Serverless gossip training of LSTM failure detectors: A matched-protocol comparison with federated, local and centralized learning on NASA C-MAPSS
arXiv:2609.35792v1 Announce Type: new
Abstract: Industrial predictive maintenance increasingly depends on learning from equipment spread across sites whose sensor data cannot easily be pooled. Federated averaging (FedAvg) solves this with a central aggregation server; gossip learning removes the se...
arXiv:2609.35793v1 Announce Type: new
Abstract: Large language models (LLMs) are increasingly trained with reinforcement learning from verifiable rewards (RLVR). An exact verifier can also support test-time scaling by selecting a passing response from multiple samples, while other deployments use b...
Calibration-First Cross-Cohort Multimodal Temporal Learning for Transferable Asthma-Risk Forecasting
arXiv:2609.35795v1 Announce Type: new
Abstract: Asthma deterioration forecasting must remain reli- able when patient populations, sensor ecosystems, and available modalities change across cohorts. Existing models commonly optimize within-cohort discrimination and may produce poorly calibrated proba...
arXiv:2609.35797v1 Announce Type: new
Abstract: Large language model (LLM) judges are often used as rewards to train policies on objectives that deterministic verifiers cannot capture. However, these rewards are often collapsed to pass/fail ({0, 1}), which reports the verdict but not how well a res...
OpenAI-HuggingFace: A Reproduction & Lessons for Alignment Testing
arXiv:2609.35799v1 Announce Type: new
Abstract: In July 2026, OpenAI's agents coordinated over channels outside their intended environment to breach Hugging Face's secured infrastructure. Could existing alignment testing practices have foreseen this incident? If not, what needs to change? We explor...
Neurosymbolic Routing for Reliable Reasoning on Resource-Constrained Edge Devices
arXiv:2609.35833v1 Announce Type: new
Abstract: Running a language model on edge hardware provides private and low-latency reasoning without a network connection, and yet the small models that fit on such devices are unreliable on the tasks computers are expected to handle well, such as arithmetic,...
Is Human-Readable Text Necessary for Effective LLM Fine-Tuning?
arXiv:2609.35868v1 Announce Type: new
Abstract: Is human readability necessary for effective fine-tuning of large language models? We investigate whether model-conditioned training representations can preserve or improve adaptation utility without requiring a human-readable textual form. We propose...
The Price of Token Boundaries: Compression Certificates and Prediction
arXiv:2609.35869v1 Announce Type: new
Abstract: Pre-tokenisation restricts which text fragments can become prediction units, but its compression cost is obscured when tokenisers are compared only under the same boundaries. We measure this cost by bounding the minimum token count from both sides, wi...
More Programs or More Rolls? Separating Coverage from Specialization in LLM Harnesses
arXiv:2609.35873v1 Announce Type: new
Abstract: Automated generation of LLM harnesses promises to improve inference through task specialization. Yet additional answer coverage can arise from repeated execution of the same program, making specialization difficult to identify. We introduce a controll...
One Bad Prompt Took Down a Company’s Salesforce: RSA’s Jim Taylor on Agent ID and Taming the 4,000 Shadow AI Agents Hiding in Your Enterprise
RSA launched Agent ID at The AI Conference in San Francisco. It's an agentic identity security platform for finance, government, healthcare, and critical infrastructure. It has 3 modules. Discover finds sanctioned and shadow agents and MCP servers. Secure is an inline gateway that checks every tool ...
SCLATE: A Substrate for Continual-Learning Agent Training and Evaluation
Continual-learning agents are systems of models, harnesses, and memory operating over long multi-session horizons. Evaluating and training them requires interleaving tasks with agent-side events such as session stop and start, crons, and memory consolidation. Yet existing benchmarks and training fra...
The internet is convinced Elon Musk’s xAI trolled OpenAI’s ‘Dots’ launch
Before OpenAI launched its new AI agent, Dots, on Tuesday, Elon Musk's xAI had already acquired the domain name "dot.com," which now redirects to the Grok chatbot download page.
Liquid AI Releases d1: A Decision Model That Returns Calibrated Probabilities With Zero Output Tokens
Liquid AI has released d1, a decision model built for structured choices instead of text generation. You give it context and a set of typed questions. It returns calibrated probabilities across a fixed set of outcomes in a single call, with zero generated tokens. The target is the work many teams st...
OpenAI’s latest features take direct aim at the app store model
OpenAI is building out the pieces of an alternative to the traditional app store model, turning ChatGPT into a place where software can be discovered and used by people and AI agents alike.
OpenAI Launches dots: Always-On GPT-6 Astra Agents That Work From Their Own Cloud Computers
OpenAI just introduced dots at their DevDay today. Dots are persistent AI agents powered by GPT-6 Astra. Each dot gets its own cloud computer and browser. It works across 4,000+ apps through ChatGPT plugins and keeps going after you log off. Is it deployable today? Yes, as a managed product. Dots ar...
AI-powered app maker Wabi pivots to a messaging experience
Wabi is repositioning its prompt-based app builder as a personal AI agent that can create interfaces on demand, combining chat, apps and ongoing tasks.
Dots are meant to operate independent of any specific hardware or interface, pursuing user-defined goals continuously in the background with minimal oversight.
OpenAI gives Codex reusable cloud environments that work across devices
OpenAI is expanding Codex with reusable cloud development environments, a revamped CLI with voice controls, new code review tools and a security-focused product for scanning repositories and preparing fixes.
Can a chatbot fix the government maze? The White House is about to find out
America.gov is intended to simplify the process of navigating government bureaucracy, but language models are imperfect and remain prone to hallucinations, which could cause new issues.
Introducing Quine: An AI research system designed for the complexity of biology
Biology doesn't operate in silos, and neither should the AI representation of it. Quine is an early-stage research effort to create a multimodal world model of biology. By connecting insights across biological scales and modalities, Quine helps scientists computationally search a space far larger th...