Knowledge catalogue
arXiv:2603.02678v3 Announce Type: replace Abstract: This paper argues for recognizing an emerging paradigm of causal learning by wisdom of the crowd. Recent developments in government, industry, and r
arXiv:2601.22427v2 Announce Type: replace-cross Abstract: Temporal link prediction is crucial for rapidly growing social networks. Existing methods often overlook the underlying causal mechanisms that
arXiv:2511.07055v3 Announce Type: replace Abstract: High-stakes decisions informed by decision support systems require explicit evidence. While prior work focuses on short sufficient evidence, regulat
arXiv:2605.10847v1 Announce Type: new Abstract: Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection f
arXiv:2602.07209v2 Announce Type: replace Abstract: Localization and mapping of an environment are crucial tasks for any robot operating in unstructured environments. Time-of-flight (ToF) sensors (e.g
arXiv:2605.10887v1 Announce Type: new Abstract: Open-world object counting remains brittle: despite rapid advances in vision-language models (VLMs), reliably counting the objects a user intends is far
arXiv:2605.10894v1 Announce Type: new Abstract: Deep learning models in medical imaging often fail when deployed in new clinical environments due to distribution shifts in demographics, scanner hardwa
arXiv:2605.10688v1 Announce Type: new Abstract: Event identification in continuous neural recordings is a critical task in neuroscience. Decoding in EEG is dominated by classifying windows aligned to
arXiv:2605.10166v1 Announce Type: new Abstract: Robotic imitation learning typically assumes access to optimal demonstrations, yet real-world data collection often yields suboptimal, exploratory, or e
arXiv:2605.08138v1 Announce Type: new Abstract: Synthetic data has emerged as a crucial solution to the data scarcity bottleneck in large language models (LLMs), particularly for specialized domains a
arXiv:2509.22531v2 Announce Type: replace-cross Abstract: In observational settings where treatment and outcome share unmeasured confounders but an observed mediator remains unconfounded, the front-do
arXiv:2605.09028v1 Announce Type: new Abstract: Machine learning-based Android malware detectors often fail in real-world deployment due to domain shift, where models trained on one data source perfor
arXiv:2510.07136v2 Announce Type: replace-cross Abstract: We study spectral graph clustering under edge differential privacy. We propose a matrix shuffling mechanism that combines randomized edge flip
arXiv:2605.08167v1 Announce Type: cross Abstract: The increasing availability of advanced image editing tools has led to a significant rise in manipulated digital content, posing serious challenges fo
arXiv:2605.09697v1 Announce Type: new Abstract: In many real-world computer vision applications, including medical imaging and industrial inspection, binary classification tasks are characterized by a
arXiv:2605.09719v1 Announce Type: cross Abstract: Large-scale 3D vision-language models (VLMs) like LLaVA-3D offer strong spatial reasoning but are difficult to deploy due to high computational costs.
arXiv:2605.08961v1 Announce Type: new Abstract: We present Dolphin-CN-Dialect, a streaming-capable ASR model with a focus on Chinese and dialect-rich scenarios. Compared to the previous version, Dolph
arXiv:2605.10765v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) achieve strong performance through instruction tuning, yet real-world deployment often requires continual cap
arXiv:2510.19414v2 Announce Type: replace-cross Abstract: The growing prevalence of speech deepfakes has raised serious concerns, particularly in real-world scenarios such as telephone fraud and ident
arXiv:2605.08273v1 Announce Type: cross Abstract: Accurate traffic prediction is essential for optimizing transportation systems, enhancing resource allocation, and improving overall urban administrat
arXiv:2509.21892v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models typically fix the number of activated experts k at both training and inference. However, real-world deployment
arXiv:2507.06658v2 Announce Type: replace-cross Abstract: Theories of democratic stability, populism, and party-system crisis often point to a form of polarization that comparative research rarely mea
arXiv:2604.16838v2 Announce Type: replace-cross Abstract: We present enclawed, a hard-fork hardening framework built on the OpenClaw AI assistant gateway. enclawed targets deployments that need attest
arXiv:2507.18847v3 Announce Type: replace-cross Abstract: We propose a new volumetric grasp model that is equivariant to rotations around the vertical axis, leading to a significant improvement in sam
arXiv:2605.09982v1 Announce Type: new Abstract: Recent advancements in Vision-Language Models (VLMs) enable large language models (LLMs) to process high-resolution images, significantly improving real
arXiv:2605.09181v1 Announce Type: new Abstract: Retinal image-based eye tracking is widely used in ophthalmic imaging and vision science, and is a promising path to deliver higher gaze accuracy than t
arXiv:2508.13434v2 Announce Type: replace-cross Abstract: Time series forecasting is vital in diverse sectors such as energy and transportation, where non-stationary dynamics are deeply intertwined wi
arXiv:2507.11185v2 Announce Type: replace-cross Abstract: Heart disease continues to pose a critical worldwide health issue, more specifically in areas with insufficient access to healthcare infrastru
arXiv:2605.08971v1 Announce Type: cross Abstract: Computer-Aided Design is ubiquitous in todays world, as almost every manufactured object begins as a digital model across industries. At the same time
arXiv:2509.21000v2 Announce Type: replace Abstract: Integer Linear Programs (ILPs) are central to real-world optimizations but notoriously difficult to solve. Learning to Optimize (L2O) has emerged as
arXiv:2602.07126v2 Announce Type: replace Abstract: Synthetic tabular data has gained attention for enabling privacy-preserving data sharing. While substantial progress has been made in single-table s
arXiv:2605.09277v1 Announce Type: new Abstract: We revisit combinatorial Thompson sampling (CTS) for semi-bandits with sleeping arms, where arm availability varies over time and actions must satisfy c
For a driver born without arms, FSD Supervised is life-changing accessibility “I was born without arms and have driven with my feet my entire life. I’m a fully licensed driver, and traditionally I dro
arXiv:2605.08140v1 Announce Type: cross Abstract: The Karlsruhe Tritium Neutrino Experiment (KATRIN) aims to measure the absolute neutrino mass with unprecedented sensitivity, requiring precise monito
arXiv:2605.10474v1 Announce Type: cross Abstract: Analog neural networks are gaining attention due to their efficiency in terms of power consumption and processing speed. However, since analog neural
arXiv:2605.10583v1 Announce Type: new Abstract: Despite extensive research on computed tomography (CT) denoising, few studies exploit projection-domain data characteristics to mitigate noise correlati
From a pure 'do good for the world' mission perspective, having the acting like a solid personalized tutor is one of the better uses of AI. If OpenAI cares about the mission of making the world a bett
arXiv:2605.10834v1 Announce Type: new Abstract: AI pentesting agents are increasingly credible as offensive security systems, but current benchmarks still provide limited guidance on which will perfor
arXiv:2605.08222v1 Announce Type: cross Abstract: Handwritten archival tables contain rich historical information, yet transforming them into structured representations, such as Knowledge Graphs, requ
arXiv:2405.09570v2 Announce Type: replace-cross Abstract: Heart murmurs are abnormal sounds caused by turbulent blood flow in the heart. Several diagnostic methods are available to detect heart murmur
gpt-realtime-2 is a great voice model (with a typically bad OpenAI name). Voice models are natively processing speech, not transcribing it, so the intelligence of the model matters. The old voice mode
Had an interesting exchange with roon of OpenAI last night over whether super intelligent AI would actually be able to navigate organizational challenges. @tszzl I think it is a reasonable argument to
arXiv:2605.10942v1 Announce Type: new Abstract: World Action Models (WAMs) have emerged as a promising paradigm for robot control by modeling physical dynamics. Current WAMs generally follow two parad
arXiv:2509.23668v3 Announce Type: replace Abstract: Time series forecasting occurs in a range of financial applications providing essential decision-making support to investors, regulatory institution
In this post, we demonstrate how Amazon FinTech teams are using Amazon Bedrock and other AWS services to build a scalable AI application to transform how regulatory inquiries are handled. Each team us
This OpenAI Academy article explores how finance teams leverage Codex, OpenAI's code generation model, to automate financial analysis, reporting, and data processing tasks. It likely covers practical
Sapu is an early-stage biopharmaceutical company developing treatments for hard-to-treat cancers. From its San Diego facility, the team is pioneering a nanomedicine pipeline that takes existing FDA-ap
Hewlett Packard Enterprise Co. today is expanding its hybrid cloud and data platform portfolio with new private cloud, storage and cyber resilience offerings designed to simplify infrastructure modern
I also agree with this comment that the current view of FDEs is likely too limited to actually catalyze organizational transformation. @emollick Are they doing org change, though? The army of forward
I think frontier model writing is good! It often has a sense of style & tone, variations in sentence structure & length, some great phrasing, etc But it also has some weak spots (fiction!) & clear tic
Before artificial intelligence can scale, governed enterprise AI has to prove it can be trusted. As companies move from pilots to production, the real test is whether platforms can bring automation, t
arXiv:2605.08180v1 Announce Type: cross Abstract: Modern IoT and sensor networks generate vast amounts of data, posing significant challenges for storage, transmission, and real-time processing. Tradi
arXiv:2601.21926v4 Announce Type: replace Abstract: Diffusion-based visuomotor policies built on 3D visual representations have achieved strong performance in learning complex robotic skills. However,
Pritam Biswas / Reuters: Isomorphic Labs, an AI-powered drug discovery spinoff from Google DeepMind, raised 2.1B led by Thrive, after raising 600M in its first round in March 2025 — Isomorphic Labs, a
arXiv:2601.22143v2 Announce Type: replace-cross Abstract: Audio-Visual Foundation Models, which are pretrained to jointly generate sound and visual content, have recently shown an unprecedented abilit
arXiv:2605.09440v1 Announce Type: cross Abstract: Clinical reports are often fragmented across healthcare institutions because privacy regulations and data silos limit direct information sharing. When
arXiv:2605.08635v1 Announce Type: new Abstract: Reconstructing dynamic 3D scenes from blurry monocular videos is challenging as motion-induced blur entangles object motion and geometry, hindering geom
arXiv:2605.09299v1 Announce Type: cross Abstract: Reconstructing 3D fluid velocity fields from sparse 2D video observations is a highly ill-posed inverse problem, demanding both transport consistency
arXiv:2605.10292v1 Announce Type: cross Abstract: Time series forecasting serves as an essential tool for many real-world applications, supporting tasks such as resource optimization and decision-maki
arXiv:2605.09382v1 Announce Type: cross Abstract: The Linear Assignment Problem (LAP) is a fundamental combinatorial optimization task with applications ranging from computer vision to logistics. Clas