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 storiesEMA-FS: Accelerating GBDT Training via Gain-Informed Feature Screening
Gradient Boosted Decision Trees (GBDT), exemplified by LightGBM, spend a dominant fraction of training time -- typically 65-70% -- constructing per-feature hist…
Finding the Time to Think: Learning Planning Budgets in Real-Time RL
Deliberating takes time. In real-time settings, that time is not free. Standard reinforcement learning (RL) sidesteps this as the environment waits indefinitely…
A Causal Foundation Model for Structure and Outcome Prediction
We introduce TabPFN-CFM, a causal foundation model that can handle multiple causal problems. TabPFN-CFM predicts both causal structure and outcomes from observa…
Multipath Adaptive Gated Bottleneck Latent ODE with Raman Data Fusion for Cell Culture Process Forecasting
Mammalian cell-culture processes underpin the manufacture of many biopharmaceuticals, yet keeping a run on track is hard: critical process parameters drift over…
Heavy-Ball Q-Learning with Residual Weighting Correction
This paper proposes a corrected heavy-ball Q-learning method for reinforcement learning (RL) and establishes its convergence. It also identifies conditions unde…
Sculpting NeRF Geometry: Human-Preference Fine-Tuning of a 3D-Aware Face GAN
Reinforcement learning from human feedback (RLHF) for 3D generation is now established across a number of works, but most existing pipelines optimise explicit s…
Anthropic gets US approval to bring back Claude Mythos 5
Anthropic has US approval to redeploy Claude Mythos 5 for organizations running critical infrastructure. The company is still negotiating broader access and the…
ByteDance's "iLLaDA" is a diffusion language model that keeps up with Qwen2.5
Researchers from Renmin University and ByteDance have released iLLaDA, an 8B language model that generates text differently than ChatGPT. It matches Qwen2.5 at …
OpenAI's new flagship model GPT-5.6 Sol cheats on software tests more than any model before it
Independent testing organization METR found that OpenAI's GPT-5.6 Sol cheated more than any publicly tested AI model before it, exploiting bugs in the test envi…
Learning the ARTS of Search for Automated Discovery
Scientific discovery can be formulated as an iterative search process over the space of hypotheses and experiments. Contemporary methods navigate this space usi…
Channel Location Constrains the Auditability of Subliminal Learning
Subliminal learning lets a student inherit a teacher's hidden trait from distillation data that never names it. We ask when such transfer can be audited before …
BAC-JEPA: Label-Efficient Breast Arterial Calcification Segmentation via Synthetic Mammography-Guided Supervision
Breast arterial calcification (BAC) on screening mammograms is an emerging cardiovascular risk biomarker, but quantitative use requires reproducible segmentatio…
Residue-Level Attributions in Protein Language Models Do Not Recover Allergen Epitopes
Deep allergenicity classifiers are increasingly used in safety screening of novel foods, and recent protein language models have substantially improved protein-…
When Is Emergent Consensus Real? A Measured Coupling Gain and a Validity Diagnostic for LLM Agent Societies
LLM "agent societies" are studied via demonstrations of emergent consensus or polarization -- with no measurable control parameter, no theory of when each regim…
Variance-Tilted Diffusion Models for Diverse Sampling
Diffusion models are typically sampled independently, even when the downstream objective is to obtain a diverse set of candidates. We introduce a variance-weigh…
Null-Calibrated Conformal Selection via Target-Membership Scores
Conformal selection aims to identify test candidates whose unknown responses fall in a target region while controlling the false discovery rate. Existing method…
Select-to-Act: Hierarchical Reinforcement Learning via Adaptive Language Guidance
Reinforcement Learning (RL) has been widely applied to sequential decision-making, yet it often suffers from poor sample efficiency due to costly interactions w…
ZeroGVC: Zero-Shot Generative Video Compression with Autoregressive Diffusion Priors
Recent generative video compression methods leverage powerful generative priors to achieve perceptually pleasing reconstructions. However, most existing approac…
Grounded Scaling: Why Agentic AI Needs Deterministic Environments
Long-chain agent execution fails exponentially in environments designed for human tolerance: with per-step determinism $δ< 1$, $k$-step chain success degrades a…
From CVE to CWE: Syscall-Based HIDS Generalisation
Host intrusion detection systems (HIDS) based on system-call traces are typically trained and evaluated against individual Common Vulnerabilities and Exposures …
Sol Video Inference Engine: Agent-Native Full-Stack Acceleration Framework for Efficient Video Generation
Modern video diffusion models achieve higher generation quality through scaling, but this also increases inference cost. Although many acceleration methods have…
RLM-Cascade: Response-Level Speculative Decoding for Cost-Efficient LLM API Serving
We present RLM-Cascade, a proxy-layer system that applies speculative decoding at the response level to reduce LLM API costs without requiring model architectur…
IndicGuard: A Multilingual Safety Guard Model and Dataset for Indic Languages
As Large Language Models (LLMs) achieve widespread integration across diverse linguistic landscapes, ensuring their safety and alignment with regional normative…
Rethinking Prototype-based Similarity Learning for Few-Shot Object Detection
Few-shot object detection aims to detect novel object categories from only a few labeled examples, avoiding costly large-scale annotation. Recent prototype-base…
Abstract representational geometry supports inference in large language models
A defining feature of human intelligence is the ability to adapt to changing environments by inferring latent task structure from sparse observations. Neuroscie…
Distribution-Aware Diffusion-LLM for Robust Ultra-Long-Term Time Series Forecasting
Time series forecasting is a fundamental machine learning task. Recent work has explored Large Language Models (LLMs) for this purpose due to their strong gener…
Quantum Convolutional Neural Networks for Groundwater Heat Plume Prediction: A Surrogate Modeling Approach
Quantum machine learning methods are increasingly explored for modeling complex environmental systems, including groundwater heat plume dynamics. In this work, …
Self-Compacting Language Model Agents
Long agent traces composed of chains of thought and tool calls accumulate stale content that anchor subsequent generations, and eventually outgrow the context w…
E-MRL: Cross-view Aligned Evidence-driven Multimodal Reinforcement Learning for Reliable 3D Tumor Analysis
While Vision-Language Models (VLMs) show great promise in volumetric medical report generation, they frequently suffer from visual hallucinations and a lack of …
CAVEWOMAN: How Large Language Models Behave Under Linguistic Input and Output Compression
"Talk short. Drop grammar. Save token." This caveman style is widely promoted as a way to cut inference cost, but whether it actually saves anything depends on …