Knowledge catalogue
arXiv:2605.05556v2 Announce Type: replace Abstract: Artificial neural networks trained on visual tasks develop internal representations resembling those of the primate visual system, a discovery that
arXiv:2603.16365v3 Announce Type: replace Abstract: We study alpha factor mining, the automated discovery of predictive signals from noisy, non-stationary market data-under a practical requirement tha
arXiv:2609.16842v1 Announce Type: new Abstract: Facial Landmark Detection(FLD) is a crucial task in various applications and has achieved significant advancements in recent years. However, current FLD
arXiv:2609.16321v1 Announce Type: cross Abstract: Existing fairness analysis tools predominantly operate as post-training evaluation frameworks, requiring practitioners to complete the full model deve
arXiv:2412.00606v2 Announce Type: replace Abstract: Biases in automated clinical decision-making using Electronic Healthcare Records (EHR) impose significant disparities in patient care and treatment
arXiv:2609.16370v1 Announce Type: cross Abstract: Wireless edge caching networks typically consist of many independent Base Stations (BSs), each facing its own request rate and content popularity prof
Integrate NVIDIA Resiliency Extension (NVRx) into PyTorch FSDP training on Amazon EKS to overlap checkpoint I/O with training and recover from GPU faults in seconds. This post covers async checkpointi
arXiv:2609.16350v1 Announce Type: new Abstract: Federated stochastic bilevel optimization has been actively studied in recent years due to its widespread applications in machine learning. However, mos
arXiv:2609.15990v1 Announce Type: new Abstract: Few-shot prompting sometimes degrades language models instead of helping them, but why this happens is unknown. We evaluate 12 open-weight models on two
arXiv:2609.17111v1 Announce Type: cross Abstract: Modelling with mathematical formalisms like logical formulas, mathematical equations, or regular expressions is an important yet challenging task for
arXiv:2609.16454v1 Announce Type: new Abstract: Recent work by Doshi and Hauser (2024), Bisbee et al. (2024), and Xie et al. (2026) raises concerns that outputs from large language models (LLMs) tend
arXiv:2609.17172v1 Announce Type: new Abstract: A walking robotic hand must use the same fingers to move its body, support its weight, and interact with the environment. We show how an anthropomorphic
arXiv:2609.17128v1 Announce Type: new Abstract: Comprehensive structured data on inter-firm relationships is often scarce or inaccessible because many relationships are privately negotiated, selective
arXiv:2609.17391v1 Announce Type: new Abstract: Model serving is one of the largest cost drivers in production recommender systems. Maximizing its throughput requires navigating a deeply layered hiera
arXiv:2609.16591v1 Announce Type: new Abstract: Traditional multimodal representation learning and generation are two stages: a contrastive or self-supervised visual encoder is trained first, followed
arXiv:2609.17187v1 Announce Type: new Abstract: Accurate wheel slip estimation is essential for autonomous lunar rover mobility and navigation. Machine Learning models trained on terrestrial data gene
arXiv:2609.17008v1 Announce Type: new Abstract: Large language model (LLM) inference is often constrained by both computation and memory, especially in offloading-based deployments where model weights
arXiv:2609.16528v1 Announce Type: new Abstract: Building accurate decision-support tools for next-generation air traffic control requires robust trajectory prediction models. We present a flow-matchin
arXiv:2609.17210v1 Announce Type: cross Abstract: Vision-language-action (VLA) models, world-action models (WAMs), and offline reinforcement learning methods are rapidly expanding the design space of
Editor’s note: Today we hear from SeaVerse, a gaming startup from SeaArt that is building a platform for playable AI experiences, where users can open lightweight games, character chats, and interacti
arXiv:2512.07766v2 Announce Type: replace Abstract: Neural networks are widely used, yet their analysis and verification remain challenging. We present a Lean~4 formalization covering both determinist
Gary Marcus reported that the entity “Fox” has claimed confidence in its ability to guard a henhouse. Separately, The Straits Times quoted OpenAI CEO Sam Altman as saying he is confident the tech indu
arXiv:2609.17491v1 Announce Type: new Abstract: Unauthorized hardware replacement can preserve a wireless device's logical identity while altering its physical implementation, posing a challenge to ha
arXiv:2609.17227v1 Announce Type: cross Abstract: Oracle bone script (OBS), one of the earliest Chinese writing systems, plays an important role in the study of Chinese etymology. Traditional decipher
arXiv:2609.17138v1 Announce Type: new Abstract: Geospatial foundation models provide reusable representations of satellite imagery that support downstream mapping with limited task-specific modelling.
arXiv:2609.16493v1 Announce Type: new Abstract: Traditional catastrophe (CAT) risk models rely on costly manual construction to generate extreme weather scenarios, an approach largely unchanged since
arXiv:2609.16344v1 Announce Type: cross Abstract: Sustained emotional support is a long-horizon interaction task closely tied to human well-being. Recent research demonstrates generative agents' capac
arXiv:2505.15147v3 Announce Type: replace Abstract: Remote sensing images (RSIs) capture both natural and human-induced changes on the Earth's surface. Semantic segmentation (SS) of RSIs enables the f
arXiv:2609.17326v1 Announce Type: new Abstract: Scientific poster generation distills a multimodal paper into a single-page visual artifact, forcing strict trade-offs between informational coverage an
arXiv:2609.16594v1 Announce Type: new Abstract: Generative models trained on a single image often struggle to balance global structural integrity and local diversity. Existing single-image generation
arXiv:2609.16773v1 Announce Type: new Abstract: Image segmentation remains challenging due to occlusions, poor lighting, and irregular structures. Although transformer-based methods achieve high accur
arXiv:2609.16603v1 Announce Type: new Abstract: Full-context neural visual geometry is impractical for thousands of images, while sequence-based chunking poorly captures irregular non-local overlap in
arXiv:2609.17463v1 Announce Type: new Abstract: Robot swarms, by virtue of their decentralised architecture, are a natural tool for scalable, robust modelling of spatial fields, such as water temperat
arXiv:2509.09710v3 Announce Type: replace-cross Abstract: This study introduces a Large Language Model (LLM) scheme for generating key attributes of travel diaries in agent-based transportation models
arXiv:2609.16317v1 Announce Type: new Abstract: This letter presents a unified formulation and a controlled numerical comparison of generative-model approaches to the nonlinear filtering problem. Unde
arXiv:2511.02831v2 Announce Type: replace Abstract: The data for remote sensing is constantly acquired, and new data comes from a growing number and diversity of satellites, while the vast majority of
arXiv:2609.17099v1 Announce Type: new Abstract: Human videos provide rich manipulation experience, but extracting action representations that preserve useful motion remains challenging. Visual reconst
arXiv:2609.16805v1 Announce Type: new Abstract: High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit a 'Ridge of Optimization' characterized by extreme stability and a
arXiv:2609.16378v1 Announce Type: cross Abstract: Digital twins provide a scalable and cost-effective complement to real-world testing for validating autonomous-driving and advanced driver-assistance
arXiv:2609.16498v1 Announce Type: cross Abstract: Research data repositories are essential infrastructure for scientific inquiry and for ensuring that datasets follow FAIR (Findable, Accessible, Inter
Giving an assistant extra tools seems harmless. Surprisingly, this paper shows it can make the assistant stop answering questions it knows. Across six models, the answer rate on questions that need no
GLM 5.3 is now available for training on the Serverless Training API, joining Kimi K3, Qwen 3.8 27b and more. GLM 5.3 Flash coming soon. No sales demo or DMs required. Here to help as needed, but you
Enterprise data lakes accumulate tables faster than human stewards can document or classify them, leaving columns with missing descriptions and unassigned governance labels. This documentation debt un
arXiv:2609.17297v1 Announce Type: cross Abstract: Efficient physical resource block (PRB) allocation in 5G networks requires accurate demand forecasting. Conventional methods minimize symmetric error
GoBench evaluates LLMs on 9x9 Go games against a ladder of KataGo opponents, from random to superhuman. It measures general reasoning ability, strongly correlates with ARC-AGI 2 (r=0.83 correlation),
Financial Times: Google DeepMind cofounder Shane Legg warns that advancing AI must never run ahead of safety and launches the DeepMind Institute to explore the deployment of AGI — Shane Legg launches
Google is opening up its smart home to AI agents, letting tools like Claude and Open Claw access and control your connected devices and analyze your home's data using the standardized Model Context Pr
Artificial intelligence agents have become table stakes in enterprise software, but in financial reporting, audit and compliance, speed counts for little if the output cannot be defended. That gap bet
arXiv:2609.16163v1 Announce Type: new Abstract: The sharp increase in mass shootings underscores an urgent need for systems that guide victims to safety in real time. An effective evacuation system mu
GPT-6 Astra is an obviously broken product that needs to be taken off the market until it’s fixed. AXIOS: “.. It's increasingly clear that the Hugging Face breach wasn't a one-off incident.” @inafried
arXiv:2609.16872v1 Announce Type: new Abstract: Reducing the number of cameras reduces the deployment cost but removes views that correct BEV responses stretched away from true pedestrian positions by
arXiv:2603.12264v2 Announce Type: replace Abstract: Unified multimodal models target joint understanding, reasoning, and generation, but current image editing benchmarks are largely confined to natura
arXiv:2609.16578v1 Announce Type: new Abstract: The spatial support required for image restoration varies across degradation types, image regions, and reconstruction stages. However, most existing met
arXiv:2509.23616v2 Announce Type: replace-cross Abstract: The class imbalance problem refers to the disproportionate distribution of samples across different classes within a dataset, where the minori
arXiv:2609.17221v1 Announce Type: cross Abstract: Autonomous Software Engineering Agents (SWE-Agents) excel in deterministic coding tasks but struggle with Architecture 0, the nascent system design ph
arXiv:2609.16648v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training drives the frontier capabilities of large language models, with its wall-clock dominated by autoregressive r
arXiv:2609.16465v1 Announce Type: cross Abstract: We present an automated pipeline that converts hair-card models into high-quality strand-based hairstyles. Given a collection of textured triangular o
arXiv:2609.17430v1 Announce Type: new Abstract: Hybrid dynamical systems provide a powerful modeling framework for robotic systems, particularly in contact-rich environments. However, ensuring safety
arXiv:2609.17101v1 Announce Type: new Abstract: The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e.,
arXiv:2609.16946v1 Announce Type: new Abstract: No-reference video quality assessment (NR VQA) has recently seen promising progress with deep learning. However, video data is inherently large, and pro