Knowledge catalogue
arXiv:2606.23686v1 Announce Type: new Abstract: Despite the impressive manipulation capabilities of Vision-Language-Action (VLA) models, their operational safety under strict constraints remains large
arXiv:2511.22354v2 Announce Type: replace Abstract: This paper introduces CoMuRoS (Collaborative Multi-Robot System), a generalizable hierarchical architecture for heterogeneous robot teams that unifi
arXiv:2606.22013v1 Announce Type: new Abstract: Machine learning (ML) model serving has become a dominant consumer of GPU infrastructure, yet capacity planning in these systems remains largely ad hoc.
arXiv:2603.14343v2 Announce Type: replace Abstract: Large Audio-Language Models (LALMs) have shown strong performance in speech understanding, making speech a natural interface for accessing factual i
arXiv:2606.22772v1 Announce Type: new Abstract: Lip-syncing deepfakes are among the most challenging forms of manipulated media because their artifacts are localized almost exclusively to the mouth re
arXiv:2606.21527v1 Announce Type: cross Abstract: Robust obstacle segmentation is essential for the safety of intelligent robots, where LiDAR-based perception systems play a fundamental role in the ro
This post likely discusses configuration options for setting up Claude agent identity and explains the design decisions behind Claude Tag, Anthropic's tool for customizing Claude's behavior and person
arXiv:2606.13912v2 Announce Type: replace-cross Abstract: Complex neural quantum states are difficult to optimize when their wavefunction phase carries gauge, chiral, fermionic, or topological structu
arXiv:2606.23118v1 Announce Type: new Abstract: Low-light human action recognition remains a challenging problem due to poor illumination, amplified noise, motion ambiguity, and diverse real-world sce
arXiv:2509.23729v3 Announce Type: replace Abstract: Large Language Models (LLMs) with multimodal capabilities have revolutionized vision-language tasks, but their deployment often requires huge memory
arXiv:2606.21119v1 Announce Type: new Abstract: Mammography is an essential tool for breast cancer detection, with millions of examinations conducted annually. However, publicly available high-quality
arXiv:2606.22597v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used to read maps for logistics, delivery, and accessible navigation, where the output is an actionable d
arXiv:2606.21830v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has driven rapid progress in mathematical and code reasoning, but when extended to science, existi
arXiv:2506.16584v3 Announce Type: replace-cross Abstract: People judge interactions with large language models (LLMs) as successful when outputs match what they want, not what they type. Yet LLMs are
arXiv:2606.21194v1 Announce Type: new Abstract: Medical Vision-Language Models (Med-VLMs) achieve strong expert-level performance, yet their ability to generate patient-accessible descriptions remains
arXiv:2606.21329v1 Announce Type: new Abstract: Medical time series (MedTS) signals such as electroencephalography (EEG) and electrocardiography (ECG) support many clinical applications. However, subs
arXiv:2606.21898v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a promising method for high-quality, real-time 3D reconstruction. To associate 3DGS with mesh representati
For the past three years, 'Meta' and 'Ray-Ban' have been synonymous in the smart glasses space. Not anymore. Yesterday, I slipped on several pairs of Meta Glasses - no Ray-Bans - in three different st
arXiv:2606.20752v1 Announce Type: new Abstract: Deep neural network-based LiDAR 3D object detection serves as a critical perception component in safety-critical autonomous systems. However, recent stu
Mistral AI Blog: Mistral debuts OCR 4, a model featuring structured document extraction with bounding boxes, block classification, and inline confidence scores, in 170 languages — Today, we're releasi
arXiv:2606.22551v1 Announce Type: cross Abstract: Hybrid Quantum Neural Network (QNN) classifiers produce logits as expectation values of quantum measurement operators. For standard Pauli measurements
arXiv:2606.22437v1 Announce Type: new Abstract: We conduct a systematic study of 18 widely used vision-language benchmarks and identify three major issues: 1) many items do not rely on visual cues and
arXiv:2603.14145v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have shown strong performance in visual and audio understanding when evaluated in isolation. However,
arXiv:2602.20208v2 Announce Type: replace Abstract: Model merging aims to integrate multiple task-specific fine-tuned models derived from a shared pre-trained checkpoint into a single multi-task model
arXiv:2606.21033v1 Announce Type: cross Abstract: Image compression for machines calls for a unified codec that serves multiple downstream vision tasks. Existing approaches either adopt task-specific
arXiv:2603.27048v3 Announce Type: replace Abstract: Computational pathology needs whole-slide image (WSI) foundation models that transfer across diverse clinical tasks, yet current approaches remain l
arXiv:2606.23603v1 Announce Type: new Abstract: Unhealthy dietary behavior continues to be a persistent public health issue in the United States, exacerbated by recommendation systems that prioritize
arXiv:2606.22077v1 Announce Type: new Abstract: Morphological traits provide important evidence for phylogenetic reconstruction and evolutionary relationship analysis. Recent image-based approaches ha
arXiv:2606.23061v1 Announce Type: new Abstract: Motion instruction generation in cross-video comparison aims to produce corrective feedback that describes the differences between a query and a referen
arXiv:2606.22377v1 Announce Type: new Abstract: Deep learning has demonstrated significant success for modeling biochemical molecular systems, where inputs are commonly represented as graphs or 3D gri
arXiv:2606.23637v1 Announce Type: new Abstract: Matrix-aware optimizers such as Muon and Muown have recently shown strong empirical performance for pre-training Transformers. In particular, Muown sepa
arXiv:2606.23155v1 Announce Type: cross Abstract: Mean field games efficiently approximate a very large population of strategic agents. While these games can aid the understanding of complex systems,
arXiv:2602.09012v2 Announce Type: replace Abstract: The rapid evolution of GUI-enabled agents has rendered traditional CAPTCHAs obsolete. While previous benchmarks like OpenCaptchaWorld established a
arXiv:2603.00180v2 Announce Type: replace Abstract: Generative modeling of neural network parameters is often tied to architectures because standard parameter representations rely on known weight-matr
arXiv:2606.23295v1 Announce Type: new Abstract: In this paper we prove some concentration inequalities for two types of error probabilities in the Empirical Risk Principle (ERP) in statistical learnin
arXiv:2606.22030v1 Announce Type: cross Abstract: We present Nous, a novel agent memory architecture grounded in the principle that knowledge is prediction, not storage. Rather than persisting facts a
arXiv:2602.00012v3 Announce Type: replace Abstract: We present OGD4All, a transparent, auditable, and reproducible framework based on Large Language Models (LLMs) to enhance citizens' interaction with
arXiv:2606.20682v1 Announce Type: new Abstract: Automated cheque processing requires localising key fields (date, legal amount, IFSC code, account number, signature, and payee name) before any recogni
Telecommunications is an incredibly complex, highly specialized domain. Modern mobile networks are inherently multi-vendor, featuring diverse and often proprietary data structures. While AI has made m
arXiv:2606.23676v1 Announce Type: new Abstract: AdamW is the de facto optimizer for training large language models (LLMs), yet the theory behind it still lives mostly in finite-variance regimes. This
OpenAI DevDay 2026, the company's major developer conference, will take place in San Francisco on September 29, 2026, with applications opening for attendees. The application deadline is July 1, 2026.
Tool: OPFS + Pyodide test harness I've been pondering if Datasette Lite - the Python Datasette application run entirely in the browser using Pyodide and WebAssembly - might be able to edit persistent
arXiv:2510.02561v2 Announce Type: replace Abstract: Recent advances in large video-language models (VLMs) rely on extensive fine-tuning techniques that strengthen alignment between textual and visual
arXiv:2606.22357v1 Announce Type: cross Abstract: Language models are widely used in assistant settings, where controlling behavioral attributes is often essential. Activation steering modifies hidden
arXiv:2606.21199v1 Announce Type: cross Abstract: We introduce a semi-parametric framework for nonlinear system identification, which decouples discrepancy functions from physics-based components. Ort
arXiv:2606.21045v1 Announce Type: cross Abstract: The rapid growth of AI has increased the demand for domain-specific post-training, while the cost and specialization of accelerator infrastructure pus
arXiv:2606.22150v1 Announce Type: new Abstract: Solving high-dimensional and high-order PDEs is challenged by the coupled growth of spatial dimensionality and derivative order. Recent stochastic deriv
arXiv:2606.22890v1 Announce Type: new Abstract: Optical microscopy enables rapid, label-free imaging of live bacteria and is the standard instrument for species identification across clinical, environ
arXiv:2606.23226v1 Announce Type: new Abstract: Remote Photoplethysmography (rPPG) enables contactless pulse estimation from facial videos, serving as a vital tool for health monitoring. However, curr
arXiv:2606.20916v1 Announce Type: new Abstract: Iterative design and optimization of large, complex structures require fast and accurate prediction of stress, displacement, and other fields. Finite el
arXiv:2606.21725v1 Announce Type: cross Abstract: The Morse index of a free boundary minimal surface is encoded in its Jacobi-Steklov spectrum, and we test how faithfully a physics-informed neural net
arXiv:2606.22889v1 Announce Type: new Abstract: Multimodal large language models (LLMs) are increasingly adopted to interpret 12-lead ECG images, though the interpretations often lack validation. Howe
arXiv:2602.12373v2 Announce Type: replace Abstract: The opioid epidemic remains one of the most severe public health crises in the United States, yet evaluating policy interventions before implementat
arXiv:2606.23604v1 Announce Type: new Abstract: The tracking-by-detection paradigm in multi-object tracking (MOT) typically relies on static appearance descriptors to complement motion estimation. How
arXiv:2606.21458v1 Announce Type: new Abstract: Speech enhancement language models achieve strong results when trained on discrete audio tokens, but their optimization relies on token-level cross-entr
arXiv:2606.21447v1 Announce Type: cross Abstract: Automated radiology report generation (RRG) has gained increasing attention because it can reduce the heavy workload of clinical report writing. Howev
arXiv:2501.09731v2 Announce Type: replace-cross Abstract: We establish a formal connection between the decades-old surrogate outcome model in biostatistics and economics and the emerging field of pred
arXiv:2606.22878v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed at the network edge to provide pervasive generative AI services, decentralized federated learn
arXiv:2606.20512v2 Announce Type: replace-cross Abstract: LLM-based coding agents need higher-level operational knowledge about a repository (which files house which subsystems, how to run the test su
arXiv:2606.22914v1 Announce Type: new Abstract: Activities in numerous evolving systems can be represented as dynamic graphs in snapshot form at different time intervals, i.e., discrete-time dynamic g