Knowledge catalogue
In a 9-0 Supreme Court decision, Cox Communications prevailed against Sony Music Entertainment in a landmark copyright case decided March 25, 2026, with the Court finding that internet service provide
The Information: Source: new revenue sharing terms cap OpenAI's payments to Microsoft at 38B; they previously could have totaled 135B through 2030 if long-term goals were met — OpenAI Chief Financial
Lucinda Shen / Axios: Source: Robinhood has filed confidentially for its second publicly traded venture fund, Robinhood Venture Fund II, focusing on early-stage startups — Robinhood has filed confiden
Financial Times: Sources: German defense tech startup Helsing is set to raise 1.2B led by Dragoneer and Lightspeed at a valuation of about 18B, up from 14B in June 2025 — German company backed by Spot
The Information: Sources: Kuaishou plans to spin off its Kling AI video unit for an IPO in 2027 and is seeking a $20B valuation in pre-IPO funding talks with potential investors — Chinese social media
Bloomberg: Sources: Masayoshi Son has held talks with French President Emmanuel Macron about unveiling a multibillion-dollar AI data center project in the coming weeks — SoftBank Group Corp. founder M
Berber Jin / Wall Street Journal: Sources: OpenAI facilitated a 6.6B secondary share sale in October 2025 for 600+ current and ex-employees; over 75 people cashed out the maximum cap of 30M — Employee
Washington Post: Sources: the White House's Office of the National Cyber Director and Commerce Department's CAISI are fighting over which agency should lead AI model evaluations — As the White House g
SpaceX has installed a cover on the Marmac 31 barge, a vessel designated to transport Super Heavy Boosters from Starbase to unspecified destinations. The barge, nicknamed 'You'll Thank Me Later,' repr
arXiv:2605.06763v1 Announce Type: new Abstract: Sparse attention improves LLM inference efficiency by selecting a subset of key-value entries, but at the cost of potential accuracy degradation. In par
arXiv:2601.22766v3 Announce Type: replace Abstract: Recent work has revealed a link between self-attention mechanisms in transformers and test-time kernel regression via the Nadaraya-Watson estimator,
arXiv:2605.07447v1 Announce Type: cross Abstract: Vision-language models (VLMs) have advanced rapidly and are increasingly deployed in real-world applications, especially with the rise of agent-based
arXiv:2605.07286v1 Announce Type: cross Abstract: Random-feature neural networks (RFNNs), including architectures with fixed hidden layers and analytically determined output weights, offer fast traini
arXiv:2603.23198v2 Announce Type: replace-cross Abstract: Scaling autoregressive large language models (LLMs) has driven unprecedented progress but comes with vast computational costs. In this work, w
arXiv:2605.07330v1 Announce Type: cross Abstract: In large-scale reinforcement learning (RL) systems with decoupled Trainer-Rollout execution, the Trainer must regularly synchronize policy weights to
Sam Altman comments on OpenAI's new ChatGPT model, noting that the combination of improved capabilities, personality features, and personalization options has crossed an important threshold of functio
arXiv:2605.07243v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by drafting a tree of candidate continuations and verifying it in one target forward. Existing drafters f
arXiv:2605.07870v1 Announce Type: cross Abstract: We study the evolution of hidden-weight spectra in wide neural networks trained by (stochastic) gradient descent. We develop a two-level dynamical mea
arXiv:2601.22400v2 Announce Type: replace-cross Abstract: We study the problem of learning complex-valued linear dynamical systems (CLDS) with sector-bounded spectrum. This class captures oscillatory
arXiv:2605.07790v1 Announce Type: cross Abstract: The Hessian spectrum of trained deep networks exhibits a characteristic structure: a continuous bulk of near-zero eigenvalues and a small number of la
arXiv:2605.07297v1 Announce Type: cross Abstract: Understanding why trained Transformers generalize well is a fundamental problem in modern machine learning theory, and complexity-based generalization
arXiv:2605.08003v1 Announce Type: new Abstract: Video anomaly detection (VAD) aims to automatically identify events that deviate from normal patterns in untrimmed surveillance videos. Existing methods
arXiv:2509.05276v4 Announce Type: replace-cross Abstract: Mainstream Transformer-based large language models face major efficiency bottlenecks: training computation scales quadratically with sequence
arXiv:2605.07287v1 Announce Type: new Abstract: Generalizable novel view synthesis aims to render unseen views from uncalibrated input images without requiring per-scene optimization. Recent feed-forw
arXiv:2605.07420v1 Announce Type: cross Abstract: Pre-trained models with parameter-efficient fine-tuning (PEFT) have demonstrated promising potential for class-incremental learning (CIL), yet catastr
arXiv:2605.07161v1 Announce Type: new Abstract: AI agents are increasingly used to diagnose and mitigate failures in production systems, known as agentic Site Reliability Engineering (SRE). Current SR
arXiv:2605.07446v1 Announce Type: new Abstract: We report the construction of a Korean evaluation-annotated corpus, hereafter called 'Evaluation Annotated Dataset (EVAD)', and its use in Aspect-Based
arXiv:2605.07390v1 Announce Type: new Abstract: Generative models have achieved success in producing apparently coherent 2D videos, but remain challenging in the physical world due to lack of 4D spati
arXiv:2605.07116v1 Announce Type: cross Abstract: Physics-informed neural solvers offer a promising route to model-based reinforcement learning in continuous time, where optimal feedback synthesis is
arXiv:2605.07182v1 Announce Type: new Abstract: Training a family of large language models (LLMs), either from scratch or via iterative compression, is prohibitively expensive and inefficient, requiri
arXiv:2605.08029v1 Announce Type: new Abstract: Deep generative models have advanced rapidly across text and vision, motivating unified multimodal systems that can understand, reason over, and generat
Starlink is shutting down a GPS-style positioning feature that customers could previously access through its local API, with the company having restricted access to this capability that some users had
Starship’s cargo bay delivers 1,000+ cubic meters of usable volume The entire International Space Station has a pressurized volume of 1,005 m³ It took 42 assembly flights and over $150 billion across
Start 'claude agents' in a high level directory with all your repos in it (for me thats ~/Projects). It keeps track of which sessions need your input and makes it really easy to resume and pick up whe
arXiv:2605.06690v1 Announce Type: new Abstract: Recursive reasoning systems alternate between acquiring new evidence and refining an accumulated understanding. Two design choices are typically left im
arXiv:2512.23927v2 Announce Type: replace-cross Abstract: Fitted Q-iteration (FQI) and soft FQI are widely used value-based methods for offline reinforcement learning, but their standard stability gua
arXiv:2605.07908v1 Announce Type: cross Abstract: Belief functions are a powerful and popular framework for the mathematical characterisation of uncertainty, in particular in situations in which lack
arXiv:2408.11065v2 Announce Type: replace-cross Abstract: Physics seeks to uncover the laws of Nature and express them through mathematical equations. Despite the vast diversity of natural phenomena,
arXiv:2605.06736v1 Announce Type: cross Abstract: Accurate sleep stage classification across datasets remains challenging due to variability in EEG channel montages, sampling rates, recording environm
arXiv:2603.21824v2 Announce Type: replace-cross Abstract: Steel surface defect analysis is critical for industrial quality control, yet existing benchmarks rely primarily on label-only annotations, li
arXiv:2605.08005v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) aims to improve time series forecasting under distribution shifts by using limited observations revealed during inference. Ho
arXiv:2605.07661v1 Announce Type: cross Abstract: Diffusion models achieve strong generation quality, diversity, and distribution coverage, but their performance often comes with expensive inference.
arXiv:2605.06902v1 Announce Type: new Abstract: Adversarial robustness has been studied extensively for offline deep networks, but less is known about strict single-pass streaming neural learners. Thi
arXiv:2605.07384v1 Announce Type: new Abstract: Inferring the evolution of high-dimensional and multi-modal (e.g., spatio-temporal) physical fields from irregular sparse measurements in real time is a
arXiv:2605.07139v1 Announce Type: cross Abstract: When distilling reasoning from large language models (LLMs) into smaller ones, teacher rationales for similar problems often vary wildly in structure
arXiv:2405.00082v4 Announce Type: replace-cross Abstract: We study the problem of Hamiltonian structure learning from real-time evolution: given the ability to apply e^{-i Ht} for an unknown local Ham
arXiv:2601.23251v2 Announce Type: replace Abstract: State-of-the-art vision-language models (VLMs) score impressively on video benchmarks yet stumble on basic visual reasoning tasks involving spatial
arXiv:2605.07676v1 Announce Type: new Abstract: Standard flow matching scales well but typically relies on an unstructured source distribution, limiting its ability to learn interpretable latent struc
arXiv:2602.17251v2 Announce Type: replace Abstract: Electroencephalography (EEG) foundation models (EFMs) have shown strong potential for transferable representation learning, yet their adaptation in
arXiv:2605.07274v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR), especially with Group Relative Policy Optimization (GRPO), has shown strong potential for improvi
Such hypocrisy Same move. Same hand on the heart, same wave to the crowd. Musk did it and gets called a Nazi to this day. Mamdani does it and those same people have not said a word. Well, not exactly.
arXiv:2602.00924v2 Announce Type: replace Abstract: Sparse auto-encoders (SAEs) have re-emerged as a prominent method for mechanistic interpretability, yet they face two significant challenges: the no
arXiv:2501.09209v2 Announce Type: replace Abstract: Owing to recent advances in machine learning and the ability to harvest large amounts of data during robotic-assisted surgeries, surgical data scien
arXiv:2605.07980v1 Announce Type: new Abstract: These notes introduce the theory of susceptibilities as developed in [arXiv:2504.18274, arXiv:2601.12703] for interpreting neural networks. The suscepti
Swap models & view their capabilities! Try out in Deep Agents CLI: https://docs.langchain.com/oss/python/deepagents/cli/ here's model profile details look like in practice, using @NVIDIAAIDev's Nemotr
arXiv:2601.02602v2 Announce Type: replace-cross Abstract: We present SWaRL, a robust and fidelity-preserving watermarking framework designed to protect the intellectual property of code LLMs by embedd
arXiv:2605.07112v1 Announce Type: new Abstract: Agentic AI systems that invoke external tools are powerful but costly, leading developers to default to large models and overspend inference budgets. Mo
arXiv:2511.22893v2 Announce Type: replace-cross Abstract: Biotechnology can benefit from dynamic control to improve production efficiency. In this context, optogenetics enables modulation of gene expr
arXiv:2605.07288v1 Announce Type: cross Abstract: The integration of Vision-Language-Action (VLA) models with World Models has gained increasing attention. One representative approach treats learned W
arXiv:2605.07912v1 Announce Type: cross Abstract: Millions of people now turn to artificial intelligence (AI) systems for personal advice, guidance, and support. Such systems can be sycophantic, frequ