Knowledge catalogue
arXiv:2605.27286v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) are transforming the forecasting paradigm through large-scale cross-domain pretraining. However, most existing T
Fast, faster, Qwen. 🚀 Thrilled to see Qwen3.5 reaching a record-breaking 580 tps for agentic workloads on the TokenSpeed engine! This milestone wouldn't be possible without our incredible partners. Hu
arXiv:2605.26615v1 Announce Type: new Abstract: Vision-language models such as CLIP have shown impressive capabilities in aligning images and text, but they often struggle with lengthy and detailed te
arXiv:2603.13282v2 Announce Type: replace-cross Abstract: Federated Learning (FL) with Low-Rank Adaptation (LoRA) has become a standard for privacy-preserving LLM fine-tuning. However, existing person
arXiv:2605.27351v1 Announce Type: new Abstract: 3D editing is a fundamental capability for scalable 3D content creation. While image editing has rapidly evolved toward large-scale feedforward generati
arXiv:2605.26589v1 Announce Type: cross Abstract: Childhood anemia affects around 40% of children aged 6-59 months globally and arises from heterogeneous factors, limiting model generalizability. We e
arXiv:2605.27284v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are increasingly expected to not only complete robot tasks, but also follow human instructions about how those tas
arXiv:2605.27333v1 Announce Type: new Abstract: Finance LLM agents must simultaneously block prompt-induced unauthorized actions and approve legitimate multi-step business workflows. However, boundary
First of all, all of this is open sourced. Even the binder design protocol [coming soon], which has been rigorously experimentally validated. Paper: https://biohub.ai/papers/esm_protein.pdf 🤗: https:/
Fleet agents can now securely write and run code. With computer use in LangSmith Fleet, agents get isolated execution environments. Analyze data, transform files, generate & write code, and run shell
Fleet agents now come with a computer! They can write and execute code, which is helpful for general purpose tasks beyond coding Fleet agents can now securely write and run code. With computer use in
arXiv:2603.17685v3 Announce Type: replace Abstract: Balancing policy expressiveness with the exploration-exploitation trade-off is a core challenge in online Reinforcement Learning (RL). While Stochas
arXiv:2602.01941v2 Announce Type: replace-cross Abstract: Autoregressive learning of time-stepping operators provides an effective approach to data-driven partial differential equation (PDE) simulatio
arXiv:2605.26423v1 Announce Type: new Abstract: Task-based fMRI provides a direct readout of task-evoked neural dynamics, but it is expensive and difficult to acquire at scale, motivating rest-to-task
arXiv:2605.26579v1 Announce Type: new Abstract: The open-ended generation in LLMs usually requires multi-dimensional rubrics to adequately assess quality and guide the improvement of reinforcement lea
For future-proof, build AI that's composable. Regardless of what you use, all these should be composable, iterative, and customizable: - LLMs - Evals - Automations - MCP/CLI tools - Skills/Memory/Cont
For over a decade, we’ve accepted that end-to-end backprop is the only way to train deep networks. But holding the entire network in memory all at once is why AI training is hitting a resource wall. W
AI adoption has become a culture shift for enterprises, moving beyond technical implementation to fundamentally reordering how organizations work, compete and grow. Few partnerships are better positio
In 2024, wind and solar energy sources generated more electricity than coal in the United States for the first time on record, marking a significant milestone in the nation's energy transition away fr
arXiv:2605.27161v1 Announce Type: new Abstract: This paper reports the core linguistic work performed to construct a dictionary-based morphological analyser for Malagasy simple verbs. It uses the Unit
arXiv:2605.26508v1 Announce Type: cross Abstract: We propose a foundational runtime actuarial layer for autonomous AI agents in which every side-effect-bearing action carries a time-consistent, counte
arXiv:2605.27178v1 Announce Type: cross Abstract: We address the challenging task of 3D object segmentation in complex scene point clouds without relying on any scene-level human annotations during tr
arXiv:2605.26273v1 Announce Type: new Abstract: Semantic segmentation in complex environments such as urban driving scenes remains challenging under adverse lighting conditions, where RGB images alone
arXiv:2605.25570v2 Announce Type: replace Abstract: Estimating continuous optical flow is a fundamental yet challenging problem in dynamic visual perception. Event-based cameras, with microsecond late
In this post, we show you how Verizon Connect built and scaled an agentic AI solution to transform overwhelming fleet data into clear, actionable insights for 100,000 users daily. We walk you through
arXiv:2605.26926v1 Announce Type: new Abstract: Computing legal indicators from normative texts is a key task in legal monitoring and policy evaluation, but presents significant challenges due to the
arXiv:2604.04948v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) systems depend critically on the quality of document preprocessing, yet no prior study has evaluated PDF
arXiv:2605.26222v1 Announce Type: new Abstract: Understanding the relationship between generalization and privacy remains a central challenge in modern machine learning theory, particularly for deep n
Production AI traces are the raw material for better evals, prompts, datasets, and fine-tuned models. This post shows how the Arize AX Airflow Provider turns that feedback loop into scheduled, monitor
arXiv:2605.27352v1 Announce Type: new Abstract: Discrete diffusion models have achieved strong empirical performance in text and other symbolic domains, but, especially for uniform-rate models, they o
arXiv:2605.26755v1 Announce Type: new Abstract: Multilingual fact verification requires evidence that is both relevant and sufficiently complete for reliable factuality prediction. However, existing s
arXiv:2605.26403v1 Announce Type: new Abstract: A long-standing goal of the research community is to develop highly interactive LLM-based dialogue agents. Recent research focuses on optimizing policie
arXiv:2605.26601v1 Announce Type: new Abstract: Vision-language models have progressed rapidly, but Tibetan remains a severely underserved low-resource language due to the lack of reproducible trainin
I can't provide a summary for this entry as the source URL appears to be invalid (the timestamp format doesn't match actual X/Twitter posts) and the title itself doesn't convey substantive information
arXiv:2605.26408v1 Announce Type: new Abstract: Causal discovery in time series is increasingly performed using nonlinear machine-learning models, yet the resulting causal relationships are almost alw
arXiv:2605.26158v1 Announce Type: cross Abstract: Safety alignment in large language models (LLMs) and multimodal large language models (MLLMs) is commonly assumed to operate as a near-binary threshol
arXiv:2605.27372v1 Announce Type: new Abstract: Modern feed-forward 3D reconstruction methods like VGGT predict pixel-aligned pointmaps in camera-centric coordinate frames. However, this choice of coo
arXiv:2605.26184v1 Announce Type: cross Abstract: Hybrid post-training usually combines supervised fine-tuning and reinforcement learning, but fixed mixing schedules cannot adapt when the relative noi
arXiv:2605.26391v1 Announce Type: cross Abstract: Practical garment design spans two modes: intuitive creation from high-level intent, such as a reference image or text description, and complex low-le
Gary's no way as bad as some people make him out to be. some data i shared yesterday on anthropic revenue possibly slowing down aren’t as a compelling as i thought; i have deleted my posts and await b
arXiv:2605.27093v1 Announce Type: cross Abstract: In probabilstic supervised learning of an input-output relationship - as a sample function of a Gaussian Process (GP) - priors are typically specified
arXiv:2605.26616v1 Announce Type: new Abstract: While 3D Gaussian Splatting has achieved remarkable success in photorealistic novel view synthesis, its pursuit of fast and high-fidelity 3D reconstruct
arXiv:2605.26121v1 Announce Type: cross Abstract: LLM pre-training efficacy increasingly depends on data composition rather than sheer volume. Yet, optimal mixing is hindered by categorization flaws:
arXiv:2605.27295v1 Announce Type: new Abstract: We introduce Gemini Embedding 2, a native multimodal embedding model that allows embedding video, audio, image, and text modalities in a unified represe
arXiv:2605.26857v1 Announce Type: new Abstract: Driven by the pressing demand for graph anomaly detection (GAD) in high-stakes domains, the generalist GAD paradigm, which trains a single detector tran
arXiv:2605.26823v1 Announce Type: new Abstract: Synthetic data offers a promising solution to two persistent barriers in supply chain analytics: data scarcity and data privacy. However, for synthetic
arXiv:2504.00307v2 Announce Type: replace Abstract: Improving the representation of precipitation in Earth system models (ESMs) is critical for assessing the impacts of climate change and especially o
arXiv:2605.27013v1 Announce Type: new Abstract: Mathematical optimization is a powerful tool for structured decision-making across domains such as resource allocation and planning. Formulating optimiz
arXiv:2605.27203v1 Announce Type: cross Abstract: Animation elevates digital documents into immersive experiences, yet creating custom motion paths remains cumbersome, requiring designers to manually
arXiv:2605.26769v1 Announce Type: cross Abstract: Generative artificial intelligence redefines higher education by restructuring the processes through which scientific knowledge is produced and valida
arXiv:2605.27360v1 Announce Type: cross Abstract: Cellular research and development (R&D) is throttled by six structural processes that each consume months of manual engineering work per iteration: (i
arXiv:2506.10225v2 Announce Type: replace-cross Abstract: Computational Music Generation is evolving towards non-conventional styles, demanding methods that enable precise and controllable blending of
arXiv:2605.26893v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) reasoning has advanced large language models (LLMs), but outcome-based supervision leads to pervasive post-hoc rationalization,
arXiv:2603.08413v2 Announce Type: replace-cross Abstract: Deep neural networks for image classification often exhibit overconfidence on out-of-distribution (OOD) samples. To address this, we introduce
arXiv:2605.26600v1 Announce Type: cross Abstract: Standard Self-Supervised Learning (SSL) for Automatic Modulation Recognition (AMR) struggles with ineffective isotropic augmentations, spectral instab
arXiv:2605.26230v1 Announce Type: new Abstract: Multi-view 3D reconstruction has achieved remarkable progress with the advent of feed-forward 3D reconstruction models. However, these models are typica
arXiv:2603.09551v2 Announce Type: replace Abstract: While Vision-Language Models (VLMs) have significantly advanced remote sensing interpretation, enabling them to perform complex, step-by-step reason
Get a state of the art protein structure prediction in just 9 lines of code. No MSAs needed. I'm so excited to show the world what we've been working on the for the past months!! I'm going to highligh
arXiv:2602.16449v2 Announce Type: replace-cross Abstract: Generative model evaluation commonly relies on high-dimensional embedding spaces to compute distances between samples. We show that dataset re
arXiv:2411.02355v4 Announce Type: replace-cross Abstract: Quantization is a powerful tool for accelerating large language model (LLM) inference, but the accuracy-performance trade-offs across differen