Knowledge catalogue
arXiv:2604.13245v1 Announce Type: new Abstract: Safe navigation for multi-robot systems requires enforcing safety without sacrificing task efficiency under decentralized decision-making. Existing dece
arXiv:2604.13471v1 Announce Type: new Abstract: In silico tools are important for generating novel hypotheses and exploring alternatives in de novo metabolic pathway design. However, while many comput
arXiv:2303.17674v5 Announce Type: replace-cross Abstract: We study the convex hulls of reachable sets of nonlinear systems with bounded disturbances and uncertain initial conditions. Reachable sets pl
arXiv:2511.13417v2 Announce Type: replace Abstract: Accurate delineation of agricultural field boundaries from satellite imagery is essential for land management and crop monitoring, yet existing meth
arXiv:2604.13995v1 Announce Type: new Abstract: This paper introduces a novel approach for image and video orientation estimation by leveraging depth distribution in natural images. The proposed metho
arXiv:2604.13416v1 Announce Type: new Abstract: Advances in radiance fields have enabled photorealistic novel view synthesis. In several domains, large-scale real-world datasets have been developed to
arXiv:2604.13841v1 Announce Type: new Abstract: Text-conditioned image editing has greatly benefitted from the advancements in Image Diffusion Models. However, extending these techniques to facial vid
arXiv:2604.13366v1 Announce Type: new Abstract: Accurate modeling of robot dynamics is essential for model-based control, yet remains challenging under distributional shifts and real-time constraints.
arXiv:2604.13899v1 Announce Type: new Abstract: Instruction-tuned LLMs can annotate thousands of instances from a short prompt at negligible cost. This raises two questions for active learning (AL): c
arXiv:2604.13230v1 Announce Type: new Abstract: Exploratory Landscape Analysis (ELA) provides numerical features for characterizing black-box optimization problems. In high-dimensional settings, howev
Ecom-RLVE is a framework for training e-commerce conversational agents using reinforcement learning with verifiable environments that can adapt to different scenarios. The system enables agents to lea
arXiv:2604.13685v1 Announce Type: cross Abstract: Deep learning-based surface electromyography (sEMG) gesture recognition is frequently bottlenecked by data scarcity and limited subject diversity. Whi
arXiv:2604.13410v1 Announce Type: cross Abstract: We study the problem of estimating the effect function for a continuous treatment, which maps each treatment value to a population-averaged outcome. A
arXiv:2511.21760v3 Announce Type: replace Abstract: Recent advances in multimodal large language models (LLMs) have enabled unified reasoning across images, audio, and video, but extending such capabi
Fundamental Truths in VC today (as I see them) 1/ The barbell between large and small firms is as wide as it's ever been. These are genuinely two distinct asset classes now, and LPs should treat them
arXiv:2510.02213v2 Announce Type: replace Abstract: Density map estimation enables accurate object counting in heavily occluded, and densely packed scenes where detection-based counting fails. In mult
Google DeepMind released MedGemma, a collection of medical vision-language foundation models based on Gemma 3 in 4B and 27B parameter sizes, demonstrating advanced medical understanding and reasoning
Editor’s note: Today we hear from Perry Nightingale, SVP of Creative AI at WPP about the workflow that cuts training time for humanoid robots from days to minutes — plus access to the open-source code
arXiv:2604.13179v1 Announce Type: cross Abstract: This paper presents HUANet, a constrained deep neural network architecture that unrolls the iterations of the Alternating Direction Method of Multipli
arXiv:2604.13728v1 Announce Type: cross Abstract: We present a hybrid retrieval system for COVID-19 scientific literature, evaluated on the TREC-COVID benchmark (171,332 papers, 50 expert queries). Th
“I am not able to do things that other dads can, now he thinks it’s so cool that I can do things other dads can’t” 🥹❤️ Life with ALS or a spinal cord injury often means navigating a gradual or sudden
arXiv:2604.13686v1 Announce Type: new Abstract: While Large Language Models (LLMs) have significantly advanced Text-to-SQL performance, existing benchmarks predominantly focus on Western contexts and
arXiv:2511.11334v3 Announce Type: replace Abstract: The rapid advancement of large language models (LLMs) has not been matched by their evaluation in low-resource languages, especially Southeast Asian
arXiv:2604.13979v1 Announce Type: new Abstract: Open-world Question Answering (OW-QA) over knowledge graphs (KGs) aims to answer questions over incomplete or evolving KGs. Traditional KGQA assumes a c
arXiv:2604.13695v1 Announce Type: new Abstract: Reliable and interpretable decision-making is essential in medical imaging, where diagnostic outcomes directly influence patient care. Despite advances
Thunderbolt is a new open-source AI client from Mozilla-owned MZLA Technologies aimed at enterprises who want to run self-hosted chatbots on their own infrastructure. The platform allows organizations
arXiv:2604.14075v1 Announce Type: cross Abstract: We introduce Multistage Conditional Compositional Optimization (MCCO) as a new paradigm for decision-making under uncertainty that combines aspects of
arXiv:2604.13919v1 Announce Type: cross Abstract: Computational fluid dynamics (CFD) has become an essential tool for predicting fire behavior, yet maintaining both efficiency and accuracy remains cha
OpenAI's Codex now features background computer use that lets multiple AI agents operate a Mac simultaneously without disrupting the user's own work. The update allows Codex to access all other apps o
The U.S. National Institute of Standards and Technology today announced an overhaul of how it processes cybersecurity vulnerabilities in its National Vulnerability Database . NIST is abandoning its lo
arXiv:2604.13681v1 Announce Type: cross Abstract: The node2vec random walk is a non-Markovian random walk on the vertex set of a graph, widely used for network embedding and exploration. This random w
arXiv:2408.10610v5 Announce Type: replace Abstract: We propose an L^2 norm for stationary Autoregressive Moving Average (ARMA) models. We look at ARMA models within the Hilbert space of the past with
arXiv:2604.13175v1 Announce Type: new Abstract: Large language models can be aligned with human preferences through offline reinforcement learning (RL) on small labeled datasets. While single-objectiv
arXiv:2604.13294v1 Announce Type: new Abstract: Existing video coding for machines is often trained for a specific downstream task and model. As a result, the compressed representation becomes tightly
arXiv:2604.13791v1 Announce Type: new Abstract: Accurate lesion segmentation in ultrasound images is essential for preventive screening and clinical diagnosis, yet remains challenging due to low contr
arXiv:2510.17043v2 Announce Type: replace Abstract: Advanced feature extraction methods have significantly contributed to enhancing the task of person re-identification. In addition, modifications to
arXiv:2604.13723v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) recast PDE solving as an optimisation problem in function space by minimising a residual-based objective, yet m
arXiv:2604.13064v1 Announce Type: new Abstract: Skill ecosystems have emerged as an increasingly important layer in Large Language Model (LLM) agent systems, enabling reusable task packaging, public d
arXiv:2604.13994v1 Announce Type: new Abstract: Generative diffusion priors have recently achieved state-of-the-art performance in natural image super-resolution, demonstrating a powerful capability t
arXiv:2604.13525v1 Announce Type: cross Abstract: The robust low-rank tensor completion problem addresses the challenge of recovering corrupted high-dimensional tensor data with missing entries, outli
arXiv:2511.14755v2 Announce Type: replace-cross Abstract: As perception-based controllers for autonomous systems become increasingly popular in the real world, it is important that we can formally ver
arXiv:2604.13817v1 Announce Type: new Abstract: Large language models (LLMs) have shown remarkable capabilities in dialogue generation and reasoning, yet their effectiveness in eliciting user-known bu
arXiv:2604.13941v1 Announce Type: new Abstract: Local feature matching plays a critical role in understanding the correspondence between cross-view images. However, traditional methods are constrained
Vercel's AI Gateway now supports Seedance 2.0, a video generation model that allows developers to create AI-generated videos through Vercel's unified API infrastructure. This integration enables users
arXiv:2604.13581v1 Announce Type: new Abstract: Accurately reconstructing human behavior in close-interaction scenarios is crucial for enabling realistic virtual interactions in augmented reality, pre
arXiv:2510.09541v3 Announce Type: replace Abstract: Diffusion large language models (dLLMs) are emerging as an efficient alternative to autoregressive models due to their ability to decode multiple to
arXiv:2602.06264v2 Announce Type: replace Abstract: We consider the problem of minimizing different notions of swap regret in online optimization. These forms of regret are tightly connected to correl
Auto-generated synthesis of 874 entries about arxiv-cs-cv
arXiv:2602.21627v3 Announce Type: replace Abstract: This paper presents a new unified approach to semantic segmentation in both images and videos by using language modeling to output the masks as sequ
arXiv:2604.14013v1 Announce Type: cross Abstract: We promote in this paper the processing of radar data in the frequency domain to achieve higher robustness against noise and structural errors, especi
arXiv:2604.14069v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection is a longstanding computer vision problem concerned with predicting the interaction between humans and objects.
This guide covers how to train and fine-tune multimodal embedding and reranker models using the Sentence Transformers library, enabling systems to work with both text and image data simultaneously. It
arXiv:2601.07422v2 Announce Type: replace Abstract: Despite their impressive capabilities, large language models (LLMs) frequently generate hallucinations. Previous work shows that their internal stat
arXiv:2604.14089v1 Announce Type: new Abstract: We present UMI-3D, a multimodal extension of the Universal Manipulation Interface (UMI) for robust and scalable data collection in embodied manipulation
arXiv:2511.23332v2 Announce Type: replace Abstract: Instruction-driven segmentation in remote sensing generates masks from guidance, offering great potential for accessible and generalizable applicati
arXiv:2604.13596v1 Announce Type: new Abstract: Instance-level object segmentation across disparate egocentric and exocentric views is a fundamental challenge in visual understanding, critical for app
arXiv:2604.13425v1 Announce Type: new Abstract: Video chroma-lux editing, which aims to modify illumination and color while preserving structural and temporal fidelity, remains a significant challenge
arXiv:2604.13610v1 Announce Type: new Abstract: In computer vision, a prevailing method for quantifying dataset bias is to train a model to distinguish between datasets. High classification accuracy i
arXiv:2604.12628v1 Announce Type: cross Abstract: Path-planning for autonomous vehicles in threat-laden environments is a fundamental challenge. While traditional optimal control methods can find idea
arXiv:2604.12211v1 Announce Type: new Abstract: Ollivier-Ricci curvature (ORC), defined via the Wasserstein distance that captures rich geometric information, has received growing attention in both th