Evaluating commercial multimodal AI for diabetic eye screening and implications for an alternative regulatory pathway - Nature
<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFB5VFJZNjVmR1NTYmdlZXgyOUY3a3dxeFpnMGVuY2hTanlmQ2VGSGl0YnlxWDc0c3o0X0pGR2lMZC00bVZQMTc4ZlIycUg1aFo5YzB3Y1NhVTV2OE1YckYw?oc=5" target="_blank">Evaluating commercial multimodal AI for diabetic eye screening and implications for an alternative regulatory pathway</a> <font color="#6f6f6f">Nature</font>
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Adapting Text LLMs to Speech via Multimodal Depth Up-Scaling
arXiv:2604.00489v1 Announce Type: new Abstract: Adapting pre-trained text Large Language Models (LLMs) into Speech Language Models (Speech LMs) via continual pretraining on speech data is promising, but often degrades the original text capabilities. We propose Multimodal Depth Upscaling, an extension of an emerging strategy in continual LLM pre-training, where new transformer layers are inserted into a frozen text LLM and only the added layers are trained on speech data. Experiments with SmolLM2-360M and SmolLM2-1.7B on 48k hours of English Automatic Speech Recognition (ASR) data show that depth up-scaling achieves ASR comparable to full fine-tuning while causing far less text degradation than both full fine-tuning and Low-Rank Adaptation (LoRA). We further show that incorporating E-Branch
Steering through Time: Blending Longitudinal Data with Simulation to Rethink Human-Autonomous Vehicle Interaction
arXiv:2604.00832v1 Announce Type: new Abstract: As semi-automated vehicles (SAVs) become more common, ensuring effective human-vehicle interaction during control handovers remains a critical safety challenge. Existing studies often rely on single-session simulator experiments or naturalistic driving datasets, which often lack temporal context on drivers' cognitive and physiological states before takeover events. This study introduces a hybrid framework combining longitudinal mobile sensing with high-fidelity driving simulation to examine driver readiness in semi-automated contexts. In a pilot study with 38 participants, we collected 7 days of wearable physiological data and daily surveys on stress, arousal, valence, and sleep quality, followed by an in-lab simulation with scripted takeover
Zhipu AI (02513.HK) Launches First Native Multimodal Coding Foundation Model GLM-5V-Turbo - AASTOCKS.com
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Alibaba rolls out Qwen3.6-Plus with stronger agentic AI and multimodal reasoning - Tech Critter
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[Full Video Replay] Galaxy XR: Merging Multimodal AI With Extended Reality - samsung.com
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Agile Robots And Google Deepmind Partner To Bring Intelligence To Robotics - TradingView
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