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arXiv:2506.11067v3 Announce Type: replace Abstract: Objective: Develop a cost-effective, large language model (LLM)-based pipeline for automatically extracting Review of Systems (ROS) entities from cl

Todd Spangler / Variety: A look at Matthew McConaughey's novel legal strategy to fight unauthorized AI use of his image and likeness, by trademarking video and audio clips of himself — The actor has s

A milestone for Pearl Research Labs: our first major enterprise partnership is live with Together AI. @togethercompute’s inference platform is an ideal demonstration of @prlnet's value proposition — O

arXiv:2602.24273v3 Announce Type: replace Abstract: We propose a minimal agentic baseline that enables systematic comparison across different AI-based theorem prover architectures. This design impleme

arXiv:2605.14917v1 Announce Type: new Abstract: Active learning for continuous regression has lacked an acquisition function that targets epistemic uncertainty when the predictive distribution is mult

A new @bgurley blog post! I have been thinking about how sophisticated executives are using open source in super creative ways. Started writing this three years ago. Excited to finish it up and publis

arXiv:2511.05159v2 Announce Type: replace-cross Abstract: Convex clustering is a well-regarded clustering method, resembling the similar centroid-based approach of Lloyd's k-means, without requiring a

Preview a new personal finance experience in ChatGPT for Pro users in the U.S. Securely connect your financial accounts and get AI-powered insights and guidance grounded in your financial context, goa

A new set of open-weight models is topping the leaderboard for document understanding 🔥 INF just released two models: Infinity-Parser2-Pro (35B) and Infinity-Parser2-Flash (2B) that top our @huggingfa

arXiv:2605.13905v1 Announce Type: cross Abstract: Drug development and pharmacovigilance are frequently bottlenecked by legacy clinical reporting pipelines. These monolithic systems encode regulatory-

arXiv:2605.14860v1 Announce Type: cross Abstract: Training deep neural networks at scale can benefit from domain decomposition, where the network is split into subdomains trained in parallel and coupl

arXiv:2605.14489v1 Announce Type: new Abstract: Building black-box models for dynamical systems from data is a challenging problem in machine learning, especially when asymptotic stability guarantees

arXiv:2605.14581v1 Announce Type: cross Abstract: Visual RAG has offered an alternative to traditional RAG. It treats documents as images and uses vision encoders to obtain vision patch tokens. Howeve

arXiv:2605.14426v1 Announce Type: cross Abstract: Reliable precipitation monitoring is essential for disaster risk reduction, water resources management, and agricultural decision-making. Multi-source

A preview for Pro users: a new personal finance experience in ChatGPT. Pro users in the U.S. can securely connect financial accounts, see where their money is going, and ask questions based on the inf

arXiv:2511.18739v2 Announce Type: replace Abstract: Time series anomaly detection is widely used in IoT and cyber-physical systems, yet its evaluation remains challenging due to diverse application ob

Rebecca Bellan / TechCrunch: A profile of AI video generation startup Runway, which is training models directly on observational data, is now valued at 5.3B, and added 40M in ARR in Q2 — Every major A

Bloomberg: A profile of Amazon CEO Andy Jassy, who is killing projects, cutting staff, and pleasing Wall Street, while steering the company toward an AI-focused era — Thirteen miles north of Jackson,

arXiv:2605.15049v1 Announce Type: new Abstract: This paper presents a prototyping framework for distributed control of multi-robot systems, aimed at bridging theory and practical testing of distribute

arXiv:2605.13916v1 Announce Type: cross Abstract: Online Multiple Testing (OMT), a fundamental pillar of sequential statistical inference, traditionally evaluates the False Discovery Rate (FDR) and st

arXiv:2603.27517v3 Announce Type: replace-cross Abstract: AI agent frameworks connecting large language model (LLM) reasoning to host execution surfaces -- shell, filesystem, containers, and messaging

arXiv:2605.13913v1 Announce Type: cross Abstract: Deep neural networks generalize well despite being heavily overparameterized, in apparent contradiction with classical learning theory based on unifor

arXiv:2605.14147v1 Announce Type: new Abstract: Objective: The primary goal of this study was to systematically examine the impact of commonly used imbalance handling methods (IHMs) on predictive perf

arXiv:2510.19973v4 Announce Type: replace-cross Abstract: The path to higher network autonomy in 6G lies beyond the mere optimization of key performance indicators (KPIs), requiring systems that perce

arXiv:2605.13850v1 Announce Type: new Abstract: Existing frameworks for LLM-based agent architectures describe systems from a single perspective: industry guides (Anthropic, Google, LangChain) focus o

arXiv:2605.13943v1 Announce Type: new Abstract: Contrastive learning (CL) aims to preserve relational structure between samples by learning representations that reflect a similarity graph. Yet, the ge

arXiv:2605.14416v1 Announce Type: new Abstract: The Capacitated Vehicle Routing Problem (CVRP) is a fundamental NP-hard problem with broad applications in logistics and transportation. Real-world CVRP

arXiv:2512.03637v2 Announce Type: replace-cross Abstract: Transformer-based audio self-supervised learning (SSL) models commonly use spectrograms, vision-style Transformers, and masked modeling object

arXiv:2602.05319v3 Announce Type: replace Abstract: Sequential probabilistic inference from streaming observations requires modeling distributions over future trajectories as new observations arrive.

arXiv:2605.14948v1 Announce Type: new Abstract: State-of-the-art diffusion models often rely on parameter-efficient fine-tuning to perform specialized image editing tasks. However, real-world applicat

arXiv:2512.11855v2 Announce Type: replace-cross Abstract: Enforcing exact symmetry in machine learning models often yields significant gains in scientific applications, serving as a powerful inductive

arXiv:2605.14246v1 Announce Type: cross Abstract: Many safety-critical control problems are modeled as risk-sensitive partially observable Markov decision processes, where the controller must make dec

arXiv:2605.14631v1 Announce Type: cross Abstract: We introduce Action-Inspired Generative Models (AGMs), a dual-network generative framework motivated by the observation that existing bridge-matching

arXiv:2605.14236v1 Announce Type: cross Abstract: Pairwise Ranking Prompting (PRP) elicits pairwise preference judgments from an LLM, which are then aggregated into a ranking, usually via classical so

arXiv:2506.04646v4 Announce Type: replace-cross Abstract: Planning with learned dynamics models offers a promising approach toward versatile real-world manipulation, particularly in nonprehensile sett

arXiv:2605.14741v1 Announce Type: cross Abstract: Electrified chemical processes are incentivized by exposure to time-varying electricity markets to operate flexibly, but participating in demand respo

After a car accident left her paralyzed from the neck down, Audrey didn’t think she would be able to draw or paint again. 20 years later, she became the first female participant in our clinical trials

arXiv:2605.14266v1 Announce Type: new Abstract: Integration of artificial intelligent (AI) agents in higher education is transforming teaching, learning and administrative processes. Although existing

arXiv:2605.14671v1 Announce Type: cross Abstract: Autoresearch offers a flexible paradigm for automating scientific tasks, in which an AI agent proposes, implements, evaluates, and refines candidate s

arXiv:2605.14401v1 Announce Type: cross Abstract: Memory-augmented LLM agents have advanced personalized recommendation, yet existing approaches universally adopt flat memory representations that conf

arXiv:2605.14163v1 Announce Type: new Abstract: Can a committee of weak reasoning-model calls reach the performance of much stronger models? We study verifier-backed committee search as inference-time

arXiv:2509.26100v2 Announce Type: replace Abstract: The rapid integration of Large Language Models (LLMs) into high-stakes domains necessitates reliable safety and compliance evaluation. However, exis

arXiv:2605.14723v1 Announce Type: new Abstract: Sepsis management in the ICU requires sequential treatment decisions under rapidly evolving patient physiology. Although large language models (LLMs) en

Agents, agents, agents at Ship London 🇬🇧 ▪︎ Video agents with @GoogleDeepMind ▪︎ Real-time voice agents with @ElevenLabs ▪︎ Agents in production with @Telegraph, @currys, @AKQA, and @easyJet June 17 a

Agent risk management is evolving rapidly as AI moves into consequential decision-making arenas, collapsing the boundary between human and machine risk across the enterprise. The dual-threat landscape

arXiv:2605.13940v1 Announce Type: cross Abstract: Third-party skills are becoming the package ecosystem for LLM agents. They package natural-language instructions, helper scripts, templates, documents