Briefing
The fast feed: breaking AI news from the global tech press, deduplicated and time-ordered.
The fast feed: breaking AI news from the global tech press, deduplicated and time-ordered.
Latest in Briefing
30 stories
Half of Claude users say AI can already handle half their work according to Anthropic survey
About half of Claude users say AI can already handle 50 percent or more of their work tasks, according to a survey of roughly 9,700 users by Anthropic. In 12 mo…
Anthropic's Fable 5 could return within days as Trump administration prepares to lift restrictions
Anthropic's AI model, Fable 5, could be available again within days. According to Axios, the Trump administration is close to lifting the restrictions imposed o…
J.P. Morgan sees a pile of red flags in the AI market
J.P. Morgan warns that there are "signs of investor exuberance" in AI markets. Just 42 AI companies in the S&P 500 account for 65 to 80 percent of the inde…
The companies most likely to automate your job are now funding a $1 billion program to retrain you
Former US Commerce Secretary Gina Raimondo has launched "Raise Us," a bipartisan nonprofit to prepare American workers for AI-driven job shifts. Amazon, Anthrop…
Native space based pipelines outperform template space based pipeline in subcortical segmentation
Accurate segmentation of subcortical regions is critical for neurosurgical planning and functional research. Most automated methods rely on template space coreg…
Adversarial Domain Prompt Tuning and Generation for Single Domain Generalization
Single domain generalization (SDG) aims to learn a robust model, which could perform well on many unseen domains while there is only one single domain available…
Training the Orchestrator: A Supervised Approach to End-to-End PDDL Planning with LLM Agents
Translating natural-language planning intent into verified plans is a longstanding challenge: people communicate goals in language, while classical planners req…
Reliability-Guided Adaptive Ensembling for Robust Test-Time Adaptation
Test-time adaptation (TTA) can mitigate domain shift without source data, but it is highly brittle under adversarially contaminated test streams, where corrupte…
Enhancing Road Safety: An IoT-Based Accident Detection and Prevention Mechanism
Road traffic accidents remain a critical global crisis, consistently serving as a primary driver of preventable mortality and severe injury. These incidents are…
Curvature-Adaptive Consistency Flow Matching: Autonomous Trajectory Optimization via Reinforcement Learning
Consistency distillation has significantly accelerated the inference of diffusion models. In this work, we reveal an intriguing asymmetry: while Logit-Normal sa…
Code Isn't Memory: A Structural Codebase Index Inside a Coding Agent
Coding agents now interleave LLMs with retrieval over the working repository, and retrieval implementations vary widely across deployed harnesses. Inside a fixe…
Curvature-aware 3D length estimation of greenhouse cucumbers using RGB-D imaging and cubic spline arc-length integration
Commercial greenhouse cucumber production is graded by fruit length, which drives harvest scheduling, labour allocation, and logistics. Manual measurement with …
Projection-Volume Fidelity Divergence: Diagnosing and Controlling Optimization Drift in Sparse-View 3D Gaussian Tomography
Sparse-view computed tomography is a severely ill-posed inverse problem, where recent 3D Gaussian Splatting methods offer an efficient explicit representation f…
Automated sign detection across the Electronic Babylonian Library: A large-scale dataset and end-to-end cuneiform OCR pipeline
Learning to read cuneiform tablets is an extremely demanding task; consequently, of the roughly half million excavated tablets, only a small fraction has been a…
Federated Learning for Global Carbon Emission Forecasting: A Hybrid Time-Series Approach with Statistical and Neural Models
Climate change, primarily driven by carbon dioxide (CO2) emissions, requires accurate forecasting tools to support effective mitigation policies and sustainable…
4DVLT: Dynamic Scene Understanding with Worldline-Centered Vision-Language Tracking
4D dynamic scene understanding requires grounding language to a persistent worldline that binds identity, metric 3D motion, and synchronized multi-view 2D proje…
Physiology-Aware CNN and Zero-Shot Multimodal LLMs for ECG Image Classification: A Comparative Study
Multimodal large language models (LLMs) are increasingly adopted to interpret 12-lead ECG images, though the interpretations often lack validation. However, ECG…
Scene-agnostic ALS boresight self-calibration
ALS boresight calibration has relied for two decades on dedicated flight patterns over structured scenes containing planar surfaces of varied aspect and slope. …
Autonomous Subsea Cable Search and Tracking with Graph-Optimised Priors and Visual Tracking
Global communications rely on subsea cable infrastructure that remains vulnerable to damage from natural hazards and human activity. Autonomous underwater vehic…
AI Exposure Scores: what they measure, what they miss, and what comes next
A set of exposure scores calculated in 2023 has become a central empirical input to the future of work debate. Produced by Eloundou et al. (2023) and referred t…
Semantic Browsing: Controllable Diversity for Image Generation
Modern text-to-image models excel in visual fidelity and prompt adherence. However, this strict adherence comes at the cost of diversity: generated samples tend…
Breaking the Filter Bubble: A Semantic Pareto-DQN Framework for Multi-Objective Recommendation
Recommender systems often induce filter bubbles and semantic homogenization by monolithically optimizing for immediate user engagement. Standard single-objectiv…
Selective Capability Unlearning in End-to-End Spoken Language Understanding
Modern spoken language understanding (SLU) systems are increasingly deployed in real-world settings, where specific functionalities may need to be removed due t…
Universal Guideline-Driven Image Clustering via a Hybrid LLM Agent
Unifying image clustering across different clustering scenarios remains challenging due to fundamental gaps among tasks. We introduce a Guideline-Driven Image C…
Breaking Shortcut Learning for Cross-Trial EEG-Guided Target Speech Extraction via Two-Stage Training
Recent end-to-end models for EEG-guided target speech extraction report impressive results, underscoring potential for neuro-steered hearing technologies. Howev…
Automated Residual Plot Assessment With the R Package autovi and the Shiny Application autovi.web
Visual assessment of residual plots is a common approach for diagnosing linear models, but it relies on manual evaluation, which does not scale well and can lea…
LLMs Prompted for Legal Context Object More: Overrefusal from Small On-Premises LLMs in Criminal Legal Context
While the validity of LLMs' use in the legal context remains subject to ethical and legal debate, legal professionals are already experimenting with personal LL…
ParaPairAudioBench: Paralinguistic Pairwise Audio Benchmark for LALM-as-a-Judge
Large Audio-Language Models (LALMs) have been widely used as judge models for the automatic evaluation of generated speech. However, prior approaches predominan…
Can Scale Save Us From Plasticity Loss in Large Language Models?
The loss of plasticity - the ability of a network to learn new information after having already learned older information - is a fundamental challenge in creati…
CANDLE: Character-level Arabic Noise Deduplication using Lightweight Encoder
Handling repeated characters in text can be tricky, since they can represent either the correct spelling of a word or informal character elongation often seen i…