All entries

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

Does a token buy you more or less now than it did a few months ago? We built a consumer price index (CPI) for AI coding output from Anthropic's Opus 4.6 model in SWE-chat, Feb 5–Apr 15, 2026. What we

arXiv:2606.07233v1 Announce Type: new Abstract: LiDAR-based 3D Multi-Object Tracking (MOT) typically relies solely on geometric information, which is often insufficient to distinguish between targets

arXiv:2606.06715v1 Announce Type: cross Abstract: We ask whether topic sentiment has a causal effect on perceived political ideology, and whether the answer depends on who assigns the ideology label.

Ideogram offers JSON prompting functionality that some users find powerful and useful, though others prefer natural language prompting interfaces. This post discusses a comparison between Ideogram and

arXiv:2606.06991v1 Announce Type: cross Abstract: Online Video Large Language Models (Video-LLMs) have advanced toward seamless human-AI interaction through frame-by-frame processing and proactive res

arXiv:2505.23131v2 Announce Type: replace Abstract: We study the problem of assigning operations in a dataflow graph to devices to minimize execution time in a work-conserving system, with emphasis on

arXiv:2606.07080v1 Announce Type: cross Abstract: We present dots.tts, a 2B-parameter continuous autoregressive text-to-speech (TTS) foundation model that models speech in a continuous latent space. C

arXiv:2606.07089v1 Announce Type: new Abstract: World Action Models (WAMs) offer a promising approach to embodied intelligence, yet existing methods rely heavily on video prediction as action priors a

arXiv:2606.06918v1 Announce Type: new Abstract: The rapid evolution of generative image models challenges existing AI-generated image detectors, particularly in open-world settings with unseen generat

arXiv:2606.07481v1 Announce Type: new Abstract: While Computational Fluid Dynamics (CFD) provides high-fidelity flow fields for optimizing indoor environments, its computational cost limits rapid expl

arXiv:2606.06537v1 Announce Type: cross Abstract: Breast cancer remains one of the leading causes of cancer-related mortality among women worldwide, making early detection essential for effective trea

arXiv:2602.00471v2 Announce Type: replace Abstract: While Visual Multi-Agent Systems (VMAS) promise to enhance comprehensive abilities through inter-agent collaboration, empirical evidence reveals a c

arXiv:2606.07222v1 Announce Type: cross Abstract: Cell detection in histopathology images strongly depends on surrounding tissue context, where visually similar cells may belong to different classes u

arXiv:2606.07299v1 Announce Type: new Abstract: Deep Research (DR) has emerged as a new agentic paradigm to tackle complex, open-ended research tasks, demanding systems that can iteratively frame prob

arXiv:2606.06515v1 Announce Type: cross Abstract: Transformer-based networks have emerged as prominent AI models with state-of-the-art performance, which potentially pave the way toward artificial gen

arXiv:2606.07108v1 Announce Type: new Abstract: Recent advances in Large Reasoning Models (LRMs) demonstrate remarkable performance improvements by iteratively reflecting, exploring, and executing com

arXiv:2601.16622v2 Announce Type: replace-cross Abstract: Equivariant Graph Neural Networks (EGNNs) have become a widely used approach for modeling 3D atomistic systems. However, mainstream architectu

Earlier today, New York University announced the creation of its new Earth Systems Institute—a multidisciplinary hub that will deploy AI and computational tools to better predict environmental changes

arXiv:2606.06906v1 Announce Type: cross Abstract: Long-context question answering (QA) remains challenging for smaller language models even when answer-bearing evidence is already present in the input

arXiv:2502.16531v2 Announce Type: replace Abstract: We consider multi-robot systems under recurring tasks formalized as linear temporal logic (LTL) specifications. To solve the planning problem effici