Sharp Monocular View Synthesis in Less Than a Second

Google and Apple have both released emergency security updates to address vulnerabilities that were actively exploited in zero-day attacks. Apple has patched its flagship devices, while Google has updated Chrome to fix a specific vulnerability that was part of these attacks.

OpenAI's ChatGPT has been named the most downloaded free app on the U.S. iOS App Store for 2025, a notable rise from its previous position at number four in 2024. This achievement underscores the app's growing popularity and the increasing reliance on AI-driven applications among users.

Anthropic has integrated its Claude Code programming agent into Slack, currently in beta, allowing developers to manage coding tasks directly within the messaging platform. This integration aims to streamline workflows by enabling task delegation through chat, enhancing productivity for software engineers.

A recent study has introduced differential smoothing as a method to mitigate the diversity collapse often observed in large language models (LLMs) during reinforcement learning fine-tuning. This method aims to enhance both the correctness and diversity of model outputs, addressing a critical issue where outputs lack variety and can lead to diminished performance across tasks.

The introduction of the D³-Predictor presents a significant advancement in dense prediction by addressing the limitations of existing diffusion models, which are hindered by stochastic noise that disrupts fine-grained spatial cues and geometric structure mappings. This new framework reformulates a pretrained diffusion model to eliminate stochasticity, allowing for a more deterministic mapping from images to geometry.

A novel framework for white balance (WB) correction has been proposed, leveraging a perception-inspired Learnable HSI (LHSI) color space. This approach aims to address the limitations of traditional sRGB-based WB editing, which struggles with color constancy in complex lighting conditions due to fixed nonlinear transformations and entangled color channels.

A recent study explores the automated recognition of instructional activities and discourse from multimodal classroom data, utilizing AI-driven analysis of 164 hours of video and 68 lesson transcripts. This research aims to replace manual annotation methods, which are resource-intensive and difficult to scale, with more efficient AI techniques for actionable feedback to educators.

A new study introduces latent-action world models that learn from both action-conditioned and action-free data, addressing the limitations of traditional models that rely heavily on labeled action trajectories. This approach allows for training on large-scale unlabeled trajectories while requiring only a small set of labeled actions.