Search: “persistence”

Agent-ToM: Learning to Monitor Autonomous LLM Agents via Theory-of-Mind Reasoning

arXiv:2605.24216v1 Announce Type: cross Abstract: Monitoring autonomous large language model (LLM) agents for covert malicious behavior is challenging due to delayed, context-dependent, and long-horiz

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Agents

AGI Requires a Coordination Layer on Top of Pattern Repositories

DGX agent

arXiv:2512.05765v2 Announce Type: replace Abstract: In this paper we argue that influential critiques dismissing Large Language Models (LLMs) as a dead end for AGI misidentify the bottleneck: they con

agentsarxiv-cs-ai

26 May 2026

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents

model-releasesarxiv-cs-cl

arXiv:2605.25971v1 Announce Type: new Abstract: While AI agents demonstrate remarkable capabilities in reasoning and tool use, they remain fundamentally reactive: they compute responses only after exp

APT-Agent: Automated Penetration Testing using Large Language Models

arXiv:2605.24949v1 Announce Type: cross Abstract: Penetration testing is essential to securing modern web infrastructures, yet traditional manual methods struggle to keep pace with their scale and com

Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction

arXiv:2605.24657v1 Announce Type: new Abstract: Major LLM platforms deploy models in an inference-only configuration: the model serves requests but never updates per-user weights. Users must repeatedl

Applications

Beyond Static Uncertainty: Modeling Temporal Uncertainty Dynamics for Probabilistic Time Series Forecasting

arXiv:2603.24254v2 Announce Type: replace-cross Abstract: Real-world time series exhibit temporally structured uncertainty: volatility clusters in turbulent regimes, dissipates in stable periods, and

applicationsarxiv-cs-ai

CausaLab: A Scalable Environment for Interactive Causal Discovery Toward AI Scientists

arXiv:2605.26029v1 Announce Type: new Abstract: We introduce CausaLab, a scalable environment for evaluating interactive causal discovery by LLM agents. Unlike prior evaluations, CausaLab evaluates bo

Do Understanding and Generation Fight? A Diagnostic Study of DPO for Unified Multimodal Models

arXiv:2603.17044v2 Announce Type: replace-cross Abstract: Unified multimodal models share a language model backbone for both understanding and generating images. Can DPO align both capabilities simult

DRInQ: Evaluating Conversational Implicature with Controlled Context Variation

model-releasesarxiv-cs-cl

arXiv:2605.24267v1 Announce Type: new Abstract: Human conversation relies heavily on conversational implicature, in which speakers convey meanings that are suggested rather than explicitly stated. Alt

EvoCode-Bench: Evaluating Coding Agents in Multi-Turn Iterative Interactions

arXiv:2605.24110v1 Announce Type: new Abstract: Coding agents are increasingly used as iterative development partners, but most benchmarks still evaluate one specification followed by one final assess

Evolutionary Physics-Informed Temporal Fusion for Lane-Change Intention Prediction

arXiv:2512.24075v5 Announce Type: replace Abstract: Early lane-change intention prediction is essential for autonomous driving and ADAS, but it remains challenging because lane-changing behavior depen

agentsarxiv-cs-lg

Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay

arXiv:2605.26097v1 Announce Type: new Abstract: Models trained on a new task typically degrade on prior tasks, a phenomenon known as forgetting. Traditionally, mitigating forgetting has required repla

From Multi-Agent Systems and the Semantic Web to Agentic AI: A Unified Narrative of the Web of Agents

arXiv:2507.10644v4 Announce Type: replace Abstract: The Web of Agents (WoA) transforms the document-centric Web into an environment of autonomous agents acting on users' behalf, a vision newly tractab

FuXi-Nowcast: Environment-conditioned deep learning for severe convection nowcasting

arXiv:2512.08974v2 Announce Type: replace-cross Abstract: Severe convection produces localized hazards that often require warnings before radar echoes fully reveal storm development. Convective initia

Hadamard Representation: Scaffolding Performance Across Model-free RL

model-releasesarxiv-cs-lg

arXiv:2406.09079v5 Announce Type: replace Abstract: Deep reinforcement learning agents progressively lose representational capacity during training: neurons become dormant, removing active capacity fr

HeartBeatAI: An Interpretable and Robust Deep Learning Framework for Multi-Label ECG Arrhythmia Detection

arXiv:2605.24588v1 Announce Type: new Abstract: While Deep Learning (DL) enhances automated electrocardiogram (ECG) analysis, clinical deployment is hindered by class imbalance and the generalization

INDUCTION: Finite-Structure Concept Synthesis in First-Order Logic

arXiv:2602.18956v3 Announce Type: replace Abstract: We introduce INDUCTION, a benchmark for finite structure concept synthesis in first order logic. Given small finite relational worlds with extension

Insuring Every Action: An Authority Frontier Framework for Runtime Actuarial Control of Autonomous AI Agents

arXiv:2605.25632v1 Announce Type: new Abstract: Autonomous AI agents increasingly issue side-effect-bearing actions: database mutations, refunds, payments, external commitments. We propose the Actuari

Is Decentralized AI Governable? From Regulative Policy to Constitutive Protocol

arXiv:2605.24538v1 Announce Type: cross Abstract: Every major framework for governing artificial intelligence presupposes an identifiable entity -- a developer, deployer, or operator -- who can be hel

KYA: A Framework-Agnostic Trust Layer for Autonomous Systems with Verifiable Provenance and Hierarchical Policy Composition

arXiv:2605.25376v1 Announce Type: cross Abstract: Observability tells operators when an agent is slow. KYA tells operators when an agent is wrong, drifting, leaking, or quietly going rogue. We present

Local Ai

Language Models Need Sleep

arXiv:2605.26099v1 Announce Type: cross Abstract: Transformer-based large language models are increasingly used for long-horizon tasks; however, their attention mechanism scales poorly with context le

local-aiarxiv-cs-ai

Tutorials

// Language Models Need Sleep // Let your agents 'sleep', folks. On a serious note, this is a fascinating paper on getting the most from lon…

// Language Models Need Sleep // Let your agents 'sleep', folks. On a serious note, this is a fascinating paper on getting the most from long-horizon agents. Here is the problem with agents today: Att

tutorialsdair-ai--x

LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization

model-releasesarxiv-cs-ro

arXiv:2510.03827v2 Announce Type: replace-cross Abstract: LIBERO has emerged as a widely adopted benchmark for evaluating Vision-Language-Action (VLA) models; however, its current training and evaluat

LipoAgent: Coordinating Fine-Tuned LLM Agents for Safer Lipid Design

arXiv:2605.25250v1 Announce Type: new Abstract: Lipid nanoparticles (LNPs) are among the most clinically mature platforms for nucleic acid delivery, yet designing lipids that are both effective and bi

LRDDv3: High-Resolution Long-Range Drone Detection Dataset with Range Information and Thermal Data

arXiv:2605.25942v1 Announce Type: cross Abstract: Unmanned Aerial Vehicles (UAVs) have quickly become common in various airspaces, representing a wide range of applications from recreation flying to c

researcharxiv-cs-ro

Memory-Induced Tool-Drift in LLM Agents

model-releasesarxiv-cs-lg

arXiv:2605.24941v1 Announce Type: cross Abstract: Modern LLM agents combine long-term memory for personalization with tool-calling interfaces for taking actions in the world -- a combination underpinn

Meta-Engineering Harnesses for AI-Native Software Production: A Contract-Driven Adversarial Verification Architecture with Early Deployment Report

arXiv:2605.25665v1 Announce Type: cross Abstract: AI-native software development is often evaluated at the level of individual models, prompts, or generated artifacts. This framing is insufficient for

Micro-Swarm Locomotion Optimization in Dynamic Flow using Multi-Objective Multi-Agent Reinforcement Learning

arXiv:2605.25025v1 Announce Type: new Abstract: Coordinating micro-robotic swarms in physiologically realistic, time-dependent fluid environments remains an unsolved challenge for biomedical and envir

safetyarxiv-cs-ro

On the Epistemic Uncertainty of Overparametrized Neural Networks

arXiv:2605.25234v1 Announce Type: cross Abstract: Epistemic uncertainty is often viewed as a reducible uncertainty that vanishes with increasing data. This perspective implicitly assumes parameter ide

Overview of the PsyDefDetect Shared Task at BioNLP 2026: Detecting Levels of Psychological Defense Mechanisms in Supportive Conversations

model-releasesarxiv-cs-cl

arXiv:2605.24907v1 Announce Type: new Abstract: We present an overview of PsyDefDetect, the shared task on detecting levels of psychological defense mechanisms in emotional support dialogues, co-locat

ParkingWorld: End-to-End Autonomous Parking Reinforcement Learning from Corrective Experience in 3DGS Simulation

arXiv:2605.25029v1 Announce Type: new Abstract: Autonomous parking demands precise low-speed maneuvering within narrow, cluttered, and highly constrained environments, where vehicles must navigate tig

safetyarxiv-cs-ro

Practical Quantum CIM Empowerment via All-Domestic-Core Agentic Large Model

arXiv:2605.23934v1 Announce Type: new Abstract: Quantum computing devices are recognized as powerful tools for solving NP-complete problems. However, the intricacy of their modeling presents notable b

Quantifying Empirical Compute-Supervision Tradeoffs in RLVR

arXiv:2605.25252v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard paradigm for post-training language models, but in practice, verifiers are

Retrieval as Reasoning: Self-Evolving Agent-Native Retrieval via LLM-Wiki

arXiv:2605.25480v1 Announce Type: new Abstract: LLM agents require retrieval to behave less like one-shot context fetching and more like reasoning: searching, reading, traversing, and deciding when ev

agentsarxiv-cs-cl

Scaling Natural-Language Graph-Based Test Time Compute for Automated Theorem Proving

arXiv:2503.11657v3 Announce Type: replace Abstract: Large language models have demonstrated remarkable capabilities in natural language processing tasks requiring multi-step logical reasoning capabili

researcharxiv-cs-cl

Spurious Stationarity and Hardness Results for Bregman Proximal-Type Algorithms

arXiv:2404.08073v3 Announce Type: replace-cross Abstract: Bregman proximal-type algorithms (BPs), such as mirror descent, have become popular tools in machine learning and data science for exploiting

STREAM: A Data-Centric Framework for Mining High-Value Task-Oriented Dialogues from Streaming Media

arXiv:2605.25162v1 Announce Type: cross Abstract: Large language models for vertical domains are bottlenecked by the scarcity of complex, domain-specific task-oriented dialogues. Existing data acquisi

Agentivism: a learning theory for the age of artificial intelligence

arXiv:2604.07813v2 Announce Type: replace Abstract: Learning theories have historically changed when the conditions of learning evolved. Generative and agentic AI create a new condition by allowing le

Asymmetric Scaling Laws from Sparse Features

arXiv:2605.23591v1 Announce Type: cross Abstract: We introduce a model for neural scaling laws under sparse activations. In the model, test loss is often dominated by rare coordinates that are never o

CapTrack: Multifaceted Evaluation of Forgetting in LLM Post-Training

arXiv:2603.06610v2 Announce Type: replace Abstract: Large language model (LLM) post-training enhances latent skills, unlocks value alignment, improves performance, and enables domain adaptation. Unfor

safetyarxiv-cs-lg

EM-Vid: Training-Free Entity-Centric Memory for Efficient and Consistent Multi-Shot Video Generation

arXiv:2605.23610v1 Announce Type: cross Abstract: Multi-shot video generation requires maintaining a consistent appearance of recurring entities across shots while remaining faithful to shot-specific

Exploitation of KnowledgeDeliver via ViewState Deserialization Vulnerability

model-releasesgoogle-cloud-ai

Written by: Takahiro Sugiyama, Peter Revelant, Mathew Potaczek Introduction In late 2025, Mandiant responded to a security incident involving a compromised web server running KnowledgeDeliver. Knowled

Applications

GeoMAE: Masking Representation Learning for Spatio-Temporal Graph Forecasting with Missing Values

arXiv:2508.14083v3 Announce Type: replace-cross Abstract: The ubiquity of missing data in urban intelligence systems, attributable to adverse environmental conditions and equipment failures, poses a s

applicationsarxiv-cs-ai

Model Collapse as Cultural Evolution

arXiv:2605.23054v1 Announce Type: cross Abstract: Model collapse, the progressive degradation of LLMs trained on their own outputs, has been characterized statistically but lacks a linguistic explanat

No Coin Left Behind: Maximizing Strategic Surplus Against No-Regret Dynamics

arXiv:2604.05129v2 Announce Type: replace-cross Abstract: We investigate the strategic surplus obtainable against a Follow-the-Regularized-Leader (FTRL) learner with constant step size eta in nimes m

Positional Failures in Long-Context LLMs: A Blind Spot in Reasoning Benchmarks

arXiv:2605.23170v1 Announce Type: cross Abstract: Position-controlled evaluation is standard for retrieval tasks such as Needle-in-a-Haystack and RULER, but mainstream reasoning benchmarks do not cont

Robots That Know What to Ask: Recovering Misaligned Rewards through Targeted Explanations

arXiv:2605.22986v1 Announce Type: cross Abstract: Learning reward functions from demonstrations assumes that demonstrations provide adequate supervision over all features -- or task-relevant aspects o

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding

arXiv:2601.12805v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown growing promise in biomedical research, particularly for knowledge-driven interpretation tasks. Howeve