released under Apache-2.0.
A Nature paper introduces EVLF-FM, an 8B-parameter clinical multimodal vision-language foundation model with fine-grain explainability that outperforms clinicians in radiology, dermatology and other medical tasks, showing frontier-level medical intelligence can run without data-center scale compute.
Canva 推出了其首个视觉语言模型 Brush，能够理解设计的布局、图层与风格并协助用户编辑，被视为传统创意平台在 AI 时代自研模型的重要转折点。
inclusionAI 发布了 ZwZ2 系列（27B/9B/4B），基于 Qwen3.6 微调的视觉语言模型，通过 EvidenceConnect 构建的多区域验证数据与 GRPO 训练，在六大领域 25 个基准上均超越基座模型，总体准确率从 55.52 提升至 60.51（+4.99）。
Canva 推出了其首个视觉语言模型 Brush，能够理解设计的布局、图层与风格，并协助用户进行文本修改、整套演示文稿重设计以及从空白页面生成设计。
Canva Research launched Canva Brush, a vision-language model that edits designs by understanding their structure, delivering claims of up to 69% faster and 46% cheaper edits while keeping everything fully editable. It is now powering Canva AI design edits for Canva Pro subscribers.
A 2B vision-language model, LFM3-VL-2B, boxed 62,873 pools across 16,692 aerial tiles of the San Fernando Valley in 5.5 hours on a single RTX 3060 with zero fine-tuning, scoring 77.3 on visual grounding versus 68.3 for LFM2.5-VL-3B.
LFM3-VL-2B 视觉语言模型可在浏览器中通过 WebGPU 本地实时进行视频字幕生成，LiquidAI 还发布了对应的 Hugging Face 模型集合与在线演示。
Maxime Labonne shares a playful demo of a newly trained multimodal model supporting bounding box detection alongside other questions in a single forward pass, credited to Aurélien Lac.
Psi-0.6 is a unified vision-language world model that adaptively composes perception, language, geometry, and simulation via 'streams of thought', achieving zero-shot gains on multi-view spatial reasoning and supporting counterfactual simulation optimized with RL from task feedback.
DriveMind 是一个基于多模态大模型的自动驾驶框架，借鉴粒子滤波思想维护并更新多个场景假设，在 Bench2Drive 上将驾驶分数从 68.50 提升至 81.37，在无信号交叉口等歧义场景中提升尤为显著。
RoboJev-27B is an open-weight vision-language judge that predicts robot manipulation success from video frames, achieving 95.2% balanced accuracy on the SO-101 robot and strong generalization across unseen labs and robots, with inference code and full evaluation data released.
Jerry Liu 宣布发布 OCRia-1，一款面向文档解析的前沿 VLM，在准确率、成本和延迟上均达到新的 SOTA，并在 ParseBench 及多个第三方基准上取得领先成绩。
该论文提出 RadCarve 方法，将放射学报告的生成单元直接定义为解剖区域集合，通过组成特化的查询库联合预测单元存在与区域构成，在 Chest ImaGenome 和 PadChest-GR 上以不到大模型六分之一的参数量取得领先的报告生成性能。
WeVisOne-VL (WeChat Vision All-in-One) 是一个统一对象级与像素级视觉感知的视觉语言模型，通过结构化 token 预测与轻量像素解码器支持检测、定位、计数、OCR、分割和抠像等任务，在30多个基准上取得领先性能，并已开源 2B/4B 模型。
OvisOCR3 is a compact 0.8B vision-language model that unifies document parsing, general OCR, key information extraction, figure captioning, and cross-page table reconstruction via multi-teacher on-policy distillation and mixed-task reinforcement learning, achieving state-of-the-art results on benchmarks like OmniDocBench v1.6, OCRBench v2, and PureDocBench.
Liquid AI 发布 LFM3-VL-2B，一款面向端侧视觉理解的 1.92B 视觉语言模型，支持文本、图像和视频输入，并引入视频理解、逐步思考以及空间与具身推理能力。
The author benchmarks Nemotron 3.5 Super VL on obscure knowledge (Anno 1602 game rules, no websearch allowed) and finds it far more accurate than GPT-OSS, Qwen, DeepSeek, and Gemma models, making it a solid local model to keep.
HOLI-WORLD 是一个集成生态系统，利用以自我为中心的录像自动化构建大规模学习资源，以提升机器对动态场景与交互的理解，并发布 HOLIWORLD-VL-4B 模型及 HOLIWORLD-Bench 评测基准。
The tweet introduces Glimpse, a new large model focused on visual understanding and reasoning, which claims to natively understand the positions and spatial relationships of elements in images and videos—unlike GPT and Claude, which rely on frame sampling—and expresses anticipation for more real-world evaluations.