Search: “papers”

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods

arXiv:2608.13333v1 Announce Type: new Abstract: Large neighborhood search normally selects a random subset of decision variables for iterative optimization. For efficiently solving different problems,

local-aiarxiv-cs-ai

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MARCH: Scaling Recurrent Memory with Content-Routed State Anchors

DGX agent

arXiv:2608.12435v1 Announce Type: new Abstract: Transformers owe much of their strong long-context retrieval capability to a token-level memory that grows with context length. This flexibility, howeve

researcharxiv-cs-lg

14 Aug 2026

Mimicry without understanding: the origins of decision bias in large language models

arXiv:2608.12339v1 Announce Type: cross Abstract: Large Language models (LLMs) were found to be susceptible to a host of social, affective, and cognitive biases. We examined two mechanisms through whi

Multi-Agent Scheduling with LLM-Assisted Contract Net Negotiation for Stream Processing in Mobile Edge Computing

arXiv:2608.12371v1 Announce Type: new Abstract: Stream-processing systems increasingly operate across heterogeneous mobile edge--cloud infrastructures, where workload volatility, resource contention,

local-aiarxiv-cs-ai

Multi-Layer Context Camouflaging: A Semantic Superposition and Contextual Lamination Framework for Malpractice-Resilient Online Assessment

arXiv:2608.13100v1 Announce Type: new Abstract: Contemporary online assessment systems rely primarily on browser lockdown, webcam monitoring, and behavioural analytics, yet remain vulnerable to attack

researcharxiv-cs-ai

NAS-Driven Hardware Accelerator Exploration for Edge AI and Quantization Effects on the Pareto Space

arXiv:2608.13293v1 Announce Type: new Abstract: Edge AI deployment demands neural architectures that are simultaneously accurate, computationally efficient, and hardware-deployable - a challenge addre

local-aiarxiv-cs-ai

Novels generated by language models show compressed formal variation

arXiv:2608.12630v1 Announce Type: cross Abstract: While large language models can generate entire novels, there is little information about the level of formal variation in their output over many gene

OGR-MARL: Option-Guided Residual Multi-Agent Reinforcement Learning for Heterogeneous USV Cooperative Pursuit in Constrained Port Waterways

arXiv:2608.12995v1 Announce Type: new Abstract: Heterogeneous USV cooperative pursuit in constrained port waterways requires evader interception under navigation, traffic, and role constraints. This p

OmniScientist: An Omni-Modal Omni-Discipline AI Scientist

arXiv:2608.13558v1 Announce Type: new Abstract: Recent advances in foundation models have enabled AI scientists to automate increasingly complete research workflows, from hypothesis generation and cod

agentsarxiv-cs-ai

Online Correlation Clustering: Simultaneously Optimizing All ell_p-norms

arXiv:2510.15076v2 Announce Type: replace Abstract: The ell_p-norm objectives for correlation clustering present a fundamental trade-off between minimizing total disagreements (the ell_1-norm) and ens

safetyarxiv-cs-lg

Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoning

arXiv:2508.17905v2 Announce Type: replace Abstract: Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions by using structured sources such as tables, databases, and k

researcharxiv-cs-cl

PhysMaster: Building an Autonomous AI Physicist for Theoretical and Computational Physics Research

arXiv:2512.19799v2 Announce Type: replace Abstract: Advances in LLM reasoning and tool use have enabled agentic science, yet frontier theoretical and computational physics remains challenging because

Privacy-Preserving RAG by Concealing Sensitive Information from External LLMs

arXiv:2608.12675v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) is widely used to improve the performance of Large Language Models (LLMs) in answering user queries. Existing priva

Prof-K: Probabilistic One-Pass Filtering for Efficient Top-k Selection

arXiv:2608.12573v1 Announce Type: new Abstract: Top-k selection is a fundamental computational primitive with applications spanning databases, information retrieval, signal processing, and modern mach

researcharxiv-cs-lg

Prompts in the Wild: A Large Analyzed Collection of Transactional Prompts in Code

arXiv:2608.12905v1 Announce Type: new Abstract: The behavior of contemporary generative Large Language Models (LLMs) is directly shaped by prompts, unstructured texts that describe the desired output

researcharxiv-cs-cl

QuISE: Defense against Typographic Attacks on VLMs via Query-Irrelevant Semantic Editing

arXiv:2608.13119v1 Announce Type: new Abstract: Typographic attacks pose a critical threat to vision-language models (VLMs) by injecting misleading text into images and causing models to rely on adver

researcharxiv-cs-cv

RAIL: An Automatic Classifier of the Artificial Intelligence Readiness Level

arXiv:2608.13428v1 Announce Type: new Abstract: Assessing the maturity of artificial intelligence technologies is essential for investment decisions, project management, and policy monitoring, yet the

Robust Dempster-Shafer Evidence Fusion with Chaos-Conflict Measurement and Historical-Experience Weighting

arXiv:2608.13108v1 Announce Type: new Abstract: Multi-source evidence fusion under Dempster-Shafer theory faces two persistent challenges: existing conflict measures assess inter-evidence inconsistenc

Scaling Automatic Research Agents via World Models

arXiv:2608.12564v1 Announce Type: new Abstract: Automating empirical research is a long-standing direction of AI. Recent automatic research (AutoResearch) agents bring this goal within reach, as moder

safetyarxiv-cs-lg

SchemaLink: An Intelligent Web Editor for LinkML Schema Curation

arXiv:2608.12529v1 Announce Type: cross Abstract: Motivation: LinkML is a suitable language for the representation of the structural and content constraints of different kinds of biomedical data. Even

researcharxiv-cs-ai

SCULPT: Subtractive Composition for 3D Part Generation

model-releasesarxiv-cs-cv

arXiv:2608.13541v1 Announce Type: new Abstract: Part-aware 3D generation aims to create digital assets that are coherent as complete objects while exposing structural parts for editing, material assig

SDS-LoRA: Overcoming Anisotropic Gradient Scaling in Low-Rank Adaptation

arXiv:2606.16454v2 Announce Type: replace-cross Abstract: Low-Rank Adaptation (LoRA) enables efficient adaptation of large pretrained models to downstream tasks by parameterizing weight updates with l

Security and Detectability Analysis of Unicode Text Watermarking Methods against Large Language Models

arXiv:2512.13325v2 Announce Type: replace-cross Abstract: Securing digital text is becoming increasingly relevant due to the widespread use of large language models. Individuals' fear of losing contro

Self-Localizing MIMO Beam Mapping for Intelligent Open RAN with Continuously Evolving Channel Memory

arXiv:2511.17007v2 Announce Type: replace-cross Abstract: Open and intelligent radio access networks (RANs) envisioned for 6G require accurate and reusable wireless channel knowledge for intelligent i

local-aiarxiv-cs-lg

SLAyiNG: A Diverse and Community-validated Dataset of Queer Slang

arXiv:2509.17449v2 Announce Type: replace Abstract: Queer vernacular is rarely studied in NLP, despite advancements in resources and evaluation for other sociolects and informal language. Because of t

safetyarxiv-cs-cl

SoK: From Generation to Consumption of Privacy Documents in Software Systems

arXiv:2608.12511v1 Announce Type: cross Abstract: Privacy documents (e.g., privacy policies) are a central mechanism through which digital services disclose data practices and seek user consent. Over

safetyarxiv-cs-cl

Statistical Properties of Robust Learning under Distributional Shifts

arXiv:2608.13133v1 Announce Type: cross Abstract: Distributional shifts arise when the target deployment environment differs from the source environment that generated the training data. Robust learni

researcharxiv-cs-lg

Applications

Towards Socially Compliant Navigation in Deep Reinforcement Learning via Proxemics-Based Reward Modeling

arXiv:2608.12917v1 Announce Type: new Abstract: Developing effective robot navigation methods in crowded environments is essential for real-world applications. Although recent deep reinforcement learn

applicationsarxiv-cs-lg

UltraFast-LiNET: Light-weight multi-scale shift convolutional network for real-time low-light image enhancement

model-releasesarxiv-cs-cv

arXiv:2512.02965v2 Announce Type: replace Abstract: Addressing the urgent need for high-performance real-time low-light image enhancement on resource-constrained edge devices in low-illumination scena

Understanding Backdoor Vulnerabilities in Vertical Federated Learning: The Gap Between Research and Practice

arXiv:2608.12962v1 Announce Type: new Abstract: Vertical Federated Learning (VFL) enables organizations holding complementary features of shared entities to collaborate and train models. In this setti

Virtual Temperature Sensors in Power Transformers Using Neural Ordinary Differential Equations

arXiv:2608.13260v1 Announce Type: new Abstract: Accurate modeling and forecasting of power transformer thermal behavior are critical for reliability, asset lifetime, and optimized power system operati

A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement

model-releasesarxiv-cs-cl

arXiv:2608.12269v1 Announce Type: new Abstract: Public procurement involves the allocation of substantial financial resources; therefore, continuous oversight through audits, controls, and monitoring

Applications

A Conceptual Framework for Enhancing Workforce Readiness for Smart Manufacturing in the AI Era

arXiv:2608.11540v1 Announce Type: cross Abstract: The convergence of artificial intelligence (AI), Industrial Internet of Things, cyber-physical systems, and advanced robotics is reshaping manufacturi

applicationsarxiv-cs-ai

Tutorials

A Simple Efficiency Incremental Learning Framework via Vision-Language Model with Nonlinear Multi-Adapters

arXiv:2603.11211v3 Announce Type: replace-cross Abstract: Incremental Learning (IL) aims to learn new tasks while preserving previously acquired knowledge. Integrating the zero-shot learning capabilit

tutorialsarxiv-cs-ai

Accuracy and Order Sensitivity Diverge Under Label-Free Strategies

arXiv:2608.11947v1 Announce Type: cross Abstract: Multiple-choice benchmarks are widely used to evaluate large language models, but MCQ scores conflate knowledge with sensitivity to option order, whic

ADEPT: A Unified Framework for Deep Learning Test Adequacy

arXiv:2608.12144v1 Announce Type: cross Abstract: Over the past decade, many test adequacy metrics have been proposed for deep learning that characterize test dataset adequacy from different perspecti

Agent Safety Should Be a Runtime Contract

arXiv:2608.11274v1 Announce Type: cross Abstract: The dominant paradigm treats AI safety as a property to be instilled during model training via RLHF, DPO, or Constitutional AI. We argue this is struc

Agent Skills Can Be Harmful: An Empirical Study of Skill-Induced Failures in LLM Agents

arXiv:2608.11888v1 Announce Type: new Abstract: Agent skills are the de facto mechanism for extending LLM agents with reusable guidance. A skill can shape the agent's task execution, including plannin

agentsarxiv-cs-ai

AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses

arXiv:2608.12307v1 Announce Type: cross Abstract: Recent work on distillation transfers the capabilities of large models to smaller ones often by updating the latter's parameters, through teacher forc

Air Quality Station Simulation via LSTM and Attention-Based Modelling

arXiv:2608.11839v1 Announce Type: new Abstract: Poor air quality in urban areas is driven by a complex chain of processes and presents a significant public health concern. To better understand and con

Autonomous Telerehabilitation via Skeletal Motion Prediction and Joint-Level Performance Assessment

arXiv:2608.12145v1 Announce Type: new Abstract: Autonomous rehabilitation systems must not only recognize human motion but also provide structured feedback to support users without continuous therapis

agentsarxiv-cs-cv

Benchmark-Based Comparative Assessment of Publicly Benchmarked Indian Foundation Models: A Capability and Evaluation-Maturity Framework

arXiv:2608.11891v1 Announce Type: cross Abstract: Governments increasingly fund indigenous foundation models to strengthen national AI capability, digital sovereignty, and multilingual computing. Asse

Benchmarking Cyberattack Detection in Electric Vehicle Charging Infrastructure with Benign User Updates

arXiv:2608.11286v1 Announce Type: cross Abstract: Cyberattack detection in electric vehicle charging infrastructure is complicated by legitimate post-activation revisions to requested energy and depar

Beyond Local Power: Functional Connectivity Analysis for Subject-Independent Learning Style Recognition

arXiv:2608.12000v1 Announce Type: cross Abstract: Identifying individual learning styles optimizes pedagogical efficacy. While traditional questionnaires are structured, behavioral tracking methods re

researcharxiv-cs-lg

CLEAR: Class-wise Expert Aggregation with Structured Sampling for Long-Tailed Classification

arXiv:2608.11287v1 Announce Type: cross Abstract: Long-tailed classification poses a reliability challenge because models trained on imbalanced data are unevenly reliable across frequent and underrepr

researcharxiv-cs-ai

Co-constructing sociotechnical AI governance: participatory system mapping using algorithm registers

arXiv:2608.12166v1 Announce Type: cross Abstract: Algorithm registers have been championed as a means of providing transparency on the use of algorithms in public services. Yet potential publics diffe

CookVoice: Unified Framework for Style Controllable Multi-Modal Human Voice Generation

arXiv:2608.11590v1 Announce Type: cross Abstract: Human voice generation has made rapid progress in speech generation, singing voice generation, voice cloning, and voice editing. However, most existin

safetyarxiv-cs-lg

Credo: Declarative Control of LLM Pipelines via Beliefs and Policies

arXiv:2604.14401v2 Announce Type: replace Abstract: Agentic AI systems are becoming commonplace in domains that require long-lived, stateful decision-making in continuously evolving conditions. As suc

agentsarxiv-cs-ai