Knowledge catalogue
Shares of Nvidia Corp. and other tech firms dropped today following a report that OpenAI Group PBC had missed its growth targets last year. The Wall Street Journal late Monday cited sources as saying
Cisco Systems Inc.’s new Universal Quantum Switch introduced last week is a strong proof point regarding the network’s importance in scaling quantum. For information technology leaders, the key takeaw
arXiv:2604.22897v1 Announce Type: cross Abstract: Patent retrieval underpins critical decisions in innovation, examination, and IP strategy, yet progress has been hampered by the absence of benchmarks
arXiv:2602.23452v2 Announce Type: replace Abstract: Scientific research relies on accurate citation for attribution and integrity, yet large language models (LLMs) introduce a new risk: fabricated ref
Anthropic has launched a set of connectors for Claude that allow the AI chatbot to tap into popular creative software, including Adobe's Creative Cloud apps, Affinity, Blender, Ableton, Autodesk, and
arXiv:2604.23781v1 Announce Type: new Abstract: Language-model agents are increasingly used as persistent coworkers that assist users across multiple working days. During such workflows, the surroundi
arXiv:2604.23853v1 Announce Type: new Abstract: Skill-distillation pipelines learn reusable rules from LLM agent trajectories, but they lack a key signal: how much each step costs. Without per-step co
arXiv:2604.16922v2 Announce Type: replace Abstract: Climate research is pivotal for mitigating global environmental crises, yet the accelerating volume of multi-scale datasets and the complexity of an
arXiv:2510.22609v2 Announce Type: replace Abstract: Accurate symptom-to-disease classification and clinically grounded treatment recommendations remain challenging, particularly in heterogeneous patie
arXiv:2604.05500v2 Announce Type: replace Abstract: Nighttime image dehazing faces a more complex degradation pattern than its daytime counterpart, as haze scattering couples with low illumination, no
arXiv:2604.24044v1 Announce Type: new Abstract: Accurate 3D object detection is critical for autonomous driving, necessitating reliable, cost-effective sensors capable of operating in adverse weather
arXiv:2509.17314v3 Announce Type: replace-cross Abstract: Software increasingly relies on the emergent capabilities of Large Language Models (LLMs), from natural language understanding to program anal
arXiv:2303.05330v1 Announce Type: cross Abstract: Geo-distributed ML training can benefit many emerging ML scenarios (e.g., large model training, federated learning) with multi-regional cloud resource
arXiv:2604.24201v1 Announce Type: new Abstract: Motivation: Multi-omics integration can improve cancer subtyping, but modality informativeness and noise vary across cancer types and patients. Existing
arXiv:2604.23137v1 Announce Type: cross Abstract: Early detection and classifying brain tumors using Magnetic Resonance Imaging (MRI) images is highly important but difficult to extract in medical ima
arXiv:2601.22301v2 Announce Type: replace Abstract: Traditional rendering pipelines rely on complex assets, accurate materials and lighting, and substantial computational resources to produce realisti
arXiv:2604.23308v1 Announce Type: new Abstract: Offline multi-agent reinforcement learning (MARL) enables policy learning from fixed datasets, but is prone to coordination failure: agents trained on s
arXiv:2604.23088v1 Announce Type: cross Abstract: We present Code Broker, a multi agent system built with Google Agent Development Kit ADK that analyses Python code from files, local directories, or G
The rise of vibe coding is pushing software teams to build faster than ever before, but enterprise buyers demand systems that can survive audits and operational risk. The result is a new kind of softw
arXiv:2509.11717v5 Announce Type: replace-cross Abstract: Text-guided sound separation enables flexible audio editing, assistive listening, and open-domain source extraction, but systems such as Audio
arXiv:2604.22785v1 Announce Type: new Abstract: Large language model (LLM) deployments increasingly rely on multi-agent architectures in which multiple models either compete through routing mechanisms
arXiv:2604.22973v1 Announce Type: new Abstract: Predicting future trajectories of surrounding traffic agents is critical for safe autonomous navigation and collision avoidance. Despite all advances in
arXiv:2604.23003v1 Announce Type: new Abstract: In this paper, we propose a Physics-Informed Neural Network framework for time-dependent simulations of pollution propagation originating from moving em
arXiv:2604.23307v1 Announce Type: cross Abstract: Dual-target molecule generation, which focuses on discovering compounds capable of interacting with two target proteins, has garnered significant atte
ComfyStudio is open. We're launching a physical R&D studio and artist residency program in LA this May pairing working VFX artists, animators, and pipeline folks with the ComfyUI team to build hybrid
Building a robust AI foundation has become the decisive competitive advantage for insurers, yet most carriers are still wrestling with fragmented, siloed data spread across dozens of legacy systems an
arXiv:2604.23546v1 Announce Type: cross Abstract: Optical chemical structure recognition (OCSR) translates molecular images into machine-readable representations like SMILES strings or molecular graph
arXiv:2602.04753v2 Announce Type: replace-cross Abstract: An exponential growth of Machine Learning and its Generative AI applications brings with it significant security challenges, often referred to
arXiv:2604.23612v1 Announce Type: new Abstract: Partial Differential Equation (PDE)-based approaches have gained significant attention in image despeckling due to their strong capability to preserve s
arXiv:2604.22820v1 Announce Type: cross Abstract: Long-horizon tool-using tasks sometimes benefit from revisiting earlier subtasks for recovery and exploration, but added multi-agent workflow flexibil
arXiv:2604.23017v1 Announce Type: new Abstract: Stochastic Gradient Descent (SGD) is a known stochastic iterative method popular for large-scale convex optimization problems due to its simple implemen
arXiv:2604.24393v1 Announce Type: cross Abstract: There has been growing interest in studying the complexity of Rectified Linear Unit (ReLU) based activation networks. Recent work investigates the evo
arXiv:2604.23585v1 Announce Type: new Abstract: Financial institutions must track over 60,000 regulatory events annually, overwhelming manual compliance teams; the industry has paid over USD 300 billi
arXiv:2604.24648v1 Announce Type: new Abstract: Climate change and resource depletion demand a shift from the dominant linear 'take-make-use-dispose' paradigm of construction toward circular, low-wast
arXiv:2604.24634v1 Announce Type: cross Abstract: Light-activated drugs are a promising way to treat localized diseases for which existing treatments have severe side effects. However, their developme
arXiv:2604.24193v1 Announce Type: new Abstract: Containerised shipping underpins global trade, yet container loss at sea remains a persistent safety, environmental, and economic challenge. Despite com
arXiv:2604.23112v1 Announce Type: new Abstract: Multimodal Federated Learning (MMFL) enables privacy-preserving collaborative training, but real-world clinical applications often suffer from within-mo
arXiv:2604.23952v1 Announce Type: cross Abstract: Stochastic reduced-order models are widely used to represent the effective dynamics of complex systems, but estimating their drift and diffusion coeff
arXiv:2604.24745v1 Announce Type: new Abstract: In this paper, we propose a harmonized rotational gradient method, termed HRGrad, for simultaneously tackling multiscale time-dependent kinetic problems
arXiv:2604.22787v1 Announce Type: cross Abstract: Africa's green industrialization imperative demands reliable infrastructure for monitoring air quality. We present a satellite-reanalysis PM2.5 fusion
Congrats to @poolsideai on Laguna XS.2 release. Day 0 support in @vllm_project. FP8, INT4, and NVFP4 quantized checkpoints created with LLM Compressor also ready today. 33B params, 3B active. Apache 2
arXiv:2504.02316v4 Announce Type: replace-cross Abstract: Recent advances in zero-shot text-to-3D generation have revolutionized 3D content creation by enabling direct synthesis from textual descripti
arXiv:2309.00578v2 Announce Type: replace Abstract: In the context of unsupervised learning, Lloyd's algorithm is one of the most widely used clustering algorithms. It has inspired a plethora of work
arXiv:2604.23377v1 Announce Type: new Abstract: Neurosymbolic systems can satisfy logical constraints during learning without achieving the intended concept-label correspondence; this is a problem kno
arXiv:2604.23940v1 Announce Type: cross Abstract: Decompilation -- recovering source code from compiled binaries -- is essential for security analysis, malware reverse engineering, and legacy software
arXiv:2604.23949v1 Announce Type: new Abstract: Medical and public health experts must make real-time resource decisions, such as expanding hospital bed capacity, based on projected hospitalization tr
arXiv:2604.22801v1 Announce Type: cross Abstract: It is a challenging task to forecast equity prices in fast moving financial markets as this becomes even more difficult when the predictive signal is
A version of this article originally appeared on X. Every agent harness runs into the same limit: the context window is too small for everything the model might want to remember.... The post Context m
arXiv:2604.24693v1 Announce Type: new Abstract: Linear activation steering is a powerful approach for eliciting the capabilities of large language models and specializing their behavior using limited
arXiv:2604.23069v1 Announce Type: new Abstract: Large language model (LLM) agents often struggle in long-context interactions. As the agent accumulates more interaction history, context management app
arXiv:2604.23987v1 Announce Type: new Abstract: Continual learning for large language models is typically evaluated through accuracy retention under sequential fine-tuning. We argue that this perspect
arXiv:2604.23281v1 Announce Type: cross Abstract: Human activity recognition serves as the foundation for various emerging applications. In recent years, researchers have used collaborative sensing of
arXiv:2604.23039v1 Announce Type: new Abstract: Physical human-robot interaction offers the potential to leverage human intelligence and robot physical capabilities to enable a range of exciting appli
arXiv:2604.23179v1 Announce Type: cross Abstract: Monitoring human activity in indoor environments is important for applications such as facility management, safety assessment, and space utilization a
arXiv:2604.23863v1 Announce Type: new Abstract: Autonomous systems are increasingly deployed in real-world environments, where they must achieve high performance while maintaining safety under state a
arXiv:2410.13903v3 Announce Type: replace-cross Abstract: Proprietary large language models (LLMs) exhibit strong generalization capabilities across diverse tasks and are increasingly deployed on edge
arXiv:2601.14952v2 Announce Type: replace-cross Abstract: While large language models now handle million-token contexts, their capacity for reasoning across entire document repositories remains largel
arXiv:2604.24637v1 Announce Type: cross Abstract: Block-sequential continual learning demands that a single model both protect prior solutions from catastrophic forgetting and efficiently infer at inf
arXiv:2604.24008v1 Announce Type: new Abstract: Post-Training Quantization (PTQ) compresses large language models to low bit-widths using a small calibration set, and its quality depends strongly on w
arXiv:2604.24170v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) predict through human-interpretable concepts, but they typically output point concept probabilities that conflate epist