Knowledge catalogue
arXiv:2509.10969v3 Announce Type: replace Abstract: This paper examines the key factors that influence the performance of state-of-the-art gaze-based authentication. Experiments were conducted on a la
arXiv:2509.25160v2 Announce Type: replace-cross Abstract: Mathematical reasoning is a key capability for vision-language models (VLMs), yet current benchmarks mainly evaluate text-based or explicitly
arXiv:2603.29353v3 Announce Type: replace Abstract: We introduce Nomad, a system for autonomous data exploration and insight discovery. Given a corpus of documents, databases, or other data sources, u
arXiv:2507.00611v2 Announce Type: replace-cross Abstract: Preference-based Reinforcement Learning (PbRL) provides a promising alternative to heuristic reward design in complex robotic environments. Ho
arXiv:2608.26832v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied to specialized domains, where effective use of domain expertise often requires reasoning over comp
arXiv:2608.26500v1 Announce Type: new Abstract: Optical Character Recognition (OCR) for text recognition using machine vision has significantly improved, particularly when handling heterogeneous textu
hexagon: support for multi-NPU devices (IQ9, IQ10) and fully asynchronous backend (#26501) hexagon: use non-host bufs by default and make the backend fully async hex-hb: remove optional hostbuf suppor
arXiv:2608.25350v1 Announce Type: new Abstract: Vision-language models (VLMs) have emerged as a powerful source of supervision for reinforcement learning, enabling agents to leverage rich semantic kno
arXiv:2512.00342v2 Announce Type: replace Abstract: Real-world intelligence systems usually operate by combining offline learning and online adaptation with highly correlated and non-stationary system
arXiv:2608.23992v1 Announce Type: cross Abstract: Large language model (LLM) agents invoke external tools to retrieve and reason over information beyond pretrained knowledge. The Model Context Protoco
arXiv:2508.09473v2 Announce Type: replace-cross Abstract: Ensuring robust safety alignment while preserving utility is critical for the reliable deployment of Large Language Models (LLMs). However, cu
arXiv:2608.24199v1 Announce Type: new Abstract: Generative simulation for surgical robotics still lacks real-time interaction. Physical-robot experiments, often involving animal or cadaver labs, are t
arXiv:2608.24876v1 Announce Type: new Abstract: Recursive self-improvement (RSI) remains hard in long-horizon tasks, where growing histories obscure the task state and misalign skill invocation. We in
arXiv:2608.23860v1 Announce Type: cross Abstract: Revelation Control is the problem of choosing priced interventions that reveal hidden state only insofar as the revealed distinctions can change a con
arXiv:2608.23421v1 Announce Type: new Abstract: Natural Language Processing (NLP) has grown rapidly over the past decade, driven by digital transformation in the Arab world, social media, and large la
arXiv:2608.21712v1 Announce Type: new Abstract: Transformer-based models are widely used for clinical prediction from electronic health records (EHRs), yet their architectures still require substantia
arXiv:2608.22187v1 Announce Type: cross Abstract: Modern driving action models are increasingly improved in a self-improvement loop, where a learned world simulator imagines future observations and th
arXiv:2508.18646v3 Announce Type: replace Abstract: Despite their rapid advancement, large language models (LLMs) suffer from a critical disconnect between benchmark scores and real-world utility. Cur
Compute has always been core to the @VerneRobotics story. Getting there meant negotiating long, expensive contracts with big neoclouds, and projecting compute needs years into the future. Verne wasn't
For the past two years, the generative artificial intelligence boom has largely been defined by a single market. Hyperscalers have dominated the market with massive capital spending. According to Cred
IBM has released Granite 4.2, an open‑source agentic AI model that adds native reasoning, tool use, coding instruction following and speech capabilities to enterprise agents. The suite of pre‑built mo
An RLM agent microharness that 'persistently' thinks continuously. What could go wrong :) Introducing Headlong, an open source microharness for persistent agents: self-guided agents that think continu
arXiv:2509.23155v3 Announce Type: replace Abstract: Robotic manipulation benefits from foundation models that describe goals, but today's agents still lack a principled way to learn from their own mis
arXiv:2608.22120v1 Announce Type: new Abstract: Cooperative teams often need to agree on the best few options rather than simply accumulate reward, and they must do so while each member sees only a fr
arXiv:2608.22828v1 Announce Type: new Abstract: X-ray angiography relies on iodinated contrast agents to visualize vascular structures during image-guided interventions. However, contrast administrati
arXiv:2608.21075v1 Announce Type: cross Abstract: This technical report presents AudioWorldSim, an open-source platform designed to generate realistic binaural audio datasets and advance research in a
arXiv:2608.20343v1 Announce Type: new Abstract: This study develops and evaluates a bankruptcy prediction framework that integrates consensus-based feature selection, hybrid resampling, stacking ensem
MobileMoE is a family of on-device Mixture-of-Experts (MoE) language models with sub-billion active parameters, designed to push the quality–efficiency Pareto frontier for on-device LLMs, including th
This is one of the most useful writeups I have seen on keeping an LLM judge effective in production. (bookmark it) Netflix runs judges over hundreds of thousands of show-level recommendation explanati
been building ShardFlow for the past few months, a distributed LLM inference framework that splits any HuggingFace transformer across N GPU machines and uses neural speculative decoding to deal with W
arXiv:2608.19526v1 Announce Type: cross Abstract: Stock market analysts and investors face a daily challenge: too much financial news, too little time. Manually reading and synthesizing hundreds of co
arXiv:2608.19201v1 Announce Type: cross Abstract: Bioinformatics software and databases are essential components of modern life science research, yet their mentions in the scientific literature are of
arXiv:2608.19688v1 Announce Type: cross Abstract: We develop a geometric framework for learning deterministic and stochastic forced Hamiltonian systems with neural networks. Motivated by the Lagrange-
arXiv:2608.19009v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly paired with verifiers (step checkers, self-consistency filters, tool-based fact checkers, formal proof ass
arXiv:2608.18907v1 Announce Type: cross Abstract: Small-scale image classification is often limited by the scarcity of training data. Generative data augmentation (GDA) based on pretrained generative
arXiv:2608.19059v1 Announce Type: cross Abstract: Long-term robot operation in evolving environments requires object-level understanding that persists across repeated revisits. Existing systems either
arXiv:2608.18111v1 Announce Type: new Abstract: Foundation models such as GPT and Claude now solve olympiad-level mathematics with remarkable proficiency, so much so that geometry problem solving has
arXiv:2608.18144v1 Announce Type: cross Abstract: Modal auxiliaries such as must, should, and have to mark necessity and obligation within the contexts of speaker authority and interpersonal stance. W
arXiv:2608.18300v1 Announce Type: new Abstract: LLM-as-a-Judge, which leverages a large language model to evaluate natural language generated by another AI application or model, has become a standard,
arXiv:2608.18504v1 Announce Type: new Abstract: Universal multimodal retrieval aims to support diverse instruction-aware retrieval tasks, demanding both efficient corpus-scale matching and fine-graine
arXiv:2602.01115v3 Announce Type: replace-cross Abstract: Diffusion-based visuomotor policies excel at modeling action distributions but are inference-inefficient, since recursively denoising from noi
New open-source agent harness just landed! I got early access to TrueForge by TrueFoundry and have been running it locally for the past few days. The harness layer deserves as much attention as the mo
arXiv:2403.15594v4 Announce Type: replace-cross Abstract: Domestic violence is commonly viewed as a gendered issue that primarily affects women, which tends to leave male victims largely overlooked. T
arXiv:2608.17180v1 Announce Type: cross Abstract: Contextual Reinforcement Learning (CRL) seeks to generalize classical RL by maximizing task coverage across a context space of related tasks. While pr
arXiv:2602.17127v2 Announce Type: replace Abstract: Large language models increasingly serve as reasoning layers in multi-agent systems, where one provider's models may generate, judge, and summarize
arXiv:2608.17959v1 Announce Type: new Abstract: State-of-the-art model-based reinforcement learning methods learn neural world models that allow policy improvement by planning in a latent space, witho
Bonsai / Ternary Bonsai During April Bonsai came with bunch of models .... 1-bit & 1.58-bit(Ternary) versions. And last month(July) they released 27B models in same versions. Last month itself, Bonsai
arXiv:2608.15363v1 Announce Type: new Abstract: Label uncertainty and annotator disagreement are common challenges in the field of computer vision, yet their study has largely been confined to the med
arXiv:2608.15407v1 Announce Type: cross Abstract: An invariant behavioral profile is the defining vulnerability of traditional honeypot installations: a skilled adversary can confirm the presence of a
arXiv:2608.16207v1 Announce Type: new Abstract: Consider a firm that surveys its competition for a particular agentic task and seeks to offer superior accuracy at every competitor price point. A firm
arXiv:2608.15447v1 Announce Type: new Abstract: Mobile money has widened financial access across Sub-Saharan Africa and enlarged the surface for money-laundering and terrorism-financing (ML/TF) activi
arXiv:2608.15282v1 Announce Type: cross Abstract: Earth observation foundation models (EOFMs) are emerging as reusable representation frameworks for data-driven retrieval, prediction and process model
arXiv:2608.15424v1 Announce Type: cross Abstract: The rapid adoption of large language models has enabled the development of clinical multi-agent systems (MAS) capable of integrating multimodal patien
arXiv:2608.15841v1 Announce Type: new Abstract: Reinforcement learning has gained increasing attention as a data-driven approach for stock trading. However, learning a policy that is both profitable a
arXiv:2608.16394v1 Announce Type: new Abstract: Generating regulation-compliant test scenarios is essential for validating safety-critical automotive systems, yet Large Language Models (LLMs) struggle
arXiv:2608.13626v1 Announce Type: new Abstract: A hidden state signal can be decodable or causally usable without supporting a reusable action map. We test whether action maps fitted without a source
arXiv:2608.14281v1 Announce Type: new Abstract: Forecasting crop growth across agricultural landscapes is important for improving the productivity, resilience, and operational management of farming sy
arXiv:2608.13973v1 Announce Type: new Abstract: Recent foundation model-based methods have endowed RGB images with strong zero-shot anomaly detection (ZSAD) through vision-language pretraining. Howeve
3000000000 downloads! Can you count the zeros at a glance? 😎 Thank you all for the incredible love. Let's keep growing together! 🌱 Alibaba's open-weight models have accumulated more than 3 billion glo
I am doing my best to stop back from this subject as it should be obvious what we are seeing here. However the arrogance that us commoners are too dumb to catch his grift must be addressed. Receipts: