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Risk Architecture for AI-Native Engineering Teams: An Organizational Framework for Agentic System Governance

arXiv:2607.01421v1 Announce Type: cross Abstract: Engineering management research has produced mature frameworks for software risk: ownership by feature, escalation by severity, and assurance by test

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Research

Robust and Explainable 3D Mode Shape Recognition Using Region-Aware Graph Neural Networks

DGX agent

arXiv:2607.01522v1 Announce Type: cross Abstract: Mode shape recognition is a fundamental task in automotive NVH development, yet it remains dependent on manual visual inspection by experienced engine

researcharxiv-cs-ai

3 Jul 2026

Robust for the Wrong Reasons: The Representational Geometry of LLM Robustness to Science Skepticism

arXiv:2607.01951v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly consulted on contested scientific questions, raising the concern that they will sycophantically retreat

Applications

Robust Image Processing Techniques for Construction Environment Monitoring Using Underwater Robots

arXiv:2607.01915v1 Announce Type: cross Abstract: This paper proposes a robust image processing framework for underwater robot-based construction environment monitoring, targeting complex degradations

applicationsarxiv-cs-ro

Role-Aware Neural Convex Divergence Heads for Asymmetric Representation Learning

arXiv:2607.01762v1 Announce Type: new Abstract: Many representation learning problems involve directed relations, such as lexical entailment, sentence entailment, ontology hierarchy, and citation link

RuleChef: Grounding LLM Task Knowledge in Human-Editable Rules

arXiv:2607.01293v1 Announce Type: new Abstract: We present RuleChef, a framework that uses large language models (LLMs) to generate executable rules for NLP tasks such as text classification, Named En

researcharxiv-cs-cl

RusFinChain: A Russian Benchmark for Verifiable Chain-of-Thought Reasoning in Finance with Fuzzy-Aligned Evaluation

model-releasesarxiv-cs-cl

arXiv:2607.01388v1 Announce Type: new Abstract: Multi-step symbolic reasoning is essential for robust financial analysis, yet most benchmarks neglect intermediate reasoning steps. FINCHAIN introduced

SA-HGNN: Sample-Adaptive Hyperbolic Graph Neural Network for EEG-Based Depression Recognition

arXiv:2607.02063v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) have been widely used to capture spatial functional connectivity patterns to improve electroencephalography (EEG)-based d

SAB-LVLM: Significance-Aware Binarization for Large Vision-Language Models

arXiv:2607.01876v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in multimodal understanding, yet their enormous parameter scale and cross-modal

SABER: A Semantic-Aligned Brain Network Analysis Framework via Multi-scale Hypergraphs

arXiv:2607.01901v1 Announce Type: cross Abstract: Effective brain disease diagnosis requires the synergy of brain connectivity patterns and high-level semantic knowledge. Existing methods, however, la

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model

arXiv:2607.01595v1 Announce Type: new Abstract: As the scale and complexity of cloud-based AI systems continue to escalate, ensuring service reliability through rapid fault detection and adaptive reco

Safeguarding LLM Agents from Misalignment through Provenance Analysis

arXiv:2607.01236v1 Announce Type: cross Abstract: As LLM agents gain increasing access to powerful tools, ensuring that their actions are aligned with the user's intent becomes critical. When an agent

Safety Targeted Embedding Exploit via Refinement

arXiv:2607.01859v1 Announce Type: new Abstract: Safety training for large language models (LLMs) is conducted predominantly in English, leaving uncertain how well safety mechanisms generalize to low-r

Safety Testing LLM Agents at Scale: From Risk Discovery to Evidence-Grounded Verification

arXiv:2607.01793v1 Announce Type: new Abstract: LLM agents increasingly perform autonomous actions through external tools, leading to complex and evolving safety risks. However, existing safety testin

Scalable and Distributed Silhouette Approximation

arXiv:2607.01993v1 Announce Type: cross Abstract: The silhouette is one of the most widely used measures to assess the quality of a k-clustering of a dataset of n elements. Its evaluation requires no

Scaling Latent Reasoning via Looped Language Models

arXiv:2510.25741v5 Announce Type: replace Abstract: Modern LLMs are trained to 'think' primarily via explicit text generation, such as chain-of-thought (CoT), which defers reasoning to post-training a

researcharxiv-cs-cl

Tutorials

Scaling Laws for Grid-Based Approximate Nearest Neighbor Search in High Dimensions

arXiv:2607.01283v1 Announce Type: cross Abstract: Grid-based approaches to approximate nearest neighbor (ANN) search have been absent from modern scaling analyses. We present a systematic characteriza

tutorialsarxiv-cs-ai

Scaling to Multimodal and Multichannel Heart Sound Classification with Synthetic and Augmented Biosignals

arXiv:2509.11606v4 Announce Type: replace-cross Abstract: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for approximately 17.9 million deaths each year. Early det

Scaling Trends for Lie Detector Oversight in Preference Learning

arXiv:2607.01567v1 Announce Type: new Abstract: Deceptive behavior in LLMs is costly to monitor and prevent, motivating approaches such as Scalable Oversight via Lie Detectors (SOLiD) (Cundy & Gleave,

Scaling with Confidence: Calibrating Confidence of LLMs for Adaptive Test Time Scaling

arXiv:2607.01612v1 Announce Type: new Abstract: Training large language models (LLMs) with reinforcement learning (RL) has significantly advanced their performance on reasoning and question-answering

SCAPE: Accurate and Efficient LLM Training with Extreme Sparse Communication

model-releasesarxiv-cs-lg

arXiv:2607.01678v1 Announce Type: new Abstract: Communication increasingly dominates the cost of Large Language Model (LLM) pre-training, especially under data-parallel and sharded training schemes, w

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion

arXiv:2607.01777v1 Announce Type: cross Abstract: Radio frequency (RF) maps provide a compact representation of multipath propagation characteristics and are fundamental to channel modeling, coverage

Applications

SE(2) Navigation Mesh

arXiv:2607.01454v1 Announce Type: new Abstract: Global navigation for ground robots in complex multi-level environments requires representations that accurately capture traversable regions while enabl

applicationsarxiv-cs-ro

Tutorials

SelectTSL: Prompt-Guided Selective Target Sound Localization in Complex Scenarios

arXiv:2607.02343v1 Announce Type: cross Abstract: Humans can selectively attend to a target sound and estimate its direction in complex scenarios, whereas such selective localization remains challengi

tutorialsarxiv-cs-ai

Self-explainable Operator Learning for Discovering Spatial Patterns in Functional Data

arXiv:2607.02203v1 Announce Type: new Abstract: Operator learning has emerged as a powerful tool for modeling complex physical systems in functional spaces. However, their neural network-based archite

local-aiarxiv-cs-lg

Self-Gating Attention for Efficient Time Series Forecasting

arXiv:2607.02344v1 Announce Type: cross Abstract: Transformer architectures have shown strong potential in time series forecasting, where multi-head self-attention is widely used to capture temporal d

Self-Supervised Test-Time Tuning for Packet Loss Concealment

arXiv:2607.01823v1 Announce Type: cross Abstract: Packet loss concealment (PLC) reconstructs audio packets that are missing at the receiver, usually with a trained model whose parameters remain fixed

researcharxiv-cs-cl

SemHash-LLM: A Multi-Granularity Semantic Hashing Framework for Document Deduplication

arXiv:2607.01601v1 Announce Type: new Abstract: Large scale document deduplication must preserve semantic equivalence while remaining efficient over massive corpora. We present SemHash LLM, a multi gr

Separating Expert Retention from Autonomous Source Inference in Raw-ECG-Replay-Free Continual ECG Deployment

arXiv:2607.01674v1 Announce Type: new Abstract: In multi-source ECG deployment, models may need to incorporate new data sources when earlier raw ECGs cannot be retained or replayed. Freezing a pretrai

SEPS: Semantic-enhanced Patch Slimming Framework for fine-grained cross-modal alignment

arXiv:2511.01390v2 Announce Type: replace-cross Abstract: Fine-grained cross-modal alignment aims to establish precise local correspondences between vision and language, forming a cornerstone for visu

local-aiarxiv-cs-ai

Set Diffusion: Interpolating Token Orderings Between Autoregression and Diffusion for Fast and Flexible Decoding

arXiv:2607.01775v1 Announce Type: new Abstract: Discrete diffusion models have steadily improved in quality relative to autoregressive (AR) models. However, these models are normally constrained to fi

Sign in the Air to Unlock: An Interface for authentication in Virtual and Augmented Reality Powered by Point-Voxel Cross-Attention Network

arXiv:2607.01435v1 Announce Type: cross Abstract: Significant advancement of immersive technologies such as Virtual and Augmented Reality (VR/AR) and their integration into diverse aspects of modern l

local-aiarxiv-cs-lg

Sim2Real-AD: A Modular Sim-to-Real Framework for Deploying VLM-Guided Reinforcement Learning in Real-World Autonomous Driving

arXiv:2604.03497v2 Announce Type: replace-cross Abstract: Vision-language-model (VLM)-guided reinforcement learning (RL) has recently attracted significant attention for it, replacing brittle hand-cra

Agents

Simulation Based Reward Function Validation for Multi-Agent On Orbit Inspection

arXiv:2607.01367v1 Announce Type: cross Abstract: A proposed method for the control of groups of inspection spacecraft is Multi-Agent Reinforcement Learning (MARL). While MARL has already been employe

agentsarxiv-cs-ro

SimWorlds: A Multi-Agent System for Dynamic 3D Scene Creation

arXiv:2607.01766v1 Announce Type: new Abstract: LLM agents are increasingly used to translate natural language into 3D scenes in a procedural way, but existing systems focus on static output. Dynamic

SINA: A Fully Automated Circuit Schematic Image to Netlist Generator Using Artificial Intelligence

arXiv:2607.01609v1 Announce Type: new Abstract: Recent advances in Artificial Intelligence (AI) have revolutionized Electronic Design Automation (EDA), particularly through Large Language Models (LLMs

Single-Channel EEG-Based Cognitive Load Assessment in Online Learning: A Hybrid Deep Learning Approach

arXiv:2607.01795v1 Announce Type: cross Abstract: Monitoring cognitive load during online learning could help instructors identify content that learners find difficult, but remote settings remove the

Agents

SkillCoach: Self-Evolving Rubrics for Evaluating and Enhancing Agentic Skill-Use

arXiv:2607.01874v1 Announce Type: new Abstract: Skills are becoming a reusable operational layer for LLM agents, encoding SOPs, domain rules, tool workflows, scripts, and validation routines. In reali

agentsarxiv-cs-ai

Agents

SkillFuzz: Fuzzing Skill Composition for Implicit Intents Discovery in Open Skill Marketplaces

arXiv:2607.02345v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents increasingly automate software engineering tasks through reusable skills, natural-language instruction documen

agentsarxiv-cs-ai

Spanning Tree Autoregressive Visual Generation

arXiv:2511.17089v2 Announce Type: replace-cross Abstract: We present Spanning Tree Autoregressive (STAR) modeling, which can incorporate prior knowledge of images, such as center bias and locality, to

local-aiarxiv-cs-ai

SPARCLE: SPeaker-aware Aligned Representations via Contrastive Language Embeddings

arXiv:2607.01238v1 Announce Type: cross Abstract: Recent advances in speech synthesis have shifted from phoneme representations to direct grapheme modeling. While phonemes address the one-to-many mapp

Spatial Support Matters: Geometry-Aware Graph Fusion for Rainfall Field Reconstruction

arXiv:2607.01621v1 Announce Type: new Abstract: Fine-scale rainfall reconstruction is critical for urban flood modeling, but real rainfall sensing systems observe the field through incompatible spatia

Spec-AUF: Accept-Until-Fail Training under Train-Inference Misalignment for Masked Block Drafters

arXiv:2607.01893v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by drafting a block of tokens that the target model verifies left-to-right, committing only t

Spectral Imbalance Causes Forgetting in Low-Rank Continual Adaptation

model-releasesarxiv-cs-lg

arXiv:2602.00722v2 Announce Type: replace Abstract: Parameter-efficient continual learning aims to adapt pre-trained models to sequential tasks without forgetting previously acquired knowledge. Most e

Spin-Weighted Spherical Harmonics Enable Complete and Scalable E(3)-Equivariant Networks

arXiv:2607.01408v1 Announce Type: cross Abstract: E(3)-equivariant networks are promising for 3D atomistic system modeling, yet their scalability is limited by the O(L^6) complexity of the Clebsch-Gor

SPLC: Social Preference Learning for Crowd Robot Navigation

arXiv:2607.01925v1 Announce Type: new Abstract: Offline reinforcement learning (RL) holds significant potential for crowd robot navigation in human-robot coexistence applications. However, the inheren

safetyarxiv-cs-ro

SPLIT: Cross-Lingual Empathy and Cultural Grounding in English and Ukrainian LLM Responses

arXiv:2607.02049v1 Announce Type: cross Abstract: Large Language Models are increasingly deployed in emotional-support contexts and crisis-related situations. Nevertheless, their cross-lingual abiliti

Split-n-Chain: Privacy-Preserving Multi-Node Split Learning with Blockchain-Based Auditability

arXiv:2503.07570v3 Announce Type: replace-cross Abstract: Deep learning, when integrated with a large amount of training data, has the potential to outperform machine learning in terms of high accurac