Knowledge catalogue
arXiv:2602.15846v2 Announce Type: replace Abstract: Decoder-only large language models achieve strong broad performance but are brittle to minor grammatical perturbations, undermining reliability for
arXiv:2501.02450v2 Announce Type: replace Abstract: Collaborative perception significantly enhances autonomous driving safety by extending each vehicle's perception range through message sharing among
arXiv:2604.23010v1 Announce Type: new Abstract: High-quality 3D assets for traffic participants are critical for multi-sensor simulation, which is essential for the safe end-to-end development of auto
arXiv:2512.20220v2 Announce Type: replace Abstract: We study offline multitask reinforcement learning in settings where multiple tasks share a low-rank representation of their action-value functions.
arXiv:2604.24047v1 Announce Type: cross Abstract: Bregman divergences play a pivotal role in statistics, machine learning and computational information geometry. Particularly in the context of machine
arXiv:2604.22894v1 Announce Type: cross Abstract: Computed tomography (CT)-based attenuation and scatter correction improves quantitative PET but adds radiation exposure that is particularly undesirab
arXiv:2604.24188v1 Announce Type: new Abstract: Accurately estimating friction coefficients between arbitrary material pairs is critical for robotics, digital fabrication, and physics-based simulation
arXiv:2604.24536v1 Announce Type: new Abstract: Large Language Models (LLMs) excel academically but struggle with social intelligence tasks, such as creating good compromises. In this paper, we presen
arXiv:2512.00127v3 Announce Type: replace-cross Abstract: Getting language models to reason correctly about code requires training on data where each reasoning step can be checked. Current synthetic C
arXiv:2603.17834v2 Announce Type: replace-cross Abstract: Diffusion models and flow matching have become a cornerstone of robotic imitation learning, yet they suffer from a structural inefficiency whe
arXiv:2604.24322v1 Announce Type: new Abstract: The need to burn 100% H2 in high efficient gas turbines featuring low NOx combustion in premix mode require the complete redesign of the combustion syst
arXiv:2604.23904v1 Announce Type: cross Abstract: Synthetic data offers a promising tool for privacy-preserving data release, augmentation, and simulation, but its use in causal inference requires pre
arXiv:2604.07105v2 Announce Type: replace Abstract: We present Genie Sim PanoRecon, a feed-forward Gaussian-splatting pipeline that delivers high-fidelity, low-cost 3D scenes for robotic manipulation
arXiv:2604.23474v1 Announce Type: new Abstract: Forecasting systems in science must be accurate, physically consistent, and certifiably reliable. Most existing models address prediction, constraint en
arXiv:2510.07324v2 Announce Type: replace-cross Abstract: We derive a general system of ODEs and associated explicit solutions in a special case for geodesics between full rank matrices in the deep li
arXiv:2604.24238v1 Announce Type: new Abstract: Diffusion models are a leading paradigm for data generation, but training-free editing typically re-runs the full denoising trajectory for every edit st
arXiv:2604.23350v1 Announce Type: cross Abstract: Deep generative models and neural operators have demonstrated significant potential for 3D aerodynamic inference. However, they often face inherent ch
arXiv:2604.24469v1 Announce Type: cross Abstract: Content-based image retrieval (CBIR) systems enable users to search images based on visual content instead of relying on metadata. The text domain has
arXiv:2604.24016v1 Announce Type: new Abstract: We study offline-to-online learning in linear contextual bandits with biased offline regression data: the offline parameter need not match the online on
arXiv:2604.23651v1 Announce Type: new Abstract: Robust in-bed human pose estimation under blanket occlusion remains challenging due to the scarcity of reliable labeled training data for heavily covere
arXiv:2604.23888v1 Announce Type: cross Abstract: Adaptation of blackbox generative models has been widely studied recently through the exploration of several methods including generator fine-tuning,
arXiv:2604.23312v1 Announce Type: cross Abstract: Deep reinforcement learning policies achieve strong performance in complex continuous control environments with nonlinear contact forces. However, the
Vlad Fedorov / The GitHub Blog: GitHub addresses two recent incidents and says it aims to improve reliability amid AI growth, focusing on “availability first, then capacity, then new features” — Here'
GitHub is transitioning GitHub Copilot to a usage-based billing model to manage escalating AI inference costs. Effective June 1, subscribers will receive a set allotment of 'AI Credits'
arXiv:2604.23779v1 Announce Type: cross Abstract: The semantic gap between colloquial user queries and professional legal documents presents a fundamental challenge in Legal Case Retrieval (LCR). Exis
GLM 5.1 from @Zai_org is now available on @FireworksAI_HQ Training Platform across the Managed and Training API workflows. Try SFT and DPO with smart defaults or your own custom loss function with a 2
arXiv:2604.24396v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are frequently undermined by object hallucination--generating content that contradicts visual reality--due to an over-re
arXiv:2604.23941v1 Announce Type: new Abstract: Graphical User Interface (GUI) element grounding (precisely locating elements on screenshots based on natural language instructions) is fundamental for
This post by AI researcher Gary Marcus contrasts Google's original 'Don't Be Evil' corporate motto from 2001 with a critical question about the company's 2026 practices, likely arguing that Google has
* 본 아티클의 원문은 2026년 4월 23일 Google Cloud 블로그(영문)에 게재되었습니다. AI는 질문에 답하는 수준을 넘어 추론하고 행동하는 단계로 진화하고 있습니다. 오늘날의 에이전틱 시대(agentic era)를 선도하고자 하는 기업에는 이러한 새로운 요구사항에 맞춰 설계되고 최적화된 컴퓨팅 인프라가 필요합니다. 오늘 Google Cloud
Google has signed a classified deal that allows the US Department of Defense to use its AI models for 'any lawful government purpose,' The Information reports. The agreement was reported less than a d
In unseren Gesprächen mit Führungskräften aus Wirtschaft und öffentlichem Sektor in Deutschland und Europa taucht immer wieder dieselbe Frage auf: Wie lassen sich modernste Innovationen mit zuverlässi
Jay Peters / The Verge: Google launches Ask YouTube, a conversational AI search “experiment” that generates pages with videos and text summaries, for Premium users in the US aged 18+ — ‘Ask YouTube’ i
⚠️ Google’s Pentagon deal seems to allow for autonomous weapons and mass surveillance. ⚠️ According to the article, the deal allows for autonomous weapons and mass surveillance (in the common meaning)
LingBot-World-Fast successfully preserves the structural integrity and physical logic of the teacher model , achieving acceleration that introduces a necessary trade-off in theoretical upper-bound qua
arXiv:2604.24686v1 Announce Type: new Abstract: Autonomous AI agents can remain fully authorized and still become unsafe as behavior drifts, adversaries adapt, and decision patterns shift without any
arXiv:2511.09749v2 Announce Type: replace Abstract: Developing reliable iris recognition and presentation attack detection methods requires diverse datasets that capture realistic variations in iris f
arXiv:2604.24549v1 Announce Type: cross Abstract: Coordinating large populations of grid-edge devices requires learning methods that remain fully decentralised in deployment while still respecting thr
arXiv:2604.23523v1 Announce Type: cross Abstract: Safety specifications in cyber-physical systems (CPS) capture the operational conditions the system must satisfy to operate safely within its intended
arXiv:2604.24234v1 Announce Type: new Abstract: The technological maturity of in situ inspection and monitoring methods in additive manufacturing is steadily increasing, enabling more efficient and pr
arXiv:2604.23862v1 Announce Type: cross Abstract: We investigate whether the Feed-Forward Network (FFN) sublayer in a decoder-only transformer can be replaced by an explicit learned memory graph while
arXiv:2604.23626v1 Announce Type: new Abstract: LLM routing has achieved promising results in integrating the strengths of diverse models while balancing efficiency and performance. However, to suppor
This post discusses how large language models (LLMs) could serve as future chief financial officers, with Mercury as a platform enabling AI systems to manage finances and financial operations. The con
arXiv:2503.10666v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become widely used across various domains spanning search engines, code generation, and text creation. Howev
arXiv:2604.24700v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed, yet their outputs can be highly sensitive to routine, non-adversarial variation in how users p
arXiv:2604.23912v1 Announce Type: new Abstract: Learning low-dimensional representations from multi-view relational data is challenging when underlying geometries differ across views. We propose Bary-
arXiv:2604.24062v1 Announce Type: new Abstract: Extracting abstract causal structures and applying them to novel situations is a hallmark of human intelligence. While Large Language Models (LLMs) and
arXiv:2512.05359v2 Announce Type: replace Abstract: Parameter-efficient fine-tuning has emerged as a promising paradigm in RGB-T tracking, enabling downstream task adaptation by freezing pretrained pa
arXiv:2604.23675v1 Announce Type: cross Abstract: This work presents GS-DOT, a novel image reconstruction framework based on Gaussian Splatting (GS) for diffuse optical tomography (DOT). Inspired by G
arXiv:2604.23366v1 Announce Type: new Abstract: Autonomous multi-agent LLM systems are increasingly deployed to investigate operational incidents and produce structured diagnostic reports. Their trust
arXiv:2604.24551v1 Announce Type: cross Abstract: Quantum error mitigation (QEM) is essential for extracting reliable results from near-term quantum devices, yet practical deployments must balance mit
arXiv:2601.19906v2 Announce Type: replace-cross Abstract: Targeting error-tolerant applications, approximate computing relaxes rigid functional equivalence to significantly improve power, performance,
arXiv:2506.04118v3 Announce Type: replace Abstract: We propose Guided Speculative Inference (GSI), a novel algorithm for efficient reward-guided decoding in large language models. GSI combines soft be
arXiv:2604.24487v1 Announce Type: new Abstract: Guiding Vector Fields (GVFs) are a powerful tool for robotic path following. However, classical methods assume smooth, ordered curves and fail when path
arXiv:2501.07237v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated exceptional capabilities across diverse natural language processing benchmarks. However, the es
arXiv:2604.23134v1 Announce Type: new Abstract: Accurate molecular representations are critical for drug discovery, and a central challenge lies in capturing the chemical environment of molecular frag
arXiv:2604.23335v1 Announce Type: new Abstract: Knee osteoarthritis (KOA) is a degenerative joint disease that can lead to chronic pain, reduced mobility, and long-term disability. Automated severity
arXiv:2604.23665v1 Announce Type: new Abstract: Recent advances in representation learning have shown that hyperbolic geometry can offer a more expressive alternative to the Euclidean embeddings used
Harrison Chase discussed deep agents and LangChain's SDK for building autonomous agents on the Talk Python podcast (episode 543). The conversation likely covered LangChain's tools, capabilities, and b
arXiv:2604.22754v1 Announce Type: cross Abstract: No standardized benchmark exists for evaluating OCR on food packaging, despite its critical role in automated halal food verification. Existing benchm