Search: “papers”

arXiv:2608.03566v1 Announce Type: cross Abstract: The drift diffusion model (DDM) is a cornerstone of cognitive decision-making research. Although numerous estimation methods exist, researchers contin

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DocTrace: Towards Traceable Long Document VQA via Hierarchical Evidence Graph Reasoning

DGX agent

arXiv:2608.03292v1 Announce Type: new Abstract: Long Document Visual Question Answering (LongDocVQA) requires Multimodal Large Language Models (MLLMs) to locate, integrate, and reason over heterogeneo

safetyarxiv-cs-ai

5 Aug 2026

Efficient Multilingual Neural Machine Translation via Corpus-Driven Vocabulary Pruning: An English-Arabic Case Study

model-releasesarxiv-cs-cl

arXiv:2608.03480v1 Announce Type: new Abstract: The adoption of large pre-trained multilingual models for neural machine translation (MNMT) faces a major challenge: excessive memory and computational

Equivariant Music Transformer

arXiv:2608.03920v1 Announce Type: cross Abstract: Humans recognize a musical passage even when it is shifted in time or transposed in pitch, indicating a notion of equivariance in the representation s

Evaluating LLM Trade-offs for Enterprise Automation: Lessons from Workflow Generation in a Production Enterprise Platform

arXiv:2608.03311v1 Announce Type: cross Abstract: Enterprise compliance management requires rapid adaptation to evolving regulatory frameworks (e.g., DORA, AI RMF, FedRAMP) and tight remediation SLAs.

Evaluation Blindness: How Silent Measurement Failures Corrupt AI Systems from Training to Deployment

model-releasesarxiv-cs-lg

arXiv:2608.02786v1 Announce Type: new Abstract: AI systems can fail silently. The failure propagates through training loops, evaluation pipelines, and production monitoring stacks until downstream har

Evidence-Grounded Multimodal Knowledge Graph Construction for Multi-Lecture Educational Reasoning

arXiv:2608.03161v1 Announce Type: new Abstract: Lecture videos distribute knowledge across speech, slide text, diagrams, equations, and presentation order, which transcript-only retrieval does not ful

Fast Object Removal Attacks on Safety-Critical Video-based Perception Systems

arXiv:2608.02806v1 Announce Type: cross Abstract: By leveraging data from video-based perception systems, intelligent transportation systems (ITS) support safety-critical applications that improve roa

safetyarxiv-cs-cv

Flying over The Uncertain Nature (FORTUNE): Intelligent and Humanistic 3D Path Planning for Low-Altitude Collaboration

arXiv:2608.03408v1 Announce Type: new Abstract: The proliferation of low-altitude intelligent agents is increasing the demand for timely and socially responsible collaborative sensing in dynamic urban

safetyarxiv-cs-ro

FreqAdapt: Frequency-Adaptive Processing for RAW Object Detection

arXiv:2608.03385v1 Announce Type: new Abstract: Existing object detection methods predominantly utilize sRGB inputs, which are compressed from RAW sensor data using Image Signal Processors (ISP) origi

From Generator to Embedder: Harnessing Innate Abilities of Multimodal LLMs via Building Zero-Shot Discriminative Embedding Model

arXiv:2508.00955v3 Announce Type: replace-cross Abstract: Adapting generative Multimodal Large Language Models (MLLMs) into universal embedding models typically demands resource-intensive contrastive

GUI-Lens: Coarse-to-Fine Cropping for GUI Grounding with General-Purpose VLMs

arXiv:2608.03270v1 Announce Type: cross Abstract: GUI grounding maps natural-language instructions to click locations and is essential for reliable GUI agents. The task remains difficult on high-resol

Hi-TTRL: Regulating Consensus with Hints for Test-Time Reinforcement Learning

arXiv:2608.03545v1 Announce Type: new Abstract: Test-time reinforcement learning (TTRL) improves the reasoning capabilities of large language models without labeled data by updating the policy with ps

safetyarxiv-cs-cl

Agents

Hybrid LLM-Augmented Reinforcement Learning Agents for Complex Sequential Decision Tasks

arXiv:2608.03502v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently shown strong capabilities in reasoning, planning, and tool-use, enabling new forms of autonomous agents. Howe

agentsarxiv-cs-ai

Hypercubes, Hyperplanes, and Constraint-Induced Complexity Collapse in Atomic Concept Learning

arXiv:2608.02930v1 Announce Type: new Abstract: We revisit higher-arity atomic concept learning through the geometry of hypercubes and hyperplanes of ground instances. Our starting point is the observ

HyVIC: A Metric-Driven Spatio-Spectral Hyperspectral Image Compression Architecture Based on Variational Autoencoders

arXiv:2603.26468v2 Announce Type: replace Abstract: The rapid growth of hyperspectral data archives in remote sensing (RS) necessitates effective compression methods for storage and transmission. Rece

Agents

Improving Sample Efficiency in Multi-Agent Reinforcement Learning for Simulated Football Games via Exploration

arXiv:2503.13077v2 Announce Type: replace Abstract: Multi-agent reinforcement learning has shown promise in learning cooperative behaviors in team-based environments. However, such methods often deman

agentsarxiv-cs-lg

Agents

Internalising the Identity Primitive: Cryptographic Individuality for an Autonomous Agent on a Public Blockchain

arXiv:2608.02986v1 Announce Type: cross Abstract: A software agent on a public blockchain accumulates authority and economic stakes, raising the engineering question of what makes it count as an indiv

agentsarxiv-cs-ai

LatentGuard: Efficient and Inspectable Latent Reasoning for LLM Safeguards

arXiv:2608.03838v1 Announce Type: new Abstract: Reasoning-based guard models improve LLM safeguards, but decoding explicit rationales for every interaction makes them costly to deploy. Although latent

LDU-Bench: Multimodal LLM Evaluation for Lithography Defect Understanding under Layout-Varying Circuit Backgrounds

arXiv:2608.03078v1 Announce Type: new Abstract: Multimodal large language models have demonstrated strong defect recognition capability in industrial anomaly detection. However, in lithography review,

Learning Music Style for Piano Arrangement Through Cross-Modal Bootstrapping

arXiv:2608.03050v1 Announce Type: cross Abstract: What is music style? Though often described using text labels such as 'swing,' 'classical,' or 'emotional,' the real style remains implicit and hidden

Lightweight Chunk Selection for Mobile Retrieval-Augmented Generation

arXiv:2608.03148v1 Announce Type: cross Abstract: RAG improves the factual grounding of LLM by incorporating external knowledge, but deploying RAG on mobile and edge devices remains challenging becaus

LoCA: Forward-Only LLM Tuning after One-Shot Calibration with Local Credit Assignment

arXiv:2608.03020v1 Announce Type: new Abstract: Parameter-efficient post-training reduces the number of trainable parameters, but still requires repeated end-to-end backpropagation through the frozen

Looking under the Wrong Lamppost: On the Limitations of Automated Translation Quality Estimation

model-releasesarxiv-cs-cl

arXiv:2608.03577v1 Announce Type: new Abstract: Automation of Translation Quality Estimation (QE) has emerged as a widely discussed approach to managing translation quality at scale, and a growing num

Low-Dimensional High-Leverage Subspace Optimization: Beyond Full-Parameter Coupled Training for Neural Network Quantization

arXiv:2608.03919v1 Announce Type: new Abstract: Low-bit quantization suffers severe accuracy degradation on compact networks, rooted in the dominant full-parameter coupled training paradigm that ignor

Tutorials

Measuring Explainer Stability via Attribution Separability

arXiv:2608.02697v1 Announce Type: cross Abstract: Attribution methods (AMs) assign an importance score to each feature and are widely adopted to explain black-box models. However, most methods can pro

tutorialsarxiv-cs-ai

Mechanism of Task-oriented Information Removal in In-context Learning

arXiv:2509.21012v4 Announce Type: replace-cross Abstract: In-context Learning (ICL) is an emerging few-shot learning paradigm based on modern Language Models (LMs), yet its inner mechanism remains unc

MeSS: City Mesh-Guided Outdoor Scene Generation with Cross-View Consistent Diffusion

arXiv:2508.15169v4 Announce Type: replace Abstract: Mesh models have become increasingly accessible for numerous cities; however, the lack of realistic textures restricts their application in virtual

safetyarxiv-cs-cv

Applications

Micro-Segmentation Anomaly Detection in Zero-Trust Software-Defined Network Fabrics

arXiv:2608.02627v1 Announce Type: cross Abstract: Zero Trust Architecture (ZTA) principles need rigorous network segmentation and ongoing verification to reduce implicit trust and lateral threat propa

applicationsarxiv-cs-cv

Multimodal Plant Root Phenotyping with Integration of 3D Skeleton Extraction and Language Analysis

arXiv:2608.03109v1 Announce Type: new Abstract: Plant root phenotyping is fundamental to understanding below-ground structures, optimizing crop management, and improving agricultural sustainability. T

researcharxiv-cs-cv

Neural network realization of binary refinement iterates via a two-chart atlas selector

arXiv:2608.02624v1 Announce Type: cross Abstract: Refinement operators generate many functions used in wavelet constructions, subdivision schemes, and geometric modeling. Their finite iterates can dev

researcharxiv-cs-lg

NOMADD: Numerical Optimization of Models Adapting to Data Drift

model-releasesarxiv-cs-lg

arXiv:2608.02845v1 Announce Type: new Abstract: Tabular model performance degrades when feature distributions change over time or the relationship between features and outcome variables change over ti

On the Performance of Malware Detection Classifiers Using Hardware Performance Counters

arXiv:2608.02671v1 Announce Type: cross Abstract: Malware detection using Hardware Performance Counters (HPC) has emerged as a promising solution to improve the security of computing systems as a comp

researcharxiv-cs-lg

Operationally Feasible Synthetic Power-Grid Scenarios via Learning the AC-Operable Joint Distribution

model-releasesarxiv-cs-lg

arXiv:2608.03878v1 Announce Type: new Abstract: Synthetic power-grid scenarios are essential for planning, resilience assessment, contingency analysis, and data-driven power-system applications. Recen

Optimal Liability Design for Medical AI

arXiv:2608.03114v1 Announce Type: cross Abstract: Artificial intelligence (AI) is increasingly integrated into medical decision-making, yet its liability implications remain complex, particularly when

pi-Attention: Online Efficient Sparse Transformers for Long-Context Modeling

arXiv:2511.10696v3 Announce Type: replace-cross Abstract: Sparse attention is crucial in long-context Transformers, which restricts each token to a limited neighborhood and thereby reduces the quadrat

Qwen-Image-3.0-Pro is live on Qwen Cloud now! Try it out👇 https://www.qwencloud.com/models/qwen-image-3.0-pro?utm_content=g_20000001188

Qwen-Image-3.0-Pro is live on Qwen Cloud now! Try it out👇 https://www.qwencloud.com/models/qwen-image-3.0-pro?utm_content=g_20000001188 🔔 Qwen-Image-3.0 is now live on Qwen Cloud! Ranked #1 among Chin

model-releasesqwen--x

Route-Align-Verify for Functional Correctness in Code Generation

arXiv:2608.03341v1 Announce Type: cross Abstract: Large language models (LLMs) have substantially improved code generation, yet achieving strong functional correctness remains difficult, especially fo

Shielding for Higher-Order Safety

arXiv:2608.03662v1 Announce Type: new Abstract: Safety shields are runtime enforcement mechanisms that restrict the actions of a controller to guarantee safety. Classical shields are usually synthesis

Should We Type or Talk to LLM Agents? A Comprehensive Study of Voice and Keyboard Input Perturbations

arXiv:2608.03970v1 Announce Type: new Abstract: Human input reaches language models by typing or speaking, and each channel leaves a distinct signature: orthographic noise for keyboards; for voice, di

SkillTrace: Traversing a Query-Skill Graph for Composable LLM Agents

arXiv:2608.02356v2 Announce Type: replace Abstract: Large language model agents increasingly solve complex tasks by composing reusable skills from a library. To address this, the key challenge is not

Socially Grounded Agentic AI: Coordinating Plural Perspectives through Social Theory

arXiv:2608.03910v1 Announce Type: new Abstract: As AI systems are deployed across increasingly diverse social contexts, alignment can no longer be framed as the optimization of a single, unified set o

SP3O: Reinforcement Learning from Segment Preferences without Reward Modeling

arXiv:2608.02951v1 Announce Type: cross Abstract: Preference-based reinforcement learning (PbRL) for general stochastic MDPs often requires training a reward model. Existing reward-model-free methods

State Propagation Also Satisfies: A Complex-Valued State-Space Model for Deterministic State Tracking

arXiv:2608.03425v1 Announce Type: new Abstract: Transformer-based architectures have dominated sequence modeling, largely due to the expressive power of attention mechanisms. However, for a class of d

Staying on Spec: Real-Time Monitoring under Uncertainty with a Maritime Case Study

arXiv:2608.02811v1 Announce Type: new Abstract: Robotic systems must operate under uncertainty while satisfying complex task and safety specifications. Monitoring such specifications under uncertainty

safetyarxiv-cs-ro

Stiffness Copilot: An Impedance Policy for Contact-Rich Teleoperation

arXiv:2603.14068v2 Announce Type: replace Abstract: In teleoperation of contact-rich manipulation tasks, selecting robot impedance is critical but difficult. The robot must be compliant to avoid damag

safetyarxiv-cs-ro

Local Ai

Stochastic Multiple Shooting Trajectory Optimization via Sequential Local Policy Evaluation

arXiv:2608.03978v1 Announce Type: new Abstract: Stochastic single shooting trajectory optimization methods such as Model Predictive Path Integral control (MPPI) have been widely adopted in robotics du

local-aiarxiv-cs-ro

Stochastic Saddle Avoidance Beyond Unit Excitation and Smoothness: A Pathwise Lyapunov-Perron Framework

arXiv:2608.03001v1 Announce Type: cross Abstract: Unit excitation (UE) is a common assumption in stochastic saddle avoidance: the stochastic error must have a uniformly positive component along every

researcharxiv-cs-lg