Search: “persistence”

arXiv:2605.28515v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become an integral part of software development, especially with the advent of agentic capabilities. Yet, many front

arXiv:2605.27489v1 Announce Type: cross Abstract: Multi-agent LLM systems decompose workflows across agents, tools, shared context, memory, and decision gates. This modularity improves interpretabilit

arXiv:2605.28158v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly used to assist with operations research (OR) modeling, yet existing OR-oriented benchmarks often redu

arXiv:2605.27686v1 Announce Type: cross Abstract: Transformers process images and videos by flattening space and time into long token sequences. While attention and KV caching preserve past features,

arXiv:2605.28498v1 Announce Type: cross Abstract: Conversational artificial intelligence (AI) provides an efficient and convenient gateway to information access. However, it can cause overreliance whe

Bug fixes shipping to Grok Build 0.2.3 (release notes will be available in the TUI) - add “Yes, and don't ask again for anything (always-approve mode)' - add alpha/stable to welcome screen - JetBrains

arXiv:2605.26316v1 Announce Type: cross Abstract: Controllable and physically grounded egocentric video generation is essential for embodied agents to reason about how their own and others' actions ma

arXiv:2601.22384v2 Announce Type: replace-cross Abstract: Graphs provide a natural representation of relational structure that arises across diverse domains. Despite this ubiquity, graph structure is

arXiv:2605.27117v1 Announce Type: new Abstract: AI safety is still largely framed as alignment: training models to follow human preferences, safety policies, and normative constraints. That framing ha

arXiv:2605.24155v1 Announce Type: cross Abstract: Effective skills-aware talent recommendation must balance behavioral transition patterns, trajectory-sensitive adaptation, and inspectable occupation-

arXiv:2605.24775v1 Announce Type: new Abstract: Operating LLMs as coordinated multi-agent research systems over multi-hour runs surfaces failure modes that single-shot evaluation cannot: upstream prov

arXiv:2605.25435v1 Announce Type: new Abstract: The rapid evolution of large language model (LLM)-driven autonomous agents has given rise to OpenClaw, a new class of open-source agent frameworks that

arXiv:2605.24411v1 Announce Type: new Abstract: Existing language model applications struggle to meet the demand for emotionally oriented support, primarily due to their inability to maintain deep, pe

arXiv:2605.23889v1 Announce Type: new Abstract: Online 3D reconstruction requires estimating camera pose and scene geometry under strict causal and bounded-memory constraints. Existing methods often s

arXiv:2605.20282v1 Announce Type: new Abstract: Machine unlearning in Vertical Federated Learning (VFL) has attracted growing interest, yet existing methods certify forgetting solely using output-leve

arXiv:2605.20241v1 Announce Type: cross Abstract: Prompt-level safety probes for large language models use hidden-state representations to separate safe from unsafe prompts, but strong average detecti

arXiv:2605.20277v1 Announce Type: new Abstract: Medical vision-language models (VLMs) have rapidly advanced as general-purpose multimodal assistants, yet their deployment in 3D Computed Tomography (CT

arXiv:2605.16309v1 Announce Type: new Abstract: LLM-based agents can recover from individual execution errors, yet they repeatedly fail on the same fault when the underlying process knowledge--operato

arXiv:2605.18610v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown remarkable ability in aligning visual and textual representations, enabling a wide range of multimodal applic

arXiv:2601.14506v3 Announce Type: replace-cross Abstract: Large language models are increasingly deployed in STEM education for personalized instruction and feedback across institutions in high- and l

arXiv:2605.16348v1 Announce Type: cross Abstract: Training-free guidance enables pre-trained diffusion and flow models to optimize application-specific objectives using feedback from external black-bo

arXiv:2605.17444v1 Announce Type: cross Abstract: Modern software ecosystems face a rapidly growing number of disclosed vulnerabilities, increasing the need for automated repair techniques that can op

arXiv:2605.18553v1 Announce Type: cross Abstract: Recovering world space 4D motion of two interacting hands from egocentric video is a fundamental capability for supervising robot policy learning, whe

arXiv:2605.17821v1 Announce Type: cross Abstract: Large Language Model (LLM) training is frequently interrupted by a heterogeneous spectrum of failures, from common GPU crashes to catastrophic cluster

arXiv:2605.15779v1 Announce Type: cross Abstract: The integration of Unmanned Aerial Vehicles(UAVs) into Intelligent Transportation Systems (ITS) offers synoptic visibility for traffic monitoring, yet

arXiv:2605.15641v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as general planners in embodied intelligence, enabling high level coordination and low level task pla

arXiv:2605.14133v1 Announce Type: new Abstract: Interactive agent benchmarks face a tension between scalable construction and realistic workflow evaluation. Hand-authored tasks are expensive to extend

arXiv:2605.15042v1 Announce Type: cross Abstract: We propose EverAnimate, an efficient post-training method for long-horizon animated video generation that preserves visual quality and character ident

arXiv:2605.14218v1 Announce Type: new Abstract: The key problem facing ChatGPT-like AI's use across society is that its behavior can shift, unnoticed, from desirable to undesirable -- encouraging self

arXiv:2605.14421v1 Announce Type: cross Abstract: We introduce MemLineage, a defense for LLM agent memory that attaches both cryptographic provenance and LLM-mediated derivation lineage to every entry

arXiv:2605.14824v1 Announce Type: new Abstract: Topological clustering, and its main algorithm ToMATo, is a clustering method from Topological Data Analysis (TDA) which has been applied successfully i

arXiv:2605.15035v1 Announce Type: new Abstract: We introduce TopoPrimer, a framework that makes the global topological structure of the series population an explicit input to any forecasting model. To

Written by: Austin Larsen, Tyler McLellan, Genevieve Stark, Dan Ebreo Introduction Google Threat Intelligence Group (GTIG) has continued to track an expansive extortion campaign by UNC6671, a threat a

arXiv:2605.13520v1 Announce Type: cross Abstract: We address shortcomings of principal component analysis (PCA) for visualizing high-dimensional data lying on a nonlinear low-dimensional manifold via

arXiv:2406.13619v4 Announce Type: replace-cross Abstract: This paper develops a generative model by minimizing the second-order Wasserstein loss (the W_2 loss) through a distribution-dependent ordinar

arXiv:2605.13801v1 Announce Type: cross Abstract: As generative AI models such as large language models (LLMs) become more pervasive, ensuring the safety, robustness, and overall trustworthiness of th

arXiv:2605.13725v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent simulation offers a powerful testbed for studying social opinion dynamics. Yet current approaches often ado

arXiv:2506.17501v3 Announce Type: replace-cross Abstract: Following successful large-vessel recanalization via endovascular thrombectomy (EVT) for acute ischemic stroke (AIS), some patients experience

May 2026 update: We’ve refreshed this post to reflect our mid-cycle positioning and the evolution of our platform since the report was first published last November. Last fall, Google was recognized a

Every day, thousands of hours of new video content sits waiting to be discovered. Most of it lives in long-form, horizontal formats, while audiences are scrolling through vertical feeds on their phone

arXiv:2605.09869v1 Announce Type: cross Abstract: Zero-shot object navigation has advanced rapidly with open-vocabulary detectors, image--text models, and language-guided exploration. However, even af

arXiv:2605.10923v1 Announce Type: cross Abstract: Large language model agents increasingly rely on external skills to solve complex tasks, where skills act as modular units that extend their capabilit

arXiv:2605.10136v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) train a single neural approximation by minimizing multiple physics- and data-derived losses, but the gradients

arXiv:2605.10529v1 Announce Type: new Abstract: Biomedical knowledge graphs underwrite drug repurposing and clinical decision support, yet the upstream ontologies they depend on update on independent

arXiv:2504.04991v4 Announce Type: replace Abstract: Conventional visuomotor imitation learning usually predicts future robot actions directly in the time domain. Such formulations often have limited p

arXiv:2605.05995v2 Announce Type: replace-cross Abstract: The safety alignment of Large Language Models (LLMs) remains vulnerable to Harmful Fine-tuning (HFT). While existing defenses impose constrain