Knowledge catalogue
arXiv:2607.06052v1 Announce Type: new Abstract: Humanoid robots are increasingly expected to perform contact-rich tasks that require not only accurate whole-body motion but also robust physical intera
To audit SWE-Bench Pro, we used model-based investigator agents alongside independent reviews from five independent experienced software engineers. That helped us examine tasks at scale while keeping
Tomorrow at 10am PT I'm hosting a live walkthrough of how we progressed from single-player Claude Code to multi-player Claude Tag. Then, we're going deep on how Claude Tag actually works. AI used to f
Trained entirely in simulation: ~400,000 trajectories across 6,000 scenes. A prefix-caching recipe cuts training tokens by 22×, turning months-long runs into days. Online RL (CISPO) pushes success rat
arXiv:2602.22600v2 Announce Type: replace-cross Abstract: Training selects for behavior, not circuitry: many weight configurations can implement the same function. Studying any single trained neural n
arXiv:2607.06306v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated growing competence in web page generation. However, existing text-driven approaches rely on complex pro
arXiv:2607.06537v1 Announce Type: new Abstract: Mobile manipulation requires a robot to navigate to a target object or receptacle and then perform intended manipulation. However, reaching the vicinity
arXiv:2607.06254v1 Announce Type: cross Abstract: Deepfake image detection is currently served by three fundamentally different paradigms: commercial APIs, zero-shot vision-language models (LLMs), and
arXiv:2607.06466v1 Announce Type: new Abstract: This paper addresses the remote verification of the authenticity of Optically Variable Devices (commonly known as holograms) on identity documents. Typi
arXiv:2510.13808v2 Announce Type: replace Abstract: Large Vision Language Models (VLMs) excel at general visual reasoning but experience significant performance degradation when deployed in novel doma
We audited SWE-Bench Pro, one of the most widely used AI coding benchmarks, and found it no longer reliably measures frontier coding capability. We find 30% of SWE-Bench Pro tasks to be broken, and ar
We need AI model selection to be MUCH easier ASAP. I want proactive flags from my AI systems suggesting models. I want my AI harness to say 'hey allie, my girl, you keep asking for bar recommendations
We tuned the harness for @NVIDIAAI Nemotron 3 Ultra. Benchmark-leading performance. 10x lower inference costs. ✅ An aggregate score of 0.86 at a cost of 4.48 ✅ The closest-performing model: 43.48 http
arXiv:2607.06118v1 Announce Type: new Abstract: As web agents increasingly demonstrate capabilities in automated task execution, the development of robust evaluation frameworks for assessing their nav
We've usually stayed away from model comparisons but 5.6 vs Fable is a unique situation We've never had a case where the team is so completely convinced on which one is better Here's the timeline of o
arXiv:2607.05752v1 Announce Type: cross Abstract: Search-augmented language models can use external evidence to compensate for limitations in parametric knowledge, but search is not uniformly benefici
arXiv:2607.06023v1 Announce Type: new Abstract: Visual SLAM is a well-established technology utilized in a wide range of real-world applications. However, its performance still degrades under challeng
This is a Wordle game result shared by Anthropic on X (formerly Twitter), showing that they solved Wordle puzzle #1,844 in 3 attempts out of 6 possible guesses. The colored squares indicate the guess
WOW! GROK 4.5 PRICES ARE NEAR OPEN SOURCE HOSTED PRICES! This will move many that have token cost fatigue in corporations. But that is only half the story: it is ~4.2 more efficient using far less tim
arXiv:2607.06114v1 Announce Type: cross Abstract: Diffusion and flow matching models generate high-quality samples, but their ODE samplers often need tens to hundreds of neural function evaluations (N
Xiaomi now processes more AI tokens than OpenAI. On OpenRouter, Chinese models just crossed 45% of all token volume. Anthropic is at 15.3%. OpenAI is at 7.4%. For now, the frontier is American models,
arXiv:2607.06424v1 Announce Type: new Abstract: X-ray fluorescence (XRF) spectroscopy is a key modality for material analysis in cultural heritage. However, automated learning from XRF spectra remains
arXiv:2502.09696v3 Announce Type: replace Abstract: Large Multimodal Models (LMMs) exhibit shortfalls when interpreting images and, by some measures, have poorer spatial cognition than young children
Cohere announced that approximately 25% of Toronto's working population is employed by the company during a particular week. This statement reflects Cohere's significant presence and growth as a major
If you’re an IT leader, you might be getting a lot of questions about how to build and deploy agents. The pressure to move fast is intense, but the engineering reality is incredibly complex. Where do
arXiv:2604.06025v2 Announce Type: replace Abstract: The performance of legged robots depends strongly on both mechanical design and control, motivating co-design approaches that jointly optimize these
Software-as-a-service (SaaS) is evolving into Agents-as-a-service (AaaS). Instead of isolated applications, developers are creating AI agents that interoperate using standardized open protocols such a
arXiv:2607.03739v1 Announce Type: cross Abstract: We release a benchmark and failure-mode-aware evaluation framework for grounded QA under coordinated retrieval poisoning. The framework partitions rea
arXiv:2607.03659v1 Announce Type: cross Abstract: Relational databases (RDBs) are the primary data infrastructure in many enterprises, yet recent deep learning methods designed for RDBs have been eval
arXiv:2607.03871v1 Announce Type: new Abstract: Minimum maximum mean discrepancy (MMD) estimation has emerged as a robust and likelihood-free alternative to maximum likelihood estimation for parameter
arXiv:2607.03945v1 Announce Type: new Abstract: Remote sensing imagery plays a crucial role in evaluating regional transportation capacity. However, existing segmentation datasets often lack diversity
arXiv:2607.03503v1 Announce Type: new Abstract: Graph-based semi-supervised learning (SSL) propagates a few labels over a similarity graph by minimizing a Dirichlet-type energy. The standard quadratic
arXiv:2607.04689v1 Announce Type: cross Abstract: Safe operation of autonomous vehicles in dense urban traffic depends on perception and planning that remain reliable when onboard sensing is degraded.
arXiv:2607.04436v1 Announce Type: cross Abstract: Natural language requirements (NLRs) are essential for bridging communication gaps among diverse stakeholders in software development. However, the in
arXiv:2607.03600v1 Announce Type: cross Abstract: Adversarial robustness in Unsupervised Domain Adaptation (UDA) remains a significant challenge due to noisy pseudo labels and inherent distributional
arXiv:2607.03664v1 Announce Type: new Abstract: The Gaussian Error Linear Unit is usually motivated as the expected output of an input-dependent stochastic Bernoulli gate. This work gives a complement
arXiv:2509.08269v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly integrated with evolutionary computation to support optimization tasks. This survey primarily fo
arXiv:2507.04136v2 Announce Type: replace Abstract: This survey offers a comprehensive foundation on the integration of RL with language models, highlighting prominent algorithms such as Proximal Poli
arXiv:2607.03839v1 Announce Type: new Abstract: Sparse feature selection is critical for high-dimensional machine learning, yet traditional ell_1-regularized methods are often brittle under observatio
arXiv:2607.05120v1 Announce Type: cross Abstract: AI agents act on behalf of user prompts, consuming external data and taking actions based on the agent context. Prior research on AI agent security ha
arXiv:2607.04331v1 Announce Type: cross Abstract: Evaluating autonomous driving systems in closed-loop settings requires realistic and interactive simulation, yet existing simulators largely rely on l
arXiv:2607.04419v1 Announce Type: new Abstract: Most agent evaluations collapse a multi-step trace into a final answer, a success flag, or a trajectory-level score. These aggregates obscure the diagno
arXiv:2607.05174v1 Announce Type: new Abstract: Language agents, i.e., LLM agents, progress rapidly and are increasingly deployed in production environments. This trend underscores the urgent need for
arXiv:2605.05409v2 Announce Type: replace Abstract: Financial document question answering (QA) demands complex multi-step numerical reasoning over heterogeneous evidence--structured tables, textual na
arXiv:2607.04758v1 Announce Type: new Abstract: Physical design quality-of-results~(QoR) optimization is hard and expensive. Choices made at one stage can help or hurt later stages. Each evaluation re
arXiv:2607.02599v1 Announce Type: cross Abstract: Tool-using LLM agents are usually evaluated by final-answer correctness or LLM judges. Neither captures how an answer was produced. In safety-critical
arXiv:2607.04410v1 Announce Type: new Abstract: We present the AI Wizards submission to EXIST 2026 for multimodal sexism identification in memes. The task is composed of three, increasingly harder sub
New York Times: Alibaba's Qwen models have made it an AI powerhouse, but the company has struggled to turn their global popularity into a profitable business — The Chinese company's models have won ov
Amazon.com Inc. is back in the bond market, this time to raise at least 25 billion for its artificial intelligence buildout, according to Bloomberg. The offering is split into eight parts, senior unse
arXiv:2607.03426v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit strong reasoning and world-knowledge capabilities, yet often struggle to gather information effectively across th
arXiv:2607.03639v1 Announce Type: cross Abstract: For a multidimensional reflected diffusion, determining whether the associated basic adjoint relationship (BAR) uniquely characterizes the stationary
arXiv:2607.03523v1 Announce Type: cross Abstract: Code repair is an important capability for language models (LMs): given a buggy program and unit tests, an LM must produce a fixed program that passes
arXiv:2607.01290v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful representation for high-fidelity rendering. However, existing assets often suffer from qualit
arXiv:2607.03182v1 Announce Type: cross Abstract: Autonomous driving planning requires translating navigation intent, traffic rules, dynamic interactions, and language instructions into executable con
Another day another big public tech co saying they’re using open source AI models extensively With our internal coding benchmark, we're able to confidently introduce open-weight models into our AI cod
Anthropic PBC today announced it’s bringing its Claude Cowork agentic artificial intelligence assistant to mobile and the web, breaking it free from the desktop. Cowork allows users to harness the com
David Gewirtz / ZDNET: Anthropic expands Claude Cowork to web and mobile in beta for Max plan subscribers, and says 90%+ of Cowork usage is unrelated to software development — ZDNET's key takeaways —
Starting Tuesday, Anthropic's Claude Cowork AI platform will be available on mobile and web for the first time. The expanded access is rolling out first to Max subscribers and coming to Claude users o
Anthropic releasing open source demos built on top of Qwen (with @neuronpedia) is not something that I was expecting We also partnered with Neuronpedia to create an interactive demo of our methods on
arXiv:2607.03162v1 Announce Type: new Abstract: LLM-powered agents struggle with personalization when users issue raw, underspecified queries. In this setting, agents must infer latent intent, extract