Knowledge catalogue
arXiv:2607.00160v1 Announce Type: new Abstract: Modular reconfigurable robotic systems provide a scalable solution for cooperative surface operations in future lunar missions. However, cooperative car
arXiv:2607.00183v1 Announce Type: new Abstract: Adapting pre-trained text-to-image diffusion models, whether to learn new visual concepts or erase unwanted ones, is routinely evaluated on its intended
arXiv:2607.00870v1 Announce Type: new Abstract: We study inference-time pattern-memory gating in a production-scale clinical natural language processing (NLP) pipeline. The pipeline pairs a generator
arXiv:2603.27757v2 Announce Type: replace Abstract: Event-based cameras capture visual information as asynchronous streams of per-pixel brightness changes, generating sparse, temporally precise data.
arXiv:2508.11664v2 Announce Type: replace-cross Abstract: Sleep stage classification is critical for diagnosing and managing disorders like sleep apnea and insomnia. However, conventional methods like
arXiv:2412.20750v3 Announce Type: replace Abstract: Large-scale Vision-Language Models (VLMs) have achieved notable progress in aligning visual inputs with text. However, their ability to deeply under
arXiv:2607.00417v1 Announce Type: cross Abstract: In the era of satellite constellations, multi-view optical satellite imagery is pivotal for Earth Observation (EO) and high-quality Digital Surface Mo
arXiv:2507.02961v2 Announce Type: replace-cross Abstract: Modern transportation network modeling increasingly involves the integration of diverse methodologies including sensor-based forecasting, rein
arXiv:2607.00763v1 Announce Type: cross Abstract: Digital forensic investigations of network intrusions require analytical outputs that are traceable, reproducible, and court-defensible - requirements
NVIDIA Confidential Computing addresses data privacy and security concerns for AI workloads by protecting data during inference and engagement with models, offering high-performance protection in loca
arXiv:2607.00926v1 Announce Type: cross Abstract: Generalizing machine learning models to environments that differ from their training distribution remains a critical hurdle, particularly when data fr
arXiv:2603.16085v2 Announce Type: replace-cross Abstract: Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets. However, generating 3D compositional obje
arXiv:2506.12851v3 Announce Type: replace-cross Abstract: Humanoid robots are promising to acquire various skills by imitating human behaviors. However, existing algorithms are only capable of trackin
arXiv:2607.00228v1 Announce Type: cross Abstract: Modern time-domain surveys such as the Zwicky Transient Facility (ZTF) generate hundreds of thousands of alerts each night, making real-time decisions
arXiv:2607.00784v1 Announce Type: cross Abstract: Vision-language pretraining remains dominated by contrastive objectives, whereas vision-only self-supervised learning has largely adopted non-contrast
arXiv:2607.00385v1 Announce Type: cross Abstract: Automated malaria diagnosis from blood smear microscopy is a critical challenge in global health AI; in resource-limited settings, the scarcity of exp
arXiv:2601.11641v3 Announce Type: replace Abstract: While Diffusion Transformers (DiTs) have achieved notable progress in video generation, this long-sequence generation task remains constrained by th
arXiv:2607.00259v1 Announce Type: cross Abstract: Test-Time Adaptation (TTA) seeks to improve model robustness under distribution shifts by adapting parameters using unlabeled target data. However, in
arXiv:2607.00486v1 Announce Type: cross Abstract: Diffusion models are highly effective at modeling complex data distributions, including images and text. However, in applications like personalized re
.@Qualcomm is expanding its collaboration with @huggingface to scale open, developer-driven AI. From model onboarding to agentic workflows across edge and data center, this simplifies how developers b
Cognition AI announced a security vulnerability remediation program for Devin, their AI software engineer product, detailing procedures for reporting and addressing security issues. The program establ
arXiv:2607.00448v1 Announce Type: cross Abstract: The two-tower model has been widely used for large-scale recommendation systems, particularly in the retrieval stage. Industry standards for training
arXiv:2607.00310v1 Announce Type: cross Abstract: Foundation video diffusion models are increasingly viewed as world simulators for embodied agents, yet their pretraining on internet-scale generic vid
arXiv:2603.21573v2 Announce Type: replace Abstract: Existing visual privacy benchmarks largely treat privacy as a binary property, labeling images as private or non-private based on visible sensitive
arXiv:2607.01060v1 Announce Type: new Abstract: Video world models are emerging as a scalable alternative for evaluating generalist robot policies, bypassing the physical constraints and engineering b
arXiv:2607.00113v1 Announce Type: new Abstract: Background. Labeled data for security classification is scarce. Semi-supervised learning (SSL) propagates labels from a small labeled pool to larger unl
This article outlines three key questions organizations should address when scaling AI initiatives from pilot projects to production impact. Based on the Databricks focus, it likely covers questions r
arXiv:2607.01115v1 Announce Type: cross Abstract: University stakeholders often face difficulties in accessing timely and reliable information, especially in developing countries, where there are very
arXiv:2607.00736v1 Announce Type: new Abstract: Self-Supervised Monocular Depth Estimation (MDE) has garnered attention in recent years due to its independence from ground truth. However, most existin
🌍 World’s Largest Hermes Buildathon 10 cities. 5 countries. $750K credits Backed by OpenAI, Convex, Cloudflare, ElevenLabs, Linkup, Dodo Payments, Hissa Fund & Wispr Flow. Proudly presented by GrowthX
Opportunistic Expert Activation (OEA) is a batch-aware expert routing technique for mixture-of-experts models that enables faster decoding without requiring model retraining. The method optimizes whic
arXiv:2606.31639v1 Announce Type: cross Abstract: Large language models are no longer only text generators. They are increasingly embedded in retrieval pipelines, enterprise assistants, coding environ
arXiv:2509.15443v2 Announce Type: replace-cross Abstract: Human-to-humanoid imitation learning presents a promising pathway to address the severe data scarcity bottleneck in robotics by utilizing abun
arXiv:2606.30775v1 Announce Type: cross Abstract: Enterprise AI agents route user queries to specialized skills by matching queries against natural language skill descriptions. When two skills share o
arXiv:2606.31635v1 Announce Type: cross Abstract: Fault recovery in process plants still relies heavily on plant operators, especially when faults fall outside predefined supervisory logic. Operators
arXiv:2606.31958v1 Announce Type: new Abstract: Generalist robot policies learn a diverse repertoire of behaviors from large-scale pretraining. In principle, this makes them excellent priors for downs
AlloyDB is an AI-native database—it isn’t just a passive data store, it intelligently understands and processes your data. With AlloyDB, you get industry-leading vector and hybrid search, near 100% ac
arXiv:2606.31004v1 Announce Type: new Abstract: AI-generated video detection benchmarks such as GenVidBench and AIGVDBench are the de facto leaderboards, yet most evaluation protocols leave uncontroll
As enterprise generative AI transitions from simple, conversational chatbots to autonomous multi-agent workflows, developers face a critical bottleneck: scale. In a production environment, an enterpri
arXiv:2601.19506v4 Announce Type: replace Abstract: Blind face restoration remains a persistent challenge due to the inherent ill-posedness of reconstructing holistic structures from severely constrai
arXiv:2606.31371v1 Announce Type: cross Abstract: When large language model (LLM) agents adapt their behavior through evaluator feedback, systematic evaluator biases propagate into the agent's learned
arXiv:2606.31023v1 Announce Type: cross Abstract: Hard-constrained sequential decision systems have no certified way to spend the test-time compute of modern AI: executing the multi-step drafts of a l
arXiv:2606.31470v1 Announce Type: new Abstract: Cloud virtual machines are often overprovisioned, creating avoidable cost and operational inefficiency. We present CLOUDADV, an interactive engineer-fac
arXiv:2606.31718v1 Announce Type: cross Abstract: Relation extraction (RE) for low-resource languages is typically constrained by the lack of annotated corpora. We investigate the feasibility of cross
DigitalOcean has released Evaluations, a feature for testing production models and routers within their inference stack. This tool enables developers to validate and benchmark their AI/ML models befor
arXiv:2606.31918v1 Announce Type: new Abstract: A pivotal step in autonomous driving simulation involves inserting foreground vehicles with predefined trajectories into simulated scenes. This process
arXiv:2604.04834v2 Announce Type: replace Abstract: Robotic Vision-Language-Action (VLA) models generalize well for open-ended manipulation, but their perception is fragile under sensing-stage degrada
arXiv:2606.31982v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) incur prohibitive inference costs due to long visual token sequences. Training-free visual token reduction prov
arXiv:2606.30704v1 Announce Type: cross Abstract: Large language models (LLMs) excel across a wide range of tasks, yet their instance-specific solutions often lack the structural consistency needed fo
In this post, we demonstrate how to implement HippoRAG using a comprehensive AWS stack. We use Amazon Bedrock for LLM capabilities, Amazon Neptune for graph database functionality, Amazon Neptune Anal
arXiv:2606.12634v2 Announce Type: replace-cross Abstract: Long-horizon tool-use reinforcement learning learns from outcome verification, but trajectory-level advantages are broadcast over reasoning, A
arXiv:2606.31045v1 Announce Type: new Abstract: Scientific embodied agents are increasingly capable of carrying out laboratory procedures, but executing these procedures safely in dynamic laboratory e
arXiv:2606.31636v1 Announce Type: new Abstract: Despite rapid progress in learning-based stereo matching, high accuracy is often achieved at the cost of heavy backbones and computationally intensive 3
arXiv:2606.31644v1 Announce Type: new Abstract: As large language models take on morally consequential roles in healthcare, legal, and hiring contexts, we need to examine whether their ethical behavio
arXiv:2601.21173v2 Announce Type: replace-cross Abstract: With the rapid development of industrial intelligence and unmanned inspection, reliable perception and safety assessment for AI systems in com
NEW paper worth reading. (bookmark it) Autonomous research systems usually prove themselves on cherry-picked wins, human-framed topics, or a handful of preset tasks. FARS runs the full loop at scale i
arXiv:2606.31334v1 Announce Type: new Abstract: Joint OFDM-RIS optimization for 6G is a mixed-integer nonlinear programming (MINLP) problem covering sum-rate maximization, energy efficiency, max-min f
arXiv:2606.31349v1 Announce Type: cross Abstract: Surface electromyography (sEMG)-based gesture recognition has emerged as a promising technology for natural human-computer interaction. However, its p
arXiv:2606.31098v1 Announce Type: new Abstract: Real-time, drift-free UAV geo-localization is essential for autonomous missions in GNSS-denied environments. The pioneering system, PiLoT, achieves high
arXiv:2509.24575v2 Announce Type: replace-cross Abstract: This paper presents a framework to prompt multi-robot teams with high-level tasks using natural language expressions. Our objective is to use