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// Artifacts as Memory Beyond the Agent Boundary // An agent doesn't always need a bigger memory buffer. Sometimes the environment itself re…

// Artifacts as Memory Beyond the Agent Boundary // An agent doesn't always need a bigger memory buffer. Sometimes the environment itself remembers on the agent's behalf. New research formalizes this

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Assessing Privacy Preservation and Utility in Online Vision-Language Models

DGX agent

arXiv:2604.09695v1 Announce Type: cross Abstract: The increasing use of Online Vision Language Models (OVLMs) for processing images has introduced significant privacy risks, as individuals frequently

researcharxiv-cs-ai

14 Apr 2026

ATANT v1.1: Positioning Continuity Evaluation Against Memory, Long-Context, and Agentic-Memory Benchmarks

arXiv:2604.10981v1 Announce Type: new Abstract: ATANT v1.0 (arXiv:2604.06710) defined continuity as a system property with 7 required properties and introduced a 10-checkpoint, LLM-free evaluation met

Local Ai

AtlasKV: Augmenting LLMs with Billion-Scale Knowledge Graphs in 20GB VRAM

arXiv:2510.17934v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) has shown some success in augmenting large language models (LLMs) with external knowledge. However, as a

local-aiarxiv-cs-ai

Attention Sink in Transformers: A Survey on Utilization, Interpretation, and Mitigation

arXiv:2604.10098v1 Announce Type: new Abstract: As the foundational architecture of modern machine learning, Transformers have driven remarkable progress across diverse AI domains. Despite their trans

researcharxiv-cs-lg

AttnTrace: Contextual Attribution of Prompt Injection and Knowledge Corruption

arXiv:2508.03793v2 Announce Type: replace Abstract: Long-context large language models (LLMs), such as Gemini-2.5-Pro and Claude-Sonnet-4, are increasingly used to empower advanced AI systems, includi

BadGraph: A Backdoor Attack Against Latent Diffusion Model for Text-Guided Graph Generation

arXiv:2510.20792v4 Announce Type: replace-cross Abstract: The rapid progress of graph generation has raised new security concerns, particularly regarding backdoor vulnerabilities. While prior work has

Beyond Black-Box Interventions: Latent Probing for Faithful Retrieval-Augmented Generation

arXiv:2510.12460v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems often fail to maintain contextual faithfulness, generating responses that conflict with the provided co

researcharxiv-cs-cl

Beyond Fluency: Toward Reliable Trajectories in Agentic IR

arXiv:2604.04269v2 Announce Type: replace Abstract: Information Retrieval is shifting from passive document ranking toward autonomous agentic workflows that operate in multi-step Reason-Act-Observe lo

Beyond Matching to Tiles: Bridging Unaligned Aerial and Satellite Views for Vision-Only UAV Navigation

arXiv:2603.22153v3 Announce Type: replace-cross Abstract: Recent advances in cross-view geo-localization (CVGL) methods have shown strong potential for supporting unmanned aerial vehicle (UAV) navigat

Beyond Offline A/B Testing: Context-Aware Agent Simulation for Recommender System Evaluation

arXiv:2604.09549v1 Announce Type: cross Abstract: Recommender systems are central to online services, enabling users to navigate through massive amounts of content across various domains. However, the

Beyond Reconstruction: Reconstruction-to-Vector Diffusion for Hyperspectral Anomaly Detection

arXiv:2604.11390v1 Announce Type: new Abstract: While Hyperspectral Anomaly Detection (HAD) excels at identifying sparse targets in complex scenes, existing models remain trapped in a scalar 'reconstr

safetyarxiv-cs-cv

Beyond Statistical Co-occurrence: Unlocking Intrinsic Semantics for Tabular Data Clustering

arXiv:2604.10865v1 Announce Type: new Abstract: Deep Clustering (DC) has emerged as a powerful tool for tabular data analysis in real-world domains like finance and healthcare. However, most existing

Bidirectional Cross-Attention Fusion of High-Res RGB and Low-Res HSI for Multimodal Automated Waste Sorting

arXiv:2603.13941v2 Announce Type: replace Abstract: Growing waste streams and the transition to a circular economy require efficient automated waste sorting. In industrial settings, materials move on

bioLeak: Leakage-Aware Modeling and Diagnostics for Machine Learning in R

arXiv:2604.10965v1 Announce Type: cross Abstract: Data leakage remains a recurrent source of optimistic bias in biomedical machine learning studies. Standard row-wise cross-validation and globally est

safetyarxiv-cs-lg

Applications

Bootstrapping Video Semantic Segmentation Model via Distillation-assisted Test-Time Adaptation

arXiv:2604.10950v1 Announce Type: new Abstract: Fully supervised Video Semantic Segmentation (VSS) relies heavily on densely annotated video data, limiting practical applicability. Alternatively, appl

applicationsarxiv-cs-cv

Both Ends Count! Just How Good are LLM Agents at 'Text-to-Big SQL'?

arXiv:2602.21480v4 Announce Type: replace-cross Abstract: Text-to-SQL and Big Data are both extensively benchmarked fields, yet there is limited research that evaluates them jointly. In the real world

BRIDGE and TCH-Net: Heterogeneous Benchmark and Multi-Branch Baseline for Cross-Domain IoT Botnet Detection

model-releasesarxiv-cs-lg

arXiv:2604.11324v1 Announce Type: cross Abstract: IoT botnet detection has advanced, yet most published systems are validated on a single dataset and rarely generalise across environments. Heterogeneo

BridgeSim: Unveiling the OL-CL Gap in End-to-End Autonomous Driving

arXiv:2604.10856v1 Announce Type: cross Abstract: Open-loop (OL) to closed-loop (CL) gap (OL-CL gap) exists when OL-pretrained policies scoring high in OL evaluations fail to transfer effectively in c

C2F-Thinker: Coarse-to-Fine Reasoning with Hint-Guided Reinforcement Learning for Multimodal Sentiment Analysis

arXiv:2604.00013v2 Announce Type: replace-cross Abstract: Multimodal sentiment analysis aims to integrate textual, acoustic, and visual information for deep emotional understanding. Despite the progre

safetyarxiv-cs-ai

Can Large Language Models Infer Causal Relationships from Real-World Text?

arXiv:2505.18931v4 Announce Type: replace Abstract: Understanding and inferring causal relationships from texts is a core aspect of human cognition and is essential for advancing large language models

Catalog-Native LLM: Speaking Item-ID Dialect with Less Entanglement for Recommendation

arXiv:2510.05125v2 Announce Type: replace Abstract: While collaborative filtering delivers predictive accuracy and efficiency, and Large Language Models (LLMs) enable expressive and generalizable reas

researcharxiv-cs-cl

Catalyst: Out-of-Distribution Detection via Elastic Scaling

arXiv:2602.02409v2 Announce Type: replace Abstract: Out-of-distribution (OOD) detection is critical for the safe deployment of deep neural networks. State-of-the-art post-hoc methods typically derive

researcharxiv-cs-cv

Hardware

Characterizing Performance-Energy Trade-offs of Large Language Models in Multi-Request Workflows

arXiv:2604.09611v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in applications forming multi-request workflows like document summarization, search-based copilots,

hardwarearxiv-cs-ai

City-Wide Low-Altitude Urban Air Mobility: A Scalable Global Path Planning Approach via Risk-Aware Multi-Scale Cell Decomposition

arXiv:2408.02786v4 Announce Type: replace Abstract: The realization of Urban Air Mobility (UAM) necessitates scalable global path planning algorithms capable of ensuring safe navigation within complex

researcharxiv-cs-ro

Collaborative Multi-Agent Scripts Generation for Enhancing Imperfect-Information Reasoning in Murder Mystery Games

arXiv:2604.11741v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown impressive capabilities in perceptual tasks, yet they degrade in complex multi-hop reasoning under multiplayer

Concept Drift Guided LayerNorm Tuning for Efficient Multimodal Metaphor Identification

model-releasesarxiv-cs-lg

arXiv:2505.11237v3 Announce Type: replace-cross Abstract: Metaphorical imagination, the ability to connect seemingly unrelated concepts, is fundamental to human cognition and communication. While unde

ConfigSpec: Profiling-Based Configuration Selection for Distributed Edge--Cloud Speculative LLM Serving

arXiv:2604.09722v1 Announce Type: cross Abstract: Speculative decoding enables collaborative Large Language Model (LLM) inference across cloud and edge by separating lightweight token drafting from he

safetyarxiv-cs-ai

Conflicts Make Large Reasoning Models Vulnerable to Attacks

arXiv:2604.09750v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) have achieved remarkable performance across diverse domains, yet their decision-making under conflicting objectives rema

Consensus-based Recursive Multi-Output Gaussian Process

arXiv:2604.10146v1 Announce Type: new Abstract: Multi-output Gaussian Processes provide principled uncertainty-aware learning of vector-valued fields but are difficult to deploy in large-scale, distri

agentsarxiv-cs-lg

Constrained Assumption-Based Argumentation Frameworks

arXiv:2602.13135v2 Announce Type: replace Abstract: Assumption-based Argumentation (ABA) is a well-established form of structured argumentation. ABA frameworks with an underlying atomic language are w

researcharxiv-cs-ai

CounterBench: Evaluating and Improving Counterfactual Reasoning in Large Language Models

arXiv:2502.11008v2 Announce Type: replace Abstract: Counterfactual reasoning is widely recognized as one of the most challenging and intricate aspects of causality in artificial intelligence. In this

CPAM: Context-Preserving Adaptive Manipulation for Zero-Shot Real Image Editing

arXiv:2506.18438v2 Announce Type: replace Abstract: Editing natural images using textual descriptions in text-to-image diffusion models remains a significant challenge, particularly in achieving consi

CuraLight: Debate-Guided Data Curation for LLM-Centered Traffic Signal Control

arXiv:2604.05663v2 Announce Type: replace Abstract: Traffic signal control (TSC) is a core component of intelligent transportation systems (ITS), aiming to reduce congestion, emissions, and travel tim

CUTEv2: Unified and Configurable Matrix Extension for Diverse CPU Architectures with Minimal Design Overhead

arXiv:2604.11615v1 Announce Type: cross Abstract: Matrix extensions have emerged as an essential feature in modern CPUs to address the surging demands of AI workloads. However, existing designs often

researcharxiv-cs-ai

DarwinNet: An Evolutionary Network Architecture for Agent-Driven Protocol Synthesis

arXiv:2604.01236v2 Announce Type: replace-cross Abstract: Traditional network architectures suffer from severe protocol ossification and structural fragility due to their reliance on static, human-def

Data-Efficient Semantic Segmentation of 3D Point Clouds via Open-Vocabulary Image Segmentation-based Pseudo-Labeling

arXiv:2604.11007v1 Announce Type: new Abstract: Semantic segmentation of 3D point cloud scenes is a crucial task for various applications. In real-world scenarios, training segmentation models often f

Decomposing and Reducing Hidden Measurement Error in LLM Evaluation Pipelines

arXiv:2604.11581v1 Announce Type: new Abstract: LLM evaluations drive which models get deployed, which safety standards get adopted, and which research conclusions get published. Yet these scores carr

Hardware

Deep Optimizer States: Towards Scalable Training of Transformer Models Using Interleaved Offloading

arXiv:2410.21316v2 Announce Type: replace-cross Abstract: Transformers and large language models~(LLMs) have seen rapid adoption in all domains. Their sizes have exploded to hundreds of billions of pa

hardwarearxiv-cs-ai

DeepFleet: Multi-Agent Foundation Models for Mobile Robots

arXiv:2508.08574v3 Announce Type: replace Abstract: We introduce DeepFleet, a suite of foundation models designed to support coordination and planning for large-scale mobile robot fleets. These models

safetyarxiv-cs-ro

Local Ai

Defending against Patch-Based and Texture-Based Adversarial Attacks with Spectral Decomposition

arXiv:2604.10715v1 Announce Type: new Abstract: Adversarial examples present significant challenges to the security of Deep Neural Network (DNN) applications. Specifically, there are patch-based and t

local-aiarxiv-cs-cv

Detecting Corporate AI-Washing via Cross-Modal Semantic Inconsistency Learning

arXiv:2604.09644v1 Announce Type: cross Abstract: Corporate AI-washing-the strategic misrepresentation of AI capabilities via exaggerated or fabricated cross-channel disclosures-has emerged as a syste

Applications

Diffusion Reinforcement Learning Based Online 3D Bin Packing Spatial Strategy Optimization

arXiv:2604.10953v1 Announce Type: new Abstract: The online 3D bin packing problem is important in logistics, warehousing and intelligent manufacturing, with solutions shifting to deep reinforcement le

applicationsarxiv-cs-ro

DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment

arXiv:2510.24574v2 Announce Type: replace-cross Abstract: Training time-series forecasting models requires aligning the conditional distribution of model forecasts with that of the label sequence. The

safetyarxiv-cs-ai

Doc-PP: Document Policy Preservation Benchmark for Large Vision-Language Models

arXiv:2601.03926v2 Announce Type: replace Abstract: The deployment of Large Vision-Language Models (LVLMs) for real-world document question answering is often constrained by dynamic, user-defined poli

DocRevive: A Unified Pipeline for Document Text Restoration

arXiv:2604.10077v1 Announce Type: new Abstract: In Document Understanding, the challenge of reconstructing damaged, occluded, or incomplete text remains a critical yet unexplored problem. Subsequent d

DRIFT: Deep Restoration, ISP Fusion, and Tone-mapping

arXiv:2604.03402v2 Announce Type: replace-cross Abstract: Smartphone cameras have gained immense popularity with the adoption of high-resolution and high-dynamic range imaging. As a result, high-perfo

safetyarxiv-cs-cv

Local Ai

Dual-Branch Remote Sensing Infrared Image Super-Resolution

arXiv:2604.10112v1 Announce Type: new Abstract: Remote sensing infrared image super-resolution aims to recover sharper thermal observations from low-resolution inputs while preserving target contours,

local-aiarxiv-cs-cv