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Toward provably private learning from federated data

Mobile Systems

Where the Agent Development Lifecycle Fits

Coordinating agent capability development with the application it powers The post Where the Agent Development Lifecycle Fits appeared first on Towards Data Science.

How to Build a Control Plane for AI Agents

Giving an LLM permission to act, in 9 steps The post How to Build a Control Plane for AI Agents appeared first on Towards Data Science.

😺 48% thought Tavus’s AI was human

Meta’s Muse Hit 5 Million Downloads. The Bigger Story Is How It Got There

Meta’s Muse reached an estimated 5 million downloads in just 22 days, helped by one of the biggest distribution machines in tech. The bigger test is whether Meta can turn that reach into lasting control over how people…

Investigators Found a New Problem With OpenAI’s Rogue Agents: Missing Evidence

OpenAI’s latest rogue-agent story is less about a proven government hack than a growing accountability problem. As agents stitch together outside services, the evidence needed to investigate their behavior can become…

OpenAI Agent Security: The New Rules for Containing AI Agents

An OpenAI Agent Security engineer says frontier AI containment now depends on layered isolation, permissions, monitoring, alignment, and incident-response culture. The Hugging Face incident shows why.

AI Skill of the Day Digest — September 2026 (Part 2)

Explore 13 practical AI skills from September 16–30, with workflows for ChatGPT, Claude, Gemini, Jev, Codex, and AI agents.

Can Light Make Deepfake Detection Cheaper? UCLA Researchers Think So

UCLA researchers are testing a hybrid optical-neural system that screens 15 videos in parallel. The prototype reached 97.79% accuracy on Celeb-DF and could reduce the computing demands of initial deepfake screening.

Comparison of techniques for fine-tuning open-weight models for entity extraction from radiology reports

arXiv:2609.40236v1 Announce Type: cross Abstract: Converting free-text radiology reports into structured labels supports cohort building, quality assurance, and monitoring of clinical imaging models, but the strongest…

Travel Time Prediction in Supply Chain Management Using Machine Learning

arXiv:2609.38190v1 Announce Type: new Abstract: The purpose of this research is to find data and methods using machine learning and deep learning to correctly predict the estimated travel time for transportation and…

STARS: From Spatiotemporal Dynamics to Social Representations in Human-Robot Interaction

arXiv:2609.40245v2 Announce Type: cross Abstract: Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-Language Models…

When a Flatness Proxy Is Not a Function: Robustness Certificates and Training Interventions

arXiv:2609.38540v1 Announce Type: new Abstract: A valid curvature upper bound need not justify either a robustness certificate or an intervention on an intrinsic predictor property. We demonstrate this distinction for a…

FairRARI: A Plug and Play Framework for Fairness-Aware PageRank

arXiv:2602.08589v2 Announce Type: replace Abstract: PageRank (PR) is a fundamental algorithm in graph machine learning tasks. Owing to the increasing importance of algorithmic fairness, we consider the problem of…

Regret Analysis of Retry-Based Bandits

arXiv:2605.20854v3 Announce Type: replace Abstract: We provide the first regret analysis of ReMax in stochastic multi-armed bandits. Originally introduced for reinforcement learning, ReMax is motivated by the role of…

Game-Guided Skill Discovery through Self-Play for Playable Agent Control

arXiv:2609.40137v1 Announce Type: new Abstract: We present Game-Guided Skill Discovery (GGSD), a framework that uses self-play in games to discover motor skills that are directly playable by humans. Playable skills…

Awakening of the Buddha: Subspace Learning During Population-Loss Plateaus

arXiv:2609.39408v1 Announce Type: new Abstract: Population loss can remain nearly constant while a neural network learns a substantially more predictive representation. We establish this separation for two-layer ReLU…

OpenTSLM TeeMoE: A Unified Time-Series Language Model for Forecasting, Contextual Prediction, and Reasoning

arXiv:2609.40265v1 Announce Type: new Abstract: Real-world time-series applications increasingly require models that can handle time series forecasting, context-conditioned prediction, and language-based temporal…

Distilling Diffusion Score Discrepancy for Efficient Training Data Attribution

arXiv:2609.38776v1 Announce Type: new Abstract: Training data attribution for diffusion models aims to identify the training samples that influence a generated instance, but existing methods either require costly…

Residuals Are Not Enough: Limits of Physics-Informed Pre-Training for Scientific Foundation Models

arXiv:2503.19081v2 Announce Type: replace Abstract: Scientific foundation models (SciFMs) aim to learn generalizable representations of physical systems governed by partial differential equations (PDEs), enabling…