Knowledge catalogue
arXiv:2604.12041v1 Announce Type: cross Abstract: This work is concerned with the continuum limit of a graph-based data visualization technique called the t-Distributed Stochastic Neighbor Embedding (
arXiv:2603.23488v2 Announce Type: replace Abstract: Monocular novel-view synthesis has long required multi-view image pairs for supervision, limiting training data scale and diversity. We argue it is
arXiv:2604.12995v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly integrated into real-world decision-making, including in the domain of public policy. Yet, their ability t
arXiv:2604.11332v1 Announce Type: cross Abstract: Deep learning has markedly advanced image based plant disease diagnosis as improved hardware and dataset quality have enabled increasingly accurate ne
arXiv:2604.10116v1 Announce Type: cross Abstract: Major depressive disorder (MDD) is a prevalent mental disorder associated with complex neurobiological changes that cannot be fully captured using a s
arXiv:2604.09979v1 Announce Type: cross Abstract: Self-supervised representation learning is central to modern machine learning because it extracts structured latent features from unlabeled data and e
arXiv:2508.03793v2 Announce Type: replace Abstract: Long-context large language models (LLMs), such as Gemini-2.5-Pro and Claude-Sonnet-4, are increasingly used to empower advanced AI systems, includi
arXiv:2604.10173v1 Announce Type: cross Abstract: Magnetic point-group analysis classifies altermagnets but returns only a binary symmetry verdict, leaving spin-splitting energy (SSE) inaccessible wit
arXiv:2604.10963v1 Announce Type: new Abstract: Medical image segmentation supports clinical workflows by precisely delineating anatomical structures and lesions. However, medical image datasets medic
arXiv:2604.10882v1 Announce Type: cross Abstract: Graph Neural Network pretraining is pivotal for leveraging unlabeled graph data. However, generalizing across heterogeneous domains remains a major ch
arXiv:2502.18026v3 Announce Type: replace-cross Abstract: Retrieving targeted pathways in biological knowledge bases, particularly when incorporating wet-lab experimental data, remains a challenging t
arXiv:2604.10560v1 Announce Type: new Abstract: Profiled Sparse Networks (PSN) replace uniform connectivity with deterministic, heterogeneous fan-in profiles defined by continuous, nonlinear functions
arXiv:2604.10164v1 Announce Type: new Abstract: Reasoning on Temporal Knowledge Graphs (TKGs) is essential for predicting future events and time-aware facts. While existing methods are effective at ca
arXiv:2604.10643v1 Announce Type: new Abstract: Reliable confidence estimation is critical when deploying vision models. We study error prediction: determining whether an image classifier's output is
arXiv:2604.11178v1 Announce Type: cross Abstract: Forecasting neural activity in response to naturalistic stimuli remains a key challenge for understanding brain dynamics and enabling downstream neuro
arXiv:2604.10908v1 Announce Type: new Abstract: Every existing knowledge system separates storage from computation. We show this separation is unnecessary and eliminate it. In a standard triple is_a(A
arXiv:2604.11109v1 Announce Type: cross Abstract: As high-performance computing and AI workloads become increasingly dependent on GPUs, maintaining high performance across rapidly evolving hardware ge
arXiv:2508.11290v3 Announce Type: replace Abstract: LLMs increasingly exhibit over-refusal behavior, where safety mechanisms cause models to reject benign instructions that seemingly resemble harmful
arXiv:2604.11200v1 Announce Type: cross Abstract: Changes in input distribution can induce shifts in the average predictions of machine learning models. Such prediction shifts may impact downstream bu
arXiv:2604.11253v1 Announce Type: cross Abstract: Feature importance methods using unrestricted permutations are flawed due to extrapolation errors; such errors appear in all non-trivial variable impo
arXiv:2604.11685v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has become a state-of-the-art framework for real-time, high-fidelity novel view synthesis. However, its substantial storage
arXiv:2604.09649v1 Announce Type: cross Abstract: Brain-computer interfaces (BCIs) have opened new platforms for human-computer interaction, medical diagnostics, and neurorehabilitation. Wearable BCI
arXiv:2412.15803v2 Announce Type: replace-cross Abstract: Advancements in large language models (LLMs) have unlocked remarkable capabilities. While deploying these models typically requires server-gra
arXiv:2602.12748v3 Announce Type: replace Abstract: The explainable AI (XAI) research community has proposed numerous technical methods, yet deploying explainability as systems remains challenging: In
arXiv:2604.08749v1 Announce Type: new Abstract: How many of a neural network's parameters actually encode task-specific information? We investigate this question with LottaLoRA, a training paradigm in
arXiv:2604.09437v1 Announce Type: new Abstract: A novel regularization technique, AdaCubic, is proposed that adapts the weight of the cubic term. The heart of AdaCubic is an auxiliary optimization pro
arXiv:2604.08847v1 Announce Type: new Abstract: Deepfake detection has become a fundamental component of modern media forensics. Despite significant progress in detection accuracy, most existing metho
arXiv:2511.06756v3 Announce Type: replace Abstract: Over-smoothing remains a fundamental challenge in deep Graph Neural Networks (GNNs), where repeated message passing causes node representations to b
arXiv:2604.08644v1 Announce Type: new Abstract: This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integr
arXiv:2604.08664v1 Announce Type: new Abstract: Developing autonomous physical human-robot interaction (pHRI) systems is limited by the scarcity of large-scale training data to learn robust robot beha
arXiv:2604.09075v1 Announce Type: new Abstract: Large language models increasingly operate under multiple instructions from heterogeneous sources with different authority levels, including system poli
arXiv:2604.09263v1 Announce Type: cross Abstract: We consider machine learning tasks with low-rank functional tree tensor networks (TTN) as the learning model. While in the case of least-squares regre
arXiv:2604.08948v1 Announce Type: new Abstract: While Large Language Models (LLMs) excel in various general domains, they exhibit notable gaps in the highly specialized, knowledge-intensive, and legal
Harrison Chase, co-founder of LangChain, argues that while prompt engineering is foundational and can get you 80% of the way to a functional AI system, the remaining 20% of engineering effort involves
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This Reddit post on r/MachineLearning discusses the decision between pursuing a PhD versus a Master's degree for those interested in computational cognitive science, an interdisciplinary field combini
Harrison Chase, co-founder and CEO of LangChain, received positive feedback from a follower referencing a distinction he made at a Daytona conference, suggesting he regularly shares accessible and wel
LangChain's concept of 'your harness = your memory' explores how the surrounding infrastructure and framework around an AI agent effectively functions as its memory system. The post likely discusses h
arXiv:2509.01878v2 Announce Type: replace-cross Abstract: Marine ecosystems face increasing pressure due to climate change, driving the need for scalable, AI-powered monitoring solutions to inform eff
arXiv:2604.08063v1 Announce Type: new Abstract: Reconstructing visual stimuli from non-invasive electroencephalography (EEG) remains challenging due to its low spatial resolution and high noise, parti
arXiv:2604.07966v1 Announce Type: new Abstract: Diffusion models have achieved remarkable progress in video generation, but their controllability remains a major limitation. Key scene factors such as
arXiv:2502.17421v4 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) can now process extremely long contexts, efficient inference over these extended inputs has become increasingl
arXiv:2604.07803v1 Announce Type: cross Abstract: Computer vision, a core domain of artificial intelligence (AI), is the field that enables the computational analysis, understanding, and generation of
Want to know the latest from Google Cloud? Find it here in one handy location. Check back regularly for our newest updates, announcements, resources, events, learning opportunities, and more. Tip: Not
Anthropic's new hosted service for long-running AI agents, designed to solve the challenge of creating systems that support 'programs as yet unthought of.' It abstracts infrastructure management to en
Enterprises are rapidly moving AI workloads from experimentation to production on Google Kubernetes Engine (GKE), using its scalability to serve powerful inference endpoints. However, as these models
The founder of a $4B inference company says that if you're building agents, foundational models could become your IP. According to @lqiao, 90% of the world's data is still private and locked inside ap
Building and serving models on infrastructure is a strong use case for businesses. In Google Cloud, you have the ability to design your AI infrastructure to suit your workloads. Recently, I experiment
Hello guys, hoping you're doing fine. Today I want to share something that may affect your cards (? I have released 3 tools: A way to modify VBIOSes, so you can increase power limit, voltage, NVVDD of
Neuralink president DJ Seo says Elon’s aggressive schedules are rigorous first-principles engineering, and an all-green-light schedule shows 80 to 90% of delays are just assumed “What I’ve learned is
arXiv:2603.18838v2 Announce Type: replace Abstract: Striking an optimal balance between predictive performance and fairness continues to be a fundamental challenge in machine learning. In this work, w
arXiv:2610.21527v1 Announce Type: new Abstract: Layer normalization (LN) and root mean square normalization (RMSNorm) depend on their inputs and remain nonlinear at inference. Inserting either next to
Artificial intelligence agentic collaboration platform for multi-agent systems Thenovi AI Ltd., also known as Band, announced Thursday the launch of Band for Developers, a platform and new desktop app
arXiv:2610.21151v1 Announce Type: cross Abstract: Cybersecurity interviews uncover critical security experiences, behaviors, and privacy concerns often not fully captured by conventional technical ass
arXiv:2610.21138v1 Announce Type: new Abstract: Feedback noise is pervasive in preference data, arising from subjective human judgments, annotation mistakes, and imperfect LLM judges. Standard reward
arXiv:2610.20679v1 Announce Type: new Abstract: Representation-based safety defenses for vision-language models (VLMs) often learn to separate harmful from benign inputs, but separation alone does not
arXiv:2610.21368v1 Announce Type: cross Abstract: With the expansion of pre-trained language model usage in recent years, the importance of datasets for performing tasks in specialized domains has sig
arXiv:2610.20823v1 Announce Type: cross Abstract: A mesh of interceptors defending a fixed site must spread over the predicted arrival point of an approaching object. This is a recurring task in multi
arXiv:2610.21257v1 Announce Type: cross Abstract: Large Language Models (LLMs) demand efficient inference, where the multiply-accumulate (MAC) operations in linear projections dominate compute and ene