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This Reddit post from r/ChatGPT documents a user's prompt request to an AI image generation tool asking for humorous, photorealistic images depicting the Met Gala red carpet attended by people from lo

Semiconductor Industry Association: Global chip sales hit 298.5B in Q1 2026, up 25% from Q4 2025, and March sales were up 79.2% YoY to 99.5B, driven by strong sales in Asia and the Americas — Worldwid

arXiv:2605.02616v1 Announce Type: new Abstract: Salient Object Detection (SOD) remains an essential yet underexplored task in the era of large-scale vision models. Although foundation models like SAM

Patrick Seitz / Investor's Business Daily: GlobalFoundries reports Q1 revenue up 3% YoY to $1.63B, in line with est., and forecasts Q2 revenue and adjusted earnings above estimates; GFS closes up 9.28

arXiv:2605.01529v1 Announce Type: new Abstract: Imitation learning offers a promising framework for enabling robots to acquire diverse skills from human users. However, most imitation learning algorit

Staffers at Google DeepMind's headquarters have voted to unionize in an effort to prevent the AI firm's technology from being used by Israel and the US military. In a letter to Google management on Tu

Google Home's May 2026 update brings a faster camera experience, Gemini 3.1 for complex voice commands, and new web-based controls. The refreshed camera UI features faster navigation and zoomed-in pre

Google Home users can now ask Gemini to complete more complex, multi-step tasks and combine multiple tasks in a single command. Google has updated Gemini for Home to Gemini 3.1, which it says will imp

Google DeepMind, Microsoft, and Elon Musk's xAI have agreed to allow the US government to review new AI models before they're released to the public. In an announcement on Tuesday, the Commerce Depart

As artificial intelligence moves from experimentation into production, government agencies are becoming an unexpected proving ground for large-scale workforce transformation. Faced with mounting opera

GPT-5.5 Instant is rolling out over the next two days as the default model to all ChatGPT users, and as ‘gpt-5.5-chat-latest’ in the API. Personalization improvements are rolling out to Plus and Pro u

OpenAI is rolling out GPT-5.5 Instant to all ChatGPT users as the new default model, replacing GPT-5.3 Instant . The model produces 52.5% fewer hallucinated claims than its predecessor on high-stakes

GPT-5.5 Instant is starting to roll out in ChatGPT. It’s a big upgrade, giving you smarter, clearer, and more personalized answers in a warmer, more natural tone. And it's also more concise, which we

GPT-5.5 Instant is OpenAI's faster, more efficient variant of their GPT-5.5 model, designed to deliver improved reasoning and clarity while maintaining lower latency for real-time applications. The mo

GPT-5.5 Instant is a faster, more efficient variant of OpenAI's GPT-5.5 model designed for real-time applications and lower-latency tasks. The system card documents the model's capabilities, limitatio

arXiv:2605.01203v1 Announce Type: cross Abstract: Currently, process reward models (PRMs) have exhibited remarkable potential for test-time scaling. Since large language models (LLMs) regularly genera

arXiv:2605.02593v1 Announce Type: new Abstract: Risk scores are an interpretable and actionable class of machine learning models with applications in medicine, insurance, and risk management. Unlike m

arXiv:2604.03190v2 Announce Type: replace Abstract: Transformer attention computes a single softmax-weighted average over values -- a one-pass estimate that cannot correct its own errors. We introduce

arXiv:2605.02609v1 Announce Type: new Abstract: The effectiveness of active learning hinges on the choice of the acquisition criterion by which a learning algorithm selects potentially informative dat

arXiv:2605.02626v1 Announce Type: new Abstract: Preference optimization has become a central paradigm for aligning large language models with human feedback. Direct Preference Optimization (DPO) simpl

arXiv:2605.02489v1 Announce Type: cross Abstract: As the ecosystem of Large Language Model (LLM)-based agents expands rapidly, efficient and accurate Agent Discovery becomes a critical bottleneck for

arXiv:2605.02376v1 Announce Type: new Abstract: Automated medical report generation, MRG, holds substantial value for alleviating radiologist workload and enhancing diagnostic efficiency. However, mai

arXiv:2605.02297v1 Announce Type: new Abstract: Graph federated learning (GFL) facilitates decentralized training on distributed graph data while keeping sensitive user information local, aligning wit

arXiv:2605.00845v1 Announce Type: cross Abstract: Knowledge Graph Question Answering (KGQA) has advanced through structured query generation, yet most efforts target RDF/SPARQL, leaving Cypher and pro

arXiv:2409.14500v5 Announce Type: replace Abstract: Although data that can be naturally represented as graphs is widespread in real-world applications across diverse industries, popular graph ML bench

arXiv:2605.01310v1 Announce Type: new Abstract: Graph self-supervised learning typically relies on large-scale unlabeled datasets, heavily inflating computational costs. However, empirical evidence su

arXiv:2605.01688v1 Announce Type: new Abstract: Long-horizon conversational agents rely on memory systems with increasingly sophisticated retrieval mechanisms. However, retrieved fragments are typical

Great new drop by @LangChain’s @hwchase17 “If you do not know what the agent saw, what it did, and what happened next, you cannot reliably know what to improve” Traces give agents this insight and tha

arXiv:2507.21153v2 Announce Type: replace Abstract: The exponential growth of digital services has positioned data centers among the most energy-intensive infrastructures in the modern economy, raisin

Grok 4.3 Grok 4.3 is now live on the xAI API. It’s our fastest, most intelligent model to date. It tops the @ArtificialAnlys leaderboards in agentic tool calling and instruction following, and ranks #

arXiv:2603.09625v2 Announce Type: replace Abstract: Deep learning models benefit from increasing data diversity and volume, motivating synthetic data augmentation to improve existing datasets. However

arXiv:2507.07129v3 Announce Type: replace-cross Abstract: We study a constrained training regime for decoder-only Transformers in which the token interface is fixed, previously trained dense blocks ar

arXiv:2405.15491v4 Announce Type: replace Abstract: We present GSDeformer, a method that enables cage-based deformation on 3D Gaussian Splatting (3DGS). Our approach bridges cage-based deformation and

arXiv:2605.00847v1 Announce Type: new Abstract: Representing and navigating hierarchy is a fundamental primitive of reasoning. Large language models have demonstrated proficiency in a wide variety of

arXiv:2605.02150v1 Announce Type: cross Abstract: Accurate prediction of physician referral links is essential for optimizing care coordination and reducing fragmentation in healthcare delivery. Howev

arXiv:2605.01561v1 Announce Type: cross Abstract: This paper develops a Hall-Sandpile model of economic instability that combines a Hall-like transversal stress mechanism with sandpile threshold dynam

arXiv:2504.10063v4 Announce Type: replace Abstract: Hallucination, i.e., generating factually incorrect content, remains a critical challenge for large language models (LLMs). We introduce TOHA, a TOp

arXiv:2605.01428v1 Announce Type: new Abstract: Despite significant strides in factual reliability, errors -- often termed hallucinations -- remain a major concern for generative AI, especially as LLM

arXiv:2605.02443v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse natural language processing tasks, yet they remain susceptible to

arXiv:2603.12243v3 Announce Type: replace Abstract: Mastering dexterous manipulation with multi-fingered hands has been a grand challenge in robotics for decades. Despite its potential, the difficulty

arXiv:2605.02596v1 Announce Type: new Abstract: With each sensing modality exhibiting inherent strengths and limitations, multi-modal approaches for wearable Human Activity Recognition (HAR) are becom

arXiv:2601.17467v2 Announce Type: replace Abstract: Large reasoning models (LRMs) often generate long, seemingly coherent reasoning traces yet still produce incorrect answers, making hallucination det

arXiv:2603.03584v2 Announce Type: replace Abstract: Maintaining situational awareness in complex driving scenarios is challenging. It requires continuously prioritizing attention among extensive scene

arXiv:2603.11308v2 Announce Type: replace Abstract: Principal Component Analysis (PCA) is a cornerstone of dimensionality reduction, yet its classical formulation relies critically on second-order mom

// HeavySkill // One of the cleaner takes on agentic harness design I've read. They argue that what actually drives agent harness performance is not the orchestration code. It's a single inner skill:

arXiv:2605.02278v1 Announce Type: new Abstract: Time series imputation benefits from leveraging cross-feature correlations, yet existing attention-based methods re-discover feature relationships at ea