Knowledge catalogue
arXiv:2606.31963v1 Announce Type: cross Abstract: Modern LLM workflows move coordinate-indexed objects across checkpoints: steering vectors, sparse autoencoders, top-k neuron sets, attribution lists,
The best players want to be coached. You build trust, then you push hard. Now here's the thing: your agent has no skin in the game. no ego to protect, no trust to earn first. So you can and should ski
arXiv:2606.30801v1 Announce Type: new Abstract: Personalization algorithms determine what content users encounter on online platforms. Auditing these systems is difficult because independent auditors
arXiv:2606.30852v1 Announce Type: new Abstract: Reasoning models spend different amounts of useful computation across instances, but it remains unclear when a learned stopping rule improves over simpl
arXiv:2606.29911v1 Announce Type: new Abstract: Decision theory provides a formal framework for how agents should make choices under uncertainty, drawing on ideas from philosophy, probability, and cau
arXiv:2606.30586v1 Announce Type: cross Abstract: Most corporate workplace environments enforce policies and technical controls that limit the storage of sensitive data on client endpoints. Consequent
arXiv:2606.29687v1 Announce Type: cross Abstract: We report a machine-verified resolution of a problem open for over a decade in quantum optimization: the Farhi, Goldstone and Gutmann (FGG) conjecture
arXiv:2606.28757v1 Announce Type: new Abstract: Generative world models hold immense promise as scalable simulators for autonomous systems, particularly for synthesizing rare but safety-critical multi
arXiv:2604.02176v3 Announce Type: replace Abstract: While textual frequency has been validated as relevant to human cognition in reading speed, its relatedness to Large Language Models (LLMs) is seldo
Belgian cybersecurity company Aikido Security NV today announced that it has acquired Root.io Inc., a company that offers patching for vulnerable open-source software at the exact versions organizatio
arXiv:2606.29571v1 Announce Type: new Abstract: The standard way to compare two text embeddings is cosine similarity. Scattered studies report that a different metric does better, but never pin down t
arXiv:2606.29181v1 Announce Type: cross Abstract: Detecting and localizing defects in 3D point clouds is challenging because abnormal samples are scarce and diverse, while training is often limited to
Anthropic: Anthropic launches Claude Sonnet 5, saying it nears Opus 4.8 performance at lower prices and is substantially better than Sonnet 4.6 for agentic work — Claude Sonnet 5 is built to be the mo
arXiv:2603.26005v2 Announce Type: replace Abstract: Grid-interactive building control has emerged as a promising approach for improving demand-side flexibility in modern power systems. Realistic studi
arXiv:2606.29845v1 Announce Type: new Abstract: Flicker-banding (FB), arises from temporal aliasing between a camera's rolling shutter and a display's brightness modulation, degrading screen-captured
Claude Sonnet 5 has been integrated into Devin Desktop and Devin CLI, offering advanced coding capabilities at a more competitive price point than previous models. This release represents an update to
arXiv:2606.29771v1 Announce Type: new Abstract: LLM agents are increasingly cast as autonomous portfolio managers, and benchmarks have moved from financial question-answering to sequential trading. Ye
arXiv:2506.13932v3 Announce Type: replace-cross Abstract: The rise of large language models (LLMs) has led to dramatic improvements across a wide range of natural language tasks. Their performance on
arXiv:2606.30479v1 Announce Type: cross Abstract: Mitigating an observed adversary in an enterprise network typically takes weeks of expert work: an analyst derives a mitigation tailored to that adver
arXiv:2511.08307v2 Announce Type: replace-cross Abstract: Generative models, such as large language models or text-to-image diffusion models, can generate relevant responses to user-given queries. Res
arXiv:2606.28370v1 Announce Type: cross Abstract: Enterprise business intelligence queries span structured warehouses and unstructured document repositories -- modalities with fundamentally different
arXiv:2606.29898v1 Announce Type: cross Abstract: Real-world evaluation is the gold standard for robot policies because it tests them against the physical conditions and deployment challenges they are
arXiv:2606.28929v1 Announce Type: cross Abstract: Cybersecurity is a real-life test-bed for many machine learning problems at once, especially when considering modern strides in using Large Language M
arXiv:2606.29746v1 Announce Type: new Abstract: Navigating the deluge of heterogeneous medical data, from academic literature (PubMed) to clinical guidelines (Web) and private knowledge bases, remains
arXiv:2606.29727v1 Announce Type: new Abstract: Professional translation is often a team-based process: translators, reviewers, and project managers must coordinate terminology, legal force, and accou
arXiv:2604.05318v2 Announce Type: replace Abstract: Harmful content detectors, particularly disinformation classifiers, are predominantly developed and evaluated on Standard American English (SAE), le
arXiv:2606.29947v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as rerankers in recommender systems, with the expectation that semantic understanding will help in
arXiv:2512.08505v2 Announce Type: replace Abstract: Conditional diffusion models frequently suffer from language-image misalignments. Due to the ambiguity of intermediate noise corrupted latents, asse
arXiv:2606.30219v1 Announce Type: new Abstract: LLM evaluation and AI safety face a shared measurement problem: benchmark scores, reward-model signals, and reported safety metrics can improve while th
arXiv:2507.05257v4 Announce Type: replace-cross Abstract: Recent benchmarks for Large Language Model (LLM) agents primarily focus on evaluating reasoning, planning, and execution capabilities, while a
arXiv:2606.30489v1 Announce Type: cross Abstract: Normalizing Flows excel at modeling a single fixed density, yet many problems across the sciences, such as high energy physics, instead require modeli
arXiv:2606.29734v1 Announce Type: new Abstract: Earnings announcements release two types of information sequentially: quantitative surprise (numeric earnings-per-share (EPS)/revenue versus analyst est
shot-scraper video is a new command introduced in today's shot-scraper 1.10 release which accepts a storyboard.yml file defining a routine to run against a web application and uses Playwright to recor
arXiv:2606.29315v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to take actions in the real world and support human decision-making, yet most agents rely on parametr
arXiv:2606.29605v1 Announce Type: new Abstract: Clinical machine learning increasingly relies on training corpora generated by large language models (LLMs) rather than annotated by clinicians, and suc
If you build with MCPs, this one is worth reading. (bookmark it) The paper covers five recurring MCP server patterns across fifteen independently developed servers. That taxonomy is useful because I s
arXiv:2606.29693v1 Announce Type: new Abstract: We ask a simple question about decoder-only transformers: between which two layers is the probability of a predicted token actually produced? Existing l
arXiv:2606.30512v1 Announce Type: cross Abstract: Why overparameterised deep networks generalise so remarkably well remains one of the most stubborn open questions in machine learning theory. Classica
arXiv:2512.17504v2 Announce Type: replace-cross Abstract: Recent advances in diffusion models have enabled impressive video editing capabilities, yet production-grade Video Object Insertion (VOI) rema
arXiv:2606.28565v1 Announce Type: cross Abstract: As large language models (LLMs) move into production serving, practitioners must rapidly evaluate inference performance across diverse hardware, model
arXiv:2606.28841v1 Announce Type: cross Abstract: Large language models are increasingly capable of mathematical reasoning, but the proofs they generate are often unreliable and hard to verify. Intera
arXiv:2606.29399v1 Announce Type: new Abstract: Reviewing nuclear regulatory documents requires multi-hop reasoning across tens of thousands of pages, where judgments depend on evidence assembled acro
arXiv:2606.29113v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly mediate strategic interactions through natural language, making semantic control a critical element of commu
arXiv:2606.29808v1 Announce Type: cross Abstract: Chart data extraction, which reverse-engineers data tables from chart images, is essential for reproducibility, analysis, retrieval, and redesign. Exi
arXiv:2606.29604v1 Announce Type: cross Abstract: We aim to discover diverse, generalizable perturbations of LLM internals that can surface hidden behavioral modes. Such perturbations could help resha
arXiv:2606.28622v1 Announce Type: new Abstract: Differentiable rendering has emerged as a powerful approach for 3D reconstruction and novel view synthesis. State-of-the-art differentiable rendering me
arXiv:2606.30182v1 Announce Type: new Abstract: AI models are rapidly improving at autonomous coding, as shown by benchmark progress and one-off demonstrations such as AI implementing a C compiler. Ho
arXiv:2602.13562v2 Announce Type: replace-cross Abstract: While reasoning models have achieved remarkable success in complex reasoning tasks, their increasing power necessitates stringent safety measu
arXiv:2606.28917v1 Announce Type: new Abstract: Lightweight Directory Access Protocol (LDAP) is a protocol that allows users to query and modify Active Directory (AD) data. By default, all users have
arXiv:2606.28470v1 Announce Type: new Abstract: We demonstrate how emotional valence influences the order-dependent structure of children's recognition memory: correct recall of a sequence of emotiona
arXiv:2606.29971v1 Announce Type: new Abstract: A growing body of work suggests that the reasoning capabilities of large language models are largely latent in their base form, with post-training prima
Life sciences has entered an era of computational scale, and for more than a decade, NVIDIA has built the full GPU-accelerated computing stack — spanning hardware, frameworks, libraries, models, micro
arXiv:2606.30625v1 Announce Type: cross Abstract: Contrastive embedding models trained with scale-invariant losses are typically paired with distance metrics like cosine similarity, effectively ignori
arXiv:2510.19465v2 Announce Type: replace Abstract: Obtaining truly representative pore-scale images that match bulk formation properties remains a fundamental challenge in subsurface characterization
Perforce Software Inc. today expanded its Perforce Intelligence lineup with an agentic gateway for managing artificial intelligence agents, an autonomous testing platform driven by natural language an
arXiv:2603.11404v3 Announce Type: replace-cross Abstract: Accurate and efficient tracking of surgical instruments is fundamental for Robot-Assisted Minimally Invasive Surgery. Although vision-based ro
arXiv:2606.28374v1 Announce Type: new Abstract: LLM agents are increasingly improved without weight updates by evolving a natural-language artifact, such as reflections, workflows, playbooks, cheatshe
arXiv:2606.28939v1 Announce Type: new Abstract: Behavior-cloned diffusion policies are expressive but remain vulnerable to covariate shift: small deviations from demonstrated states can compound into
arXiv:2606.30294v1 Announce Type: new Abstract: Live product demonstrations are a recurring, high-cost activity in software organizations: a human presenter must select features, dispatch the correspo
arXiv:2606.29538v1 Announce Type: cross Abstract: Skills are a useful abstraction for software agents, turning human and agent experience into reusable procedural knowledge. Yet existing skill librari