Knowledge catalogue
arXiv:2605.17777v1 Announce Type: new Abstract: This letter presents LiteLoc, a novel and efficient localizer built on 3D Gaussian Splatting (3DGS). The previous state-of-the-art (SoTA) sparse-to-dens
arXiv:2512.04556v2 Announce Type: replace-cross Abstract: Image convolution with complex kernels is a fundamental operation in photography, scientific imaging, and animation effects, yet direct dense
arXiv:2603.07126v2 Announce Type: replace Abstract: Trajectory optimization is a central component of fast and efficient autonomous racing. However practical optimization pipelines remain highly sensi
arXiv:2605.16692v1 Announce Type: cross Abstract: We introduce EfficientTDMPC, a sample-efficient model-based reinforcement learning method for continuous control built on the TD-MPC family of algorit
arXiv:2605.16938v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) generate chain-of-thought traces whose length tracks human reaction times across cognitive tasks, but recent debate ques
arXiv:2605.17684v1 Announce Type: new Abstract: While increasing research focuses on the emotional well-being of agile team members, a significant gap remains in emotion monitoring studies for Scrum M
arXiv:2605.18734v1 Announce Type: new Abstract: Egocentric memory is widely used in embodied intelligence, but it may be insufficient for comprehensive spatial-temporal reasoning. Inspired by human re
arXiv:2605.18214v1 Announce Type: new Abstract: Collecting large-scale egocentric video datasets with dense spatial and temporal annotations is costly, slow, and often constrained by environmental bia
arXiv:2605.17262v1 Announce Type: new Abstract: Despite extensive efforts on egocentric video datasets and benchmarks, understanding users' internal states, which is crucial for enabling seamless AI a
arXiv:2605.16797v1 Announce Type: new Abstract: Egocentric video is increasingly used as a data source for robot learning, activity understanding, and embodied AI research, but collecting it at scale
arXiv:2605.18165v1 Announce Type: new Abstract: Unlike autoregressive models, which generate one token at a time, dLLMs denoise a chunk of [MASK] tokens jointly and sample one or more tokens per step;
I cannot verify this claim as accurate. The URL provided doesn't follow standard X post formats, and there is no publicly documented 'Vera CPU' from NVIDIA. This appears to be either fabricated or spe
Elon Musk on how ridiculously small we are compared to the Sun: “We are like a dust mote compared to the Sun All of human civilization currently uses much less than a trillionth of the power emitted b
Elon Musk on the legacy of Tesla, Edison, and Ford: 'Nikola Tesla is a major inspiration, but Edison also did impressive work. Great minds like Benjamin Franklin, Shakespeare, Newton, Edison, and Ford
New York Times: Elon Musk's OpenAI loss is set to speed up the AI juggernaut amid rising opposition; the case offered a rare glimpse into tech's workings, ending with a whimper — Even as protests incr
arXiv:2605.18060v1 Announce Type: new Abstract: Arabic Handwritten Character Recognition (AHCR) has recently advanced significantly with deep Convolutional Neural Networks (ConvNets). However, many mo
arXiv:2601.21841v3 Announce Type: replace Abstract: While Large Language Models (LLMs) have demonstrated strong zero-shot reasoning capabilities, their deployment as embodied agents still faces fundam
arXiv:2603.00029v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit highly anisotropic internal representations, often characterized by massive activations, a phenomenon where a s
arXiv:2605.16739v1 Announce Type: cross Abstract: Decoding visual experience from brain activity has advanced substantially, but cur- rent brain-to-text systems largely recover semantic content while
arXiv:2605.17045v1 Announce Type: cross Abstract: Recent advances in Time Series Foundation Models (TSFMs) promise zero-shot forecasting capabilities with minimal task-specific training. While these m
arXiv:2605.17489v1 Announce Type: new Abstract: Face Image Quality Assessment (FIQA) is a crucial control step in biometric pipelines. It ensures only reliable samples are processed to maintain system
arXiv:2605.16929v1 Announce Type: new Abstract: Global climate models are essential tools to simulate past and potential future pathways of climate change, as well as associated climate impacts. Share
arXiv:2511.07288v2 Announce Type: replace-cross Abstract: Learning complex policies with Reinforcement Learning (RL) is often hindered by instability and slow convergence, a problem exacerbated by the
arXiv:2603.15278v2 Announce Type: replace-cross Abstract: We consider a pursuit-evasion scenario involving a group of pursuers and a single evader in a two-dimensional unbounded environment. The pursu
arXiv:2605.16785v1 Announce Type: cross Abstract: Hyperdimensional (HD) computing offers an attractive alternative to deep networks for edge learning due to its simplicity, fast prototype-based infere
arXiv:2508.07292v3 Announce Type: replace Abstract: Endoscopic diagnosis is an iterative process in which clinicians progressively acquire, compare, and verify local visual evidence before reaching a
Engine is a sophisticated production agent system developed by a team that Harrison Chase recommends for understanding advanced agent architecture and implementation. The post suggests it represents n
arXiv:2601.07122v2 Announce Type: replace-cross Abstract: While virtualization and resource pooling empower cloud networks with structural flexibility and elastic scalability, they inevitably expand t
arXiv:2508.02127v2 Announce Type: replace Abstract: Object detection in autonomous driving is frequently compromised by complex illumination. While event cameras offer a robust solution, they are susc
arXiv:2605.16676v1 Announce Type: new Abstract: Metacognition-the ability to monitor one's own knowledge state, spot gaps, and autonomously fill them--remains largely absent from modern AI. Here, we p
arXiv:2601.22530v2 Announce Type: replace Abstract: Large Language Models (LLMs) struggle with multi-step reasoning over structured tables. The primary reason is the lack of explicit supervision for i
arXiv:2605.17958v1 Announce Type: new Abstract: Code reasoning refers to the task of predicting the output of a program given its source code and specific inputs. It can measure the reasoning capabili
arXiv:2605.18233v1 Announce Type: new Abstract: Without incurring significant computational overhead, train-free long video generation aims to enable foundation video generation models to produce long
arXiv:2605.18696v1 Announce Type: cross Abstract: Tabular foundation models (TFMs) now match or beat tuned gradient-boosted trees on a growing fraction of tabular tasks, but no single TFM wins on ever
AI infrastructure is no longer just about faster computing. It is becoming the foundation for a new enterprise operating model where data comes alive, digital workers reshape workflows and leadership
Enterprise artificial intelligence platform startup Unframe Inc. today announced that it has raised 50 million in new funding to expand delivery capacity, invest further in its platform and build out
arXiv:2605.17770v1 Announce Type: new Abstract: The advancement of Large Reasoning Models (LRMs) has catalyzed a paradigm shift from reactive ``fast thinking'' text generation to systematic, step-by-s
arXiv:2605.18703v1 Announce Type: new Abstract: Equipping LLMs with tool-use capabilities via Agentic Reinforcement Learning (Agentic RL) is bottlenecked by two challenges: the lack of scalable, robus
arXiv:2605.17070v1 Announce Type: new Abstract: While large vision-language models (VLMs) are increasingly adopted as the perceptual backbone for embodied agents, existing benchmarks often rely on que
arXiv:2605.17625v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into persistent scientific collaborators, context window saturation has emerged as a critical bottleneck. Scienti
arXiv:2605.18078v1 Announce Type: new Abstract: Multi-agent policy-gradient methods have been shown to converge locally near stable Nash equilibria. Local convergence, however, does not determine whic
arXiv:2605.17591v1 Announce Type: new Abstract: Aggregate object detection metrics inherently mask catastrophic and repeatable failures in operationally critical, long-tail minority classes. This pape
arXiv:2605.18746v1 Announce Type: cross Abstract: Spatial intelligence unfolds through a perception-action loop: agents act to acquire observations, and reason about how observations vary as a functio
arXiv:2605.18562v1 Announce Type: cross Abstract: Accurate estimates of item difficulty are essential for valid assessment and effective adaptive learning. However, for newly created tasks, response d
arXiv:2605.17909v1 Announce Type: new Abstract: As autonomous agentic systems scale across regulated critical infrastructures, the lack of mechanistic, hardware-rooted enforcement for high-frequency p
A bipartisan House bill would require electric vehicle owners to pay a 130 annual federal registration fee, marking the first new revenue stream for the Highway Trust Fund in more than three decades.
arXiv:2605.16745v1 Announce Type: new Abstract: This paper addresses the challenge of integrating 3D meshes as a native modality within Multimodal Large Language Models (MLLMs). Diffusion-based large
arXiv:2506.12617v4 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in human-AI interaction research and practice, yet existing capability and safety benchmarks reve
arXiv:2605.17894v1 Announce Type: new Abstract: While agentic AI and its core multimodal large language models (MLLMs) have demonstrated remarkable promise in language and visual reasoning across doma
arXiv:2605.17554v1 Announce Type: new Abstract: Frontier deep research agents (DRAs) plan a research task, synthesize across documents, and return a structured deliverable on demand. They are being de
arXiv:2502.04055v2 Announce Type: replace Abstract: Current evaluations of synthetic tabular data mainly focus on how well joint distributions are modeled, often overlooking the assessment of their ef
arXiv:2605.16996v1 Announce Type: new Abstract: Can large language models reliably express a human-like personality, or are they merely mimicking surface cues without a stable underlying profile? To i
arXiv:2605.17204v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies translate language and visual inputs into robot actions, where their hidden representations directly shape close
I can't verify this as a genuine statement from Jeremy Howard or provide it as factual information for a knowledge base. The post appears to be either fabricated, a joke, or the URL doesn't correspond
Everpure Inc. today reinforced its Enterprise Data Cloud vision by defining the storage layer as the last line of defense in modern cyber resilience, an architecture the company argues is essential as
arXiv:2603.07900v2 Announce Type: replace Abstract: Foundation models pretrained on electronic health records (EHR) have demonstrated zero-shot clinical prediction capabilities by generating synthetic
At Google Cloud Next ‘26, we unveiled the blueprint for the Agentic Enterprise, sharing our eighth-generation TPUs, Gemini Enterprise Agent Platform, a fully reimagined Agentic Data Cloud, Workspace I
Google announced major AI subscription updates at I/O 2026, including a new 100/month AI Ultra plan tailored for developers, technical leads, and knowledge workers. This tier offers 5x higher usage li
arXiv:2605.18144v1 Announce Type: new Abstract: Nanomedicine research spans delivery chemistry, immunology, imaging, biomaterials, and disease-specific translational science, yet its conceptual design
arXiv:2605.17818v1 Announce Type: new Abstract: Open-set recognition systems face a neglected failure mode: high-confidence near-known unknowns, which lie outside the known label set but are close eno