Knowledge catalogue
arXiv:2606.07289v1 Announce Type: cross Abstract: Model merging combines several independently fine-tuned experts into a single multi-task model without any training data, reducing the storage, servin
arXiv:2606.07107v1 Announce Type: new Abstract: Most vision-language-action (VLA) models map observations directly to actions without explicit intermediate planning, which limits performance on long-h
arXiv:2605.06215v2 Announce Type: replace-cross Abstract: Multiconfiguration pair-density functional theory (MC-PDFT) provides an efficient and accurate framework for computing electronic energies in
@cognition funny you should say that https://x.com/manuelsampedrop/status/2063746243180773656?s=20 @swyx @cognition hope it scores scope discipline too, half my agent failures are perfectly fine code
Coinbase : 'At Coinbase we're working hot on routing prompts to cheaper models where appropriate, & in some cases have been able to keep costs roughly flat, while token usage continues to grow exponen
arXiv:2606.07488v1 Announce Type: new Abstract: Personalized virtual heart simulations face challenges in model personalization and computational cost. While neural surrogates offer state-of-the-art s
arXiv:2606.06977v1 Announce Type: new Abstract: This work presents a compliance-based sensor placement method for force sensing on a sensorized prostate phantom designed for Digital Rectal Examination
arXiv:2601.09698v2 Announce Type: replace Abstract: 3D human pose estimation from sparse multi-view camera rigs is an essential task for numerous applications, including action recognition, sports ana
arXiv:2606.06725v1 Announce Type: cross Abstract: Myocardial perfusion quantification using contrast-enhanced ultrasound offers a bedside non-ionizing alternative to nuclear imaging modalities. Howeve
OpenAI submitted a confidential draft S-1 registration statement to the Securities and Exchange Commission, which is typically the first step toward a potential initial public offering (IPO). The conf
arXiv:2505.21423v3 Announce Type: replace Abstract: The remarkable generalization properties of overparameterized networks are often attributed to implicit biases, such as norm minimization at small l
arXiv:2408.15344v2 Announce Type: replace Abstract: Many scientific and engineering problems involve observing a common phenomenon through multiple heterogeneous sensors or measurement modalities. Suc
Information technology management software company ConnectWise Inc. today launched the ConnectWise Platform, a new operational platform for managed service providers that the company is positioning as
arXiv:2602.15287v2 Announce Type: replace Abstract: Text-to-video generation is expensive, so only a few samples are typically produced per prompt. In this low-sample regime, maximizing the value of e
arXiv:2606.07145v1 Announce Type: new Abstract: Text-guided diffusion models have become effective tools for real-image visual editing, where the edited image must follow a target instruction while pr
arXiv:2606.07058v1 Announce Type: cross Abstract: Variational autoencoders (VAEs) learn low-dimensional latent representations of high-dimensional data. When the data lies on a manifold with non-Eucli
arXiv:2606.06985v1 Announce Type: new Abstract: Code-switching (CS), the alternation between multiple languages within a single utterance, remains challenging for Automatic Speech Recognition (ASR). T
arXiv:2606.06543v1 Announce Type: cross Abstract: This study examines the coordinated optimization of departure sequencing and section-track allocation in railway short-term concentrated departure sce
arXiv:2506.11066v3 Announce Type: replace-cross Abstract: Code retrieval is essential in modern software development, as it boosts code reuse and accelerates debugging. However, current benchmarks pri
arXiv:2604.03779v2 Announce Type: replace-cross Abstract: Diffusion models have excelled at generative tasks for both continuous and token-based domains, but their application to discrete ordinal data
arXiv:2606.07382v1 Announce Type: new Abstract: We recast classical shrinkage of high-dimensional covariance estimators as empirical risk minimization over a parametric stochastic interpolant between
arXiv:2606.06842v1 Announce Type: new Abstract: Table reasoning remains challenging for large language models (LLMs), particularly in tasks that require multi-step inference over long and structured t
arXiv:2509.14380v3 Announce Type: replace Abstract: Multi-Agent Reinforcement Learning (MARL) provides a powerful framework for learning coordination in multi-agent systems. However, applying MARL to
arXiv:2512.09634v2 Announce Type: replace Abstract: This article presents the creation of an Estonian-language dataset for document-level subjectivity, analyzes the resulting annotations, and reports
arXiv:2606.06526v1 Announce Type: new Abstract: Large language models have made substantial progress on mathematical reasoning, but existing benchmarks typically evaluate well-specified problems with
arXiv:2606.07311v1 Announce Type: cross Abstract: As video generation models like Veo 3.1 and LTX-2 advance, their ability to accurately represent diverse global cultures remains a critical yet unders
arXiv:2603.19146v2 Announce Type: replace Abstract: Discrete diffusion models are promising alternatives to autoregressive approaches for text generation, yet their decoding methods remain under-studi
arXiv:2606.07366v1 Announce Type: new Abstract: Self-driving simulations typically rely on data collected in a small number of cities or on hand-authored synthetic scenarios. Dashcam videos cover a fa
arXiv:2606.06888v1 Announce Type: new Abstract: Classical scaling laws for language model pretraining balance model size against training dataset size under a fixed compute budget, assuming abundant d
arXiv:2606.06712v1 Announce Type: cross Abstract: We study the transformation of autoregressive models (ARLMs) into diffusion language models (DLMs). Rather than pretraining from scratch, prior work r
arXiv:2508.17693v2 Announce Type: replace-cross Abstract: Database normalization is crucial to preserving data integrity. However, it is time-consuming and error-prone, as it is typically performed ma
arXiv:2606.07001v1 Announce Type: cross Abstract: High-quality training data is essential to large language models (LLMs) and typically requires extensive and costly manual curation. Existing automati
arXiv:2606.06983v1 Announce Type: cross Abstract: Computational pathology requires visual representations that transfer across diverse clinical endpoints and remain robust to variation in magnificatio
arXiv:2606.07146v1 Announce Type: new Abstract: Physics-informed machine learning is often assessed by curve error, although engineering use depends on downstream decisions: ranking candidates, avoidi
arXiv:2606.06923v1 Announce Type: new Abstract: We study orchestration mechanisms for tool-using AI agents in realistic customer-service workflows over an unstructured knowledge base. We argue that de
Deep Agents are an AI concept that Sydney Runkle explains concisely in under 90 seconds, likely covering how agents can be designed to operate with deeper reasoning and decision-making capabilities. T
arXiv:2602.00163v2 Announce Type: replace Abstract: Hyperkinetic movement disorders (HMDs) such as dystonia, tremor, chorea, myoclonus, and tics are disabling motor manifestations across childhood and
arXiv:2606.06957v1 Announce Type: cross Abstract: Predicting outputs that are located in non-Euclidean spaces, such as probability distributions, networks, and symmetric positive-definite matrices, is
deepagent for competitive analysis Introducing 'Signals of AI' - DeepAgent powered by - @nebiustf for Inference - @NVIDIAAI Nemotron 3 Ultra - @tavilyai for Web Search - @LangChain for the core deepag
DeepAgents is a framework or tool designed to enable the creation of intelligent agents, likely demonstrated or explained in a brief 90-second format by Harrison Chase, a co-founder of LangChain. The
DeepSeek is increasing its presence in the AI inference market by competing for higher token volumes, while Anthropic maintains its leadership position in terms of overall spending. This analysis like
arXiv:2606.07226v1 Announce Type: cross Abstract: Human creativity has emerged as a critical competency in the era of large language models. Assessing creativity in complex, open-ended environments is
arXiv:2606.06107v1 Announce Type: cross Abstract: Quantum key distribution (QKD) is increasingly considered for deployment in realistic communication networks, where long distances, heterogeneous fibe
arXiv:2606.06555v1 Announce Type: cross Abstract: Noisy evolution strategies under fixed evaluation budgets face a depth-fidelity trade-off: spending evaluations to denoise intra-generation rankings r
arXiv:2603.24963v3 Announce Type: replace Abstract: Modern computational advertising platforms typically rely on recommendation systems to predict user responses, such as click-through rates, conversi
arXiv:2606.06514v1 Announce Type: new Abstract: Machine learning systems deployed in high stakes socioeconomic settings routinely display bias. We formalize bias as a symmetry breaking operation: a cl
arXiv:2606.07090v1 Announce Type: new Abstract: The rapid advancement of video editing and generative artificial intelligence technologies has made realistic video manipulation increasingly accessible
arXiv:2606.06890v1 Announce Type: new Abstract: Vision-Language Models (VLMs) frequently rely on language priors, producing confident answers that are weakly grounded in visual evidence. While this be
arXiv:2601.10896v2 Announce Type: replace Abstract: LLMs are increasingly used as third-party judges, yet their reliability when evaluating speakers in dialogue remains poorly understood. We show that
arXiv:2606.06518v1 Announce Type: new Abstract: Sudoku is a representative constraint satisfaction problem that requires global structural reasoning under strict discrete constraints. The existing wor
arXiv:2606.06942v1 Announce Type: cross Abstract: Policymakers in defence and defence-aligned sectors must monitor rapidly evolving research alongside sector priorities relevant to operational and str
arXiv:2606.07503v1 Announce Type: new Abstract: We propose Differences in Detection (DnD), an intuitive method to compare two object detection models. Based on the same matching algorithm, it compleme
arXiv:2606.07114v1 Announce Type: cross Abstract: Next-generation wireless networks, including satellite-to-Open RAN systems, demand agile and intelligent resource management capable of handling dynam
arXiv:2606.06601v1 Announce Type: cross Abstract: Object insertion aims to seamlessly composite a reference object into a specified region of a background image. Recent diffusion-based methods achieve
arXiv:2606.07356v1 Announce Type: cross Abstract: Text-guided audio editing aims to modify the language-specified acoustic content while preserving edit-irrelevant source components. Existing training
arXiv:2512.01362v2 Announce Type: replace Abstract: Neural prediction offers a promising approach to forecasting the individual variability of neurocognitive functions and disorders and providing prog
arXiv:2602.08857v2 Announce Type: replace-cross Abstract: Recent work has shown that the computations of Transformers can be simulated in the RASP family of programming languages. These findings have
arXiv:2606.07426v1 Announce Type: new Abstract: A fundamental problem in science is identifying underlying patterns of complex systems in the form of concise mathematical formulas. Current Artificial
arXiv:2606.07419v1 Announce Type: new Abstract: Recovering 3D human poses for multiple individuals from different camera views is a fundamental bottleneck for analyzing interacting behaviors. Existing
arXiv:2606.07379v1 Announce Type: cross Abstract: A growing failure mode in agent evaluation and training is that models can achieve high evaluation scores by exploiting shortcuts instead of solving t