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Reverse to Advance: Teleoperation-Cost Effective Hard Policy Learning from Reversed Easy Tasks

arXiv:2607.13455v1 Announce Type: new Abstract: High-quality teleoperation datasets are costly to collect, particularly for hard tasks. We observe that many tasks exhibit directional asymmetry: comple

safetyarxiv-cs-ro

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Research

RF-Informed Graph Neural Networks for Accurate and Data-Efficient Circuit Performance Prediction

DGX agent

arXiv:2508.16403v3 Announce Type: replace Abstract: Accurately predicting the performance of active radio frequency (RF) circuits is essential for modern wireless systems but remains challenging due t

researcharxiv-cs-lg

16 Jul 2026

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation

model-releasesarxiv-cs-lg

arXiv:2607.13897v1 Announce Type: new Abstract: The broadcast nature of wireless channels exposes radio-frequency (RF) networks to anomalous and malicious transmissions, making anomaly detection a fun

RoughNet: Mapping Arctic Sea Ice Roughness Using Diffusion-Based Super-Resolution of Satellite Imagery

arXiv:2607.13371v1 Announce Type: new Abstract: Accurate estimation of landfast sea ice roughness is critical for climate modeling and safe Arctic over-ice travel, yet existing approaches rely on cost

local-aiarxiv-cs-cv

S-squared-VLA: Decoupling Semantic and Spatial Streams in Vision-Language-Action Models for Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2607.13926v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable potential for high-level reasoning in autonomous driving, yet they fundamentally struggle to

Safe Overtaking for Autonomous Racing Using Hierarchical Optimization and Learning-Based Control

model-releasesarxiv-cs-ro

arXiv:2607.13348v1 Announce Type: new Abstract: Autonomous racing overtaking requires balancing competitive performance with safety under nonlinear vehicle dynamics and real-time constraints. Model Pr

Safeguard-Conditioned Uplift: Measuring Utility-Risk Frontiers for Dual-Use Biology Assistants

arXiv:2607.13039v1 Announce Type: cross Abstract: Safety evaluations for dual-use biology assistants often measure base-model capability, refusal behavior, or jailbreak success. These metrics miss a d

SAFETY SENTRY: Context-Aware Human Intervention via EXECUTE-ASK-REFUSE Routing

arXiv:2607.13594v1 Announce Type: new Abstract: LLM agents act on real-world environments through tool calls, and a single misjudged action can cause irreversible harm. The standard safeguard is a gua

safetyarxiv-cs-ai

SalientGS: Unified SfM-to-3DGS with Importance-Guided MCMC Gaussian Allocation

arXiv:2607.11285v2 Announce Type: replace Abstract: Reconstructing 3D scenes from unordered images remains bottlenecked by expensive Structure-from-Motion (SfM) preprocessing and frozen pose interface

SARFA: Segment Anything with Radiomic Feature Alignment

arXiv:2607.13323v1 Announce Type: new Abstract: The Segment Anything Model (SAM) has demonstrated strong generalizability across a variety of segmentation tasks. However, SAM often struggles in situat

safetyarxiv-cs-cv

ScanFocus: A Coarse-to-Fine Framework for Spatio-Temporal Video Grounding

arXiv:2607.13421v1 Announce Type: cross Abstract: Spatio-Temporal Video Grounding (STVG) aims to retrieve the visual trajectory of a specific object from a video stream as described by a natural langu

SCOPE-RL: Optimizing Reasoning Paths Before and After Success

arXiv:2607.11506v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) optimizes LLMs using sparse verifiable final-answer rewards. This sparse anchor reliably verif

safetyarxiv-cs-lg

Screening Is Effective for Visual Recognition

arXiv:2607.13983v1 Announce Type: new Abstract: Vision Transformer (ViT) has been widely used as a powerful framework for modeling global dependencies among image patches. However, its core component,

Tutorials

Screening of Biosecurity Features in Metagenomic Data with Evo 2 Probes

arXiv:2607.14070v1 Announce Type: cross Abstract: Genomic foundation models such as Evo 2 learn rich sequence representations, but their value for biosecurity screening is largely unexplored. We ask h

tutorialsarxiv-cs-lg

Securing LLMs in the Wild: Privacy and Security Challenges at the Edge

model-releasesarxiv-cs-lg

arXiv:2607.13088v1 Announce Type: cross Abstract: Large Language Models (LLMs) are rapidly moving from research settings into the wild, deployed on enterprise infrastructure, personal devices, and edg

Self-Improvements in Modern Agentic Systems: A Survey

arXiv:2607.13104v1 Announce Type: new Abstract: Self-improving autonomous agents are moving from research prototypes to deployed systems. The primary goal is controllable evolution, or adaptation, fro

agentsarxiv-cs-ai

Self-Improving AI Coding Agents Through Accumulated Behavioral Rules: A Closed-Loop Framework

arXiv:2607.13091v1 Announce Type: cross Abstract: LLM-based coding agents repeat the same classes of mistakes across sessions because they lack a mechanism to retain corrections from human review feed

agentsarxiv-cs-ai

Self-Improving is Often Sudden: Enlightenment-style Finetuning for Large-Scale Models

arXiv:2607.13395v1 Announce Type: new Abstract: The pursuit of autonomously self-improving models has attracted growing interest in the era of large-scale foundation models. Drawing inspiration from t

researcharxiv-cs-lg

Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training?

model-releasesarxiv-cs-cv

arXiv:2607.13192v1 Announce Type: new Abstract: Self-supervision is a powerful technique for learning visual representations from unlabeled data. Existing techniques primarily adopt a two-stage approa

SemaDiff: Identifying Semantic-Changing Commits with Generated Code and Tests

arXiv:2607.13111v1 Announce Type: cross Abstract: Distinguishing semantic-preserving commits from changing ones remains an open challenge in software repository mining. While existing approaches detec

local-aiarxiv-cs-ai

Applications

Semantic Anchoring for Robotic Action Representations

arXiv:2607.13597v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models inherit rich semantic representations from pretrained Vision-Language Models, yet fine-tuning on limited robot dem

applicationsarxiv-cs-ai

Set-shifting Behavioral Test for Harnessed Agents

arXiv:2607.13396v1 Announce Type: new Abstract: What happens to an LLM agent's tool choice when the reliable tool silently changes within an ongoing session? We borrow set-shifting from cognitive psyc

ShortOPD: Recovering Pruned LLMs with Short-to-Long On-Policy Distillation

arXiv:2607.13124v1 Announce Type: cross Abstract: Structured pruning is a hardware-friendly way to compress LLMs, but it is mostly validated on multiple-choice recognition tasks, while the same compre

safetyarxiv-cs-ai

SingGuard-NSFA: Extensible Guardrails for Agentic AI via Generative Reasoning and Real-Time Classification

arXiv:2607.13081v1 Announce Type: cross Abstract: We present nsfaguard, a guardrail framework for securing agentic AI systems against operational threats, such as prompt injection, sensitive informati

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning

arXiv:2607.13931v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) drives multimodal reasoning, but answer-level correctness does not guarantee that a vision-languag

safetyarxiv-cs-cv

Smooth Quasar-Convex Optimization with Constraints

arXiv:2510.01943v3 Announce Type: replace-cross Abstract: Quasar-convex functions form a broad nonconvex class with applications to linear dynamical systems, generalized linear models, and Riemannian

researcharxiv-cs-lg

Social Simulations: from Agent-Based Modeling to Digital Twins

arXiv:2607.13693v1 Announce Type: cross Abstract: This book chapter covers the evolution of social simulation from classical agent-based models, in which agents interact according to explicitly define

agentsarxiv-cs-ai

Spectral-Informed Neural Networks Outperform Spectral Methods in High-dimensional PDEs

arXiv:2607.13566v1 Announce Type: cross Abstract: For low-dimensional problems (dleq3), spectral methods can achieve exceptionally high accuracy. For middle-dimensional problems (4 leq d lesssim 10),

researcharxiv-cs-ai

Industry

Spectro Cloud wants to ease AI infrastructure management after raising $100M in funding

Kubernetes software startup Spectro Cloud Inc. has bagged 100 million in a late-stage funding round as it looks to solve a significant and growing problem in artificial intelligence. Powerful processo

industrysiliconangle

SPINE: Bridging the Cyber-Physical Gap with Agentic AI

arXiv:2607.13049v1 Announce Type: new Abstract: Foundation models have given robots a sophisticated brain for complex decision-making, yet deploying that intelligence into a physical platform still de

SteinGate: Tail-Sensitive Safe Reinforcement Learning via Stein Discrepancy

arXiv:2607.13175v1 Announce Type: cross Abstract: Safe reinforcement learning typically enforces safety by bounding expected cumulative costs, a criterion that often fails to detect rare but catastrop

safetyarxiv-cs-ai

STITCHER: Constrained Trajectory Planning in Complex Environments with Real-Time Motion Primitive Search

arXiv:2510.14893v4 Announce Type: replace Abstract: Autonomous high-speed navigation through large, complex environments requires real-time generation of agile trajectories that are dynamically feasib

safetyarxiv-cs-ro

Applications

STKAN: Kolmogorov-Arnold Networks for Spatio-Temporal Forecasting

arXiv:2607.13108v1 Announce Type: cross Abstract: Real-world traffic data exhibit heterogeneous spatial correlations and nonlinear temporal dynamics, posing substantial challenges for accurate spatio-

applicationsarxiv-cs-ai

STOCKTAKE: Measuring the Gap Between Perception and Action in LLM Agents with a Fair Oracle

arXiv:2607.13618v1 Announce Type: new Abstract: LLM agents are increasingly evaluated on multi-week decision tasks in which the state that drives cost is never directly observed. On such tasks the fin

Stress-Sharing: A Bio-Inspired Approach to Decentralized Fault Repair in Modular Spacecraft

arXiv:2607.13444v1 Announce Type: new Abstract: Structural damage in modular spacecraft can disrupt mechanical and communication connectivity, reducing system capability. Existing approaches rely on r

local-aiarxiv-cs-ro

Structured Reinforcement Learning for Bayesian Persuasion : Application to Intelligent Interactive Driving

arXiv:2607.13576v1 Announce Type: new Abstract: Interactive driving, wherein an intelligent lead vehicle equipped with real-time traffic data coordinates route choices of connected vehicles, offers a

safetyarxiv-cs-lg

Survival Dynamics of Neural and Programmatic Policies in Evolutionary Reinforcement Learning

arXiv:2601.04365v2 Announce Type: replace Abstract: In evolutionary reinforcement learning tasks (ERL), agent policies are often encoded as small artificial neural networks (NERL). Such representation

agentsarxiv-cs-lg

Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection

arXiv:2607.13452v1 Announce Type: cross Abstract: Incremental object detection (IOD) aims to extend detectors to new categories while retaining previously acquired knowledge. Existing methods often ad

T3HG-Editor: Text-driven 3D Human Garment Editing with Body Priors Embedded in SMPL-X

arXiv:2607.13654v1 Announce Type: new Abstract: While 3D Gaussian Editing (3DGE) has seen substantial progress, text-driven 3D human garment editing remains largely underexplored. Existing 3DGE works

Tabular Foundation Models for Discrete Choice Estimation

arXiv:2607.13314v1 Announce Type: cross Abstract: Tabular foundation models (TFMs) generate predictions on structured data via in-context learning, without task-specific estimation. We ask whether TFM

researcharxiv-cs-ai

Tactile Modality Fusion for Vision-Language-Action Models

arXiv:2603.14604v2 Announce Type: replace-cross Abstract: We propose TacFiLM, a lightweight modality-fusion approach that integrates visual-tactile signals into vision-language-action (VLA) models. Wh

Targeted Recovery of Weight-Space Mechanisms From Neural Networks

model-releasesarxiv-cs-lg

arXiv:2607.13047v1 Announce Type: new Abstract: Parameter decomposition (PD) decomposes neural networks into interpretable computational components that faithfully reflect the original network's opera

Task-Oriented Sensing and Covert Transmissions for Collaborative Multi-AUV Systems

arXiv:2607.13880v1 Announce Type: new Abstract: In underwater covert cooperative missions, autonomous underwater vehicles (AUVs) often cannot rely on active sonar to continuously obtain complete infor

local-aiarxiv-cs-lg

Task-Specific Feature Fusion Method for Multi-Task Affective Behavior Analysis

arXiv:2607.13986v1 Announce Type: new Abstract: The 11th Affective Behavior Analysis in-the-wild (ABAW11) Multi-Task Learning Challenge requires a unified system to predict valence-arousal, categorica

Tutorials

TCAM-Diff: Triplane-Aware Cross-Attention Medical Diffusion Model

arXiv:2607.13812v1 Announce Type: cross Abstract: We introduce TCAM-Diff, a novel 3D medical image generation model that reduces the memory requirements to encode and generate high-resolution 3D data.

tutorialsarxiv-cs-cv

Temperature Scaling Is Not Enough: Calibration Gaps Under Human Label Distributions

arXiv:2607.13423v1 Announce Type: new Abstract: Temperature scaling is the dominant post-hoc calibration method in modern deep learning. Its theoretical justification rests on an assumption that is ra

safetyarxiv-cs-lg

Hardware

Text2Sign: A Single-GPU Diffusion Baseline for Text-to-Sign Language Video Generation

arXiv:2607.13164v1 Announce Type: cross Abstract: Sign language is a primary communication channel for millions of Deaf and hard-of-hearing people, yet text-to-signer video generation remains costly b

hardwarearxiv-cs-cv

The 2nd International StepUP Competition for Biometric Footstep Recognition: From Steps to Strides

arXiv:2607.13905v1 Announce Type: new Abstract: The International StepUP Competition Series was launched to advance research in pressure-based footstep biometrics through a standardized and challengin