Knowledge catalogue
Alexey Shabanov / TestingCatalog AI News: OpenAI launches Daybreak, a cybersecurity initiative integrating AI models and Codex Security to help organizations patch vulnerabilities — OpenAI launches Da
arXiv:2605.07278v1 Announce Type: cross Abstract: A latent world model may achieve accurate short-horizon prediction while still inducing a latent space that is poorly aligned with planning. A key iss
arXiv:2605.07076v1 Announce Type: new Abstract: Large language models (LLMs) increasingly receive information as streams of passages, conversations, and long-context workflows. While longer context wi
arXiv:2605.07725v1 Announce Type: cross Abstract: Tool-integrated reasoning (TIR) is difficult to scale to small language models due to instability in long-horizon tool interactions and limited model
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:2605.07282v1 Announce Type: new Abstract: Final outputs hide when a checkpoint commits to its next-token prediction. We introduce the convergence gap, a model-diffing diagnostic that decodes eac
arXiv:2605.07776v1 Announce Type: cross Abstract: Language model (LM) 'reasoning', commonly described as Chain-of-Thought or test-time scaling, often improves benchmark performance, but the dynamics u
arXiv:2601.18744v2 Announce Type: replace Abstract: Time series are ubiquitous in real-world scenarios and crucial for applications ranging from energy management to traffic control. Consequently, the
arXiv:2605.07984v1 Announce Type: cross Abstract: We study planning site formation in language models -- where internal representations of structurally-constrained future tokens form during the forwar
This post provides a detailed review and practical guide for setting up and testing Ollama with DeepSeek models specifically on Ryzen APU systems. It likely covers performance benchmarks, configuratio
100% agree on the Context Hub. Developers constantly tweak their approaches to manage context in their prompts with each new model and tool suite release. I would even say that the core problem we fac
Anthropic: Anthropic details how it improved Claude's safety training after finding agentic misalignment in older models, such as Opus 4 blackmailing engineers — Last year, we released a case study on
Google has offered Gemini Nano for Chrome since 2024 as a lightweight, on-device model , but users reasonably expect the visible AI Mode to use the on-device model with queries staying local, when in
CyberSecQwen-4B is a specialized 4-billion parameter language model designed for cybersecurity defense tasks that can run locally on standard hardware. The model addresses the need for small, efficien
OpenAI announced new voice intelligence models available through its API, expanding capabilities for developers to integrate advanced voice processing and understanding features into their application
Anthropic: Anthropic researchers detail “natural language autoencoders”, which convert LLM activations, the numbers encoding a model's thoughts, into natural language text — When you talk to an AI mod
arXiv:2605.05092v1 Announce Type: cross Abstract: Safe L2/L3 driving automation requires anticipating human-in-the-loop reactions during shared-control transitions. While most driving world models for
arXiv:2510.18518v2 Announce Type: replace Abstract: We present an online model-based reinforcement learning algorithm suitable for controlling complex robotic systems directly in the real world. Unlik
arXiv:2605.05082v1 Announce Type: cross Abstract: We externally validated three deep learning models (DenseNet121, ViT-B/32, and ResNet50) for predicting mammographic breast density from breast ultras
arXiv:2605.05062v1 Announce Type: new Abstract: As time-to-market is crucial in the Integrated Circuit (IC) industry, speeding up layout manufacturability verifi-cation is essential. Chemical-Mechanic
Introducing GPT-Realtime-2 in the API: our most intelligent voice model yet, bringing GPT-5-class reasoning to voice agents. Voice agents are now real-time collaborators that can listen, reason, and s
arXiv:2605.05187v1 Announce Type: new Abstract: This paper reports on the LoViF 2026 PhyScore challenge, a competition on holistic quality assessment of world-model-generated videos across both 2D and
arXiv:2602.22291v3 Announce Type: replace Abstract: While prior work has focused on projecting adversarial examples back onto the manifold of natural data to restore safety, we argue that a comprehens
arXiv:2505.00835v2 Announce Type: replace-cross Abstract: Appropriate modelling of extreme skew surges is crucial, particularly for coastal risk management. Our study focuses on modelling extreme skew
Saw this and thought 'yes! ChatGPT voice mode is going to stop acting like a two-year-model' but that upgrade hasn't shipped just yet Introducing GPT-Realtime-2 in the API: our most intelligent voice
A TLDR on Harness Profiles: ✅ Model-specific profiles to adjust prompts, tools, and middleware. 📦 Profiles for @OpenAI, @Anthropic, and @Google models out of the box. 📈 A 10–20 point jump on a subset
arXiv:2605.03903v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have recently shown strong performance on Optical Character Recognition (OCR) tasks, demonstrating their promising capabi
arXiv:2605.00932v1 Announce Type: cross Abstract: This report documents the preparedness assessment of Code World Model (CWM), a model for code generation and reasoning about code from Meta. We conduc
arXiv:2605.02285v1 Announce Type: new Abstract: The deployment of Large Language Models (LLMs) for specialized engineering domains, such as circuit analysis, often faces a trade-off between reasoning
arXiv:2605.03547v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs), trained on web-scale data, risk memorizing and regenerating copyrighted visual content such as characters and logo
arXiv:2605.03855v1 Announce Type: new Abstract: Human-AI collaboration requires AI agents to understand human behavior for effective coordination. While advances in foundation models show promising ca
arXiv:2605.03460v1 Announce Type: cross Abstract: Time series (TS) reasoning models (TSRMs) have shown promising capabilities in general domains, yet they consistently fail on financial domain, which
Ryan Whitwam / Ars Technica: Google releases Multi-Token Prediction drafters for its Gemma 4 models, which use a form of speculative decoding to guess future tokens for faster inference — Google launc
arXiv:2605.03497v1 Announce Type: new Abstract: Score-based diffusion models in infinite-dimensional function spaces provide a mathematically principled framework for modelling function-valued data, o
arXiv:2511.08877v2 Announce Type: replace Abstract: Large language models (LLMs) generate fluent text across a wide range of tasks, but the fabrication of non-existent academic citations remains a cri
arXiv:2605.03438v1 Announce Type: new Abstract: Pre-trained 3D point cloud foundation models (PFMs) have demonstrated strong transferability across diverse downstream tasks. However, full fine-tuning
arXiv:2603.10083v2 Announce Type: replace-cross Abstract: Quantum machine learning models based on parameterized circuits can be viewed as Fourier series approximators. However, they often struggle to
arXiv:2605.02728v1 Announce Type: new Abstract: This paper presents ORPilot, an open-source agentic AI system that translates real-world business problems into solver-ready optimization models. Unlike
arXiv:2605.01147v1 Announce Type: new Abstract: As large language models are increasingly deployed as interacting agents in high-stakes decisions, the AI safety community assumes that safety propertie
arXiv:2605.04039v1 Announce Type: new Abstract: Clinical LLMs are often scaled by increasing model size, context length, retrieval complexity, or inference-time compute, with the implicit expectation
arXiv:2507.00994v4 Announce Type: replace Abstract: Learning high-quality text representations is fundamental to a wide range of NLP tasks. While encoder pretraining has traditionally relied on Masked
arXiv:2508.05691v3 Announce Type: replace-cross Abstract: Detecting the source model of AI-generated images is a growing accountability problem. AI fingerprinting techniques address this by detecting
arXiv:2605.02269v1 Announce Type: new Abstract: Specification gaming is a critical failure mode of LLM agents. Despite this, there has been little systematic research into when it arises and what driv
arXiv:2605.03276v1 Announce Type: new Abstract: Real-world video editing demands not only expert knowledge of cinematic techniques but also multimodal reasoning to select, align, and combine footage i
arXiv:2605.01449v1 Announce Type: cross Abstract: Universal adversarial attacks on aligned multimodal large language models are increasingly reported with attack success rates in the 60-80% range, sug
We’ve developed our own inference engine Runtime-Optimized Serving Engine (ROSE) to serve models ranging from embeddings to trillion-parameter LLMs. With CuTeDSL integrated into our inference engine,
arXiv:2605.03475v1 Announce Type: new Abstract: Evaluating generative video models remains an open problem. Reference-based metrics such as Structural Similarity Index Measure (SSIM) and Peak Signal t
arXiv:2605.02270v1 Announce Type: new Abstract: This paper presents the first comprehensive comparative analysis of modern machine learning architectures for transliteration between Tajik (Cyrillic sc
arXiv:2605.00245v1 Announce Type: new Abstract: Large language models (LLMs) are now being explored for defense applications that require reliable and legally compliant decision support. They also hol
arXiv:2605.01451v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly being integrated into high-stakes public safety systems, including emergency call triage and dispatch decision
arXiv:2605.01073v1 Announce Type: new Abstract: The paper studies the local geometry of embedding clouds induced by controlled local classes of semantically close sentences. The central question is ho
arXiv:2605.01896v1 Announce Type: new Abstract: Emerging multi-modal world models attempt to jointly generate videos across diverse modalities (e.g., RGB, depth, and mask), yet they fail to fully expl
arXiv:2605.00850v1 Announce Type: cross Abstract: Foundation models (FMs) for the Earth system learn statistical relationships between physical variables across massive datasets to enable versatile do
arXiv:2605.01650v1 Announce Type: new Abstract: Reliable subnational population estimates are essential for applications, yet remain difficult where censuses are sparse, outdated or spatially coarse.
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
Large language models are becoming increasingly costly to develop and operate, creating a need for open-source alternatives that reduce dependency on expensive proprietary models and make AI more acce
arXiv:2605.01333v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have emerged as a promising paradigm for dental image analysis. However, their ability to capture the multi-lev
arXiv:2603.27259v2 Announce Type: replace Abstract: Long video understanding (LVU) remains a core challenge in multimodal learning. Although recent vision-language models (VLMs) have made notable prog
arXiv:2605.01653v1 Announce Type: new Abstract: We introduce SteeringDiffusion, a bottlenecked activation-level control interface for diffusion models that exposes a smooth, monotonic, and runtime-adj
arXiv:2605.01950v1 Announce Type: new Abstract: World models enable long-horizon planning by internally generating and evaluating imagined trajectories, making them a promising foundation for generali