Knowledge catalogue
arXiv:2606.22296v1 Announce Type: new Abstract: Edge Internet of Things (IoT) agents are often constrained by memory capacity, privacy requirements, communication latency, and recurring inference cost
arXiv:2606.23567v1 Announce Type: new Abstract: Masked diffusion language models decode by iteratively unmasking tokens, where the unmasking order defines an 'order of thought' that strongly influence
arXiv:2602.12346v2 Announce Type: replace Abstract: Mutual information (MI) is a principled and widely used objective for robotic information gathering (RIG), providing strong theoretical guarantees f
arXiv:2606.13007v2 Announce Type: replace Abstract: Clustering is fundamental to scRNA-seq analysis, serving as a cornerstone for identifying cell populations and resolving tissue heterogeneity. Howev
arXiv:2606.21300v1 Announce Type: new Abstract: We present SCOPE (Scale-Consistent One-Pass Estimation of 3D Geometry), a novel approach for estimating 3D geometry from extended monocular video sequen
Jan Wolfe / Reuters: SCOTUS ends a suit alleging Cisco aided China's Falun Gong persecution, further limiting a law used to hold corporations liable for overseas human rights abuses — The U.S. Supreme
arXiv:2606.22700v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training without sharing raw data, making it a promising paradigm for privacy-sensitive applicatio
arXiv:2606.21326v1 Announce Type: cross Abstract: We present an ML-based vessel detection and localization system, trained with weak supervision from imperfect AIS labels, that achieves a 97.8% detect
arXiv:2606.15171v2 Announce Type: replace Abstract: Seams encode rich structural information about garments but are frequently partially observable in robotic manipulation scenarios. To robustly lever
arXiv:2606.21138v1 Announce Type: new Abstract: AI-assisted image editing threatens trust in financial, legal, and identity records. The GenText-Forensics Challenge at ACM MM 2026 addresses this by re
arXiv:2606.19120v2 Announce Type: replace-cross Abstract: On-policy self-distillation (OPSD) trains a model on its own rollouts and uses a frozen copy to provide dense token-level targets conditioned
arXiv:2606.22568v1 Announce Type: new Abstract: Training image generation foundation models consumes substantial resources. Previous methods have attempted to leverage semantic guidance to accelerate
arXiv:2606.17702v2 Announce Type: replace Abstract: Characterising the tumour microenvironment (TME) from routine H&E-stained histology images requires simultaneous cell segmentation, feature extracti
arXiv:2606.22350v1 Announce Type: new Abstract: Reinforcement Learning (RL) has been widely applied to sequential decision-making, yet it often suffers from poor sample efficiency due to costly intera
arXiv:2606.21929v1 Announce Type: new Abstract: Selective ensemble for modern machine learning systems requires choosing promising model candidates under limited evaluation budgets, while downstream t
arXiv:2606.23448v1 Announce Type: new Abstract: Deep learning methods have achieved state-of-the-art in time series forecasting, yet their accuracy varies considerably across samples, as some instance
arXiv:2602.21816v2 Announce Type: replace Abstract: Precise shape control of Deformable Linear Objects (DLOs) is crucial in robotic applications such as industrial and medical fields. However, existin
arXiv:2606.23112v1 Announce Type: new Abstract: Multi-turn tool-using agents must coordinate long-horizon tool sequences while tracking dialogue state and policy constraints. Existing approaches often
arXiv:2606.22449v1 Announce Type: cross Abstract: Current embodied world models are primarily optimized for predictive objectives, limiting their ability to generalize under distribution shifts and re
🧠Self-Harness: Harnesses that improve themselves New paper on agents shaping their own harnesses to improve over time. Not from LangChain, but builds on top of DeepAgents! Three key steps: 1/ Weakness
self-harness: harnesses that improve themselves spoiler alert, it's all loop engineering! 1. weakness mining - run agent and observe failures 2. propose improvements to the harness 3. confirm improvem
arXiv:2606.21090v1 Announce Type: cross Abstract: Self-improvement can self-regress. In REINFORCE post-training for code, a model can quickly improve on its optimized metric and then collapse within t
arXiv:2606.21027v1 Announce Type: new Abstract: Single-shot fringe projection profilometry (FPP) has been actively studied for real-time measurement, dynamic object reconstruction, and motion-sensitiv
arXiv:2606.22670v1 Announce Type: new Abstract: Autonomous exploration in unknown environments requires unmanned aerial vehicles (UAVs) to efficiently generate informative trajectories while simultane
arXiv:2606.23679v1 Announce Type: new Abstract: Modern text-to-image models excel in visual fidelity and prompt adherence. However, this strict adherence comes at the cost of diversity: generated samp
arXiv:2606.21493v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models enable robots to predict actions directly from visual observations and language instructions, but adapting them to n
arXiv:2503.16000v2 Announce Type: replace Abstract: We present extbf{SenseExpo}, a lightweight single-robot exploration framework that integrates a compact map prediction network into a frontier-based
arXiv:2606.22210v1 Announce Type: new Abstract: One of the powerful techniques in data modeling is accounting for features that are available at the training stage, but are not available when the trai
arXiv:2602.22747v2 Announce Type: replace Abstract: Epistemic uncertainty in neural networks is commonly modeled using two second-order paradigms: distribution-based representations, which rely on pos
arXiv:2606.18487v2 Announce Type: replace Abstract: The standard heuristic of selecting the SFT checkpoint with the highest pass@1 for GRPO can fail when SFT compresses the rollout distribution. For b
arXiv:2606.21716v1 Announce Type: new Abstract: The capability to encode spatially distinct magnetization patterns within soft materials enables remote control over complex deformations. This characte
In this post, you will learn patterns for implementing production-ready multi-tenant systems using Amazon Bedrock AgentCore. You will see these patterns demonstrated through healthcare AI agents that
Chipmaker Cerebras Systems Inc. delivered mixed results in its first earnings report since going public last month, beating Wall Street’s revenue projections but falling short on earnings, sending its
The national conversation about the value of education is currently dominated by speculation about the risks and positive potential of AI. Whatever your own perspective on that debate, I hope you’ll b
arXiv:2606.20684v1 Announce Type: new Abstract: Viewport-adaptive 360-degree imaging seeks to allocate a fixed sampling budget to the region a viewer is likely to observe. Existing view-biased project
arXiv:2505.11494v3 Announce Type: replace Abstract: Robot learning has produced remarkably effective ``black-box'' controllers for complex tasks such as dynamic locomotion on humanoids. Yet ensuring d
This article describes Hugging Face's automated weekly release process for the huggingface_hub library, which combines AI-assisted tools with human oversight to streamline software deployment. The app
arXiv:2606.20918v1 Announce Type: new Abstract: Accurate short-term electricity demand forecasting is critical for reliable power system operation, energy market planning, and infrastructure optimizat
Clem Delangue, CEO of Hugging Face, announced a new collaboration via video post on X/Twitter. The specific details of the collaboration partner and nature of the partnership are not visible from the
arXiv:2606.23152v1 Announce Type: new Abstract: We introduce ShotcreteDepth, a bi-modal dataset from the construction domain that captures both an active shotcreting process and general construction e
arXiv:2606.21099v1 Announce Type: new Abstract: Variational inference (VI) is a powerful method for principled posterior inference for scientific inverse imaging. VI learns the posterior distribution,
arXiv:2606.21875v1 Announce Type: cross Abstract: Modern data analysis usually gives a prediction without showing whether the evidence behind it is clear, conflicting, or stable. Two cases can have th
arXiv:2606.20857v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models enable robots to execute manipulation tasks from natural-language instructions grounded in visual observations. Ho
arXiv:2606.21085v1 Announce Type: new Abstract: Offline-to-online adaptation serves as a pivotal paradigm for mitigating the prohibitive cost of online exploration by bootstrapping reinforcement learn
arXiv:2312.07865v4 Announce Type: replace Abstract: Despite the success of diffusion-based customization methods on visual content creation, increasing concerns have been raised about such techniques
arXiv:2606.13589v2 Announce Type: replace Abstract: We present Simplex-Constrained Sparse Bagging (SCSB), a mathematically rigorous framework for post-training compression and probability calibration
arXiv:2510.02469v2 Announce Type: replace-cross Abstract: Driving scene manipulation using real-world sensor data has emerged as a promising alternative to traditional driving simulators. Despite adva
arXiv:2606.23536v1 Announce Type: new Abstract: We propose a method for estimating time-varying traffic flow patterns from sparse aggregated vehicle counts. The method partitions the study area into s
arXiv:2606.22873v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed in consumer, medical, financial, and enterprise applications. This broad deployment expands the
Single-shot generation still surfaces net-new kernels with no public reference: NeMo vocab-parallel log-probs, Hyena context parallelism, SAM 3 mask suppression. One GEMM + All-Gather kernel hit 87.9µ
arXiv:2603.05963v2 Announce Type: replace Abstract: Recent advances in large-scale pretrained vision models have demonstrated impressive capabilities across a wide range of downstream tasks, including
arXiv:2606.20659v1 Announce Type: cross Abstract: Agent skills encode reusable procedural knowledge that guides large language model agents across tasks and execution contexts. Existing evaluations pr
arXiv:2606.20636v1 Announce Type: cross Abstract: Computer-Use Agents (CUAs) are increasingly deployed in dynamic interactive environments, creating a growing need for continual skill learning during
arXiv:2606.23444v1 Announce Type: cross Abstract: Accurate dynamics models are critical for informed decision-making in robotic systems, particularly for agile aerial vehicles operating under uncertai
arXiv:2606.21096v1 Announce Type: new Abstract: Semi-supervised learning (SSL) on data streams is challenging due to the continuous evolution of high-volume data and the scarcity of labels. Existing m
arXiv:2606.14150v2 Announce Type: replace Abstract: Pruning promises a shortcut to strong small language models. In this work, we examine this promise by pruning Llama-3.1-8B at pruning ratios of 0.5-
Cybersecurity company Snyk Ltd. today launched Evo Agentic Development Security, a new layer of its artificial intelligence security platform built to police the autonomous coding agents that increasi
arXiv:2606.23357v1 Announce Type: new Abstract: Structured weight-uncertainty can improve many aspects of deep learning, but it remains costly to estimate and difficult to implement. Here, we show tha
arXiv:2606.21356v1 Announce Type: new Abstract: Many machine learning applications rely on heterogeneous event streams to make predictions, either causally as events arrive or bidirectionally over com
arXiv:2602.08690v2 Announce Type: replace Abstract: Deep Reinforcement Learning (DRL) has achieved remarkable success in domains requiring sequential decision-making, motivating its application to cyb