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Robustness Meets Uncertainty: Evidential Adversarial Training for Robust Selective Classification

arXiv:2607.03075v1 Announce Type: cross Abstract: Safety-critical applications require classifiers that are both robust and reliable. Adversarial training is a widely adopted defense for improving rob

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Robustness Verification of an Autonomous Underwater Vehicle-based Plankton Classifier

DGX agent

arXiv:2607.04453v1 Announce Type: cross Abstract: The assessment of planktonic standing stocks and microorganism structures is critical for understanding upper ocean biological processes. Currently, a

agentsarxiv-cs-ai

7 Jul 2026

Hardware

RoMa v2: Harder Better Faster Denser Feature Matching

arXiv:2511.15706v3 Announce Type: replace Abstract: Dense feature matching aims to estimate all correspondences between two images of a 3D scene and has recently been established as the gold standard

hardwarearxiv-cs-cv

RotateAttention: RoPE-Aware Rotation and Range Rectification for INT4 Quantized Attention in Video Generation

arXiv:2607.02584v1 Announce Type: new Abstract: In extbf{DiT-based video generation models equipped with 3D Rotary Position Embeddings (3D RoPE)}, the attention mechanism remains a primary computation

Routing Anonymity and Identifiability of Noisy Quantum Hardware

arXiv:2607.05281v1 Announce Type: cross Abstract: Present-day quantum computing is cloud-based, where a user submits a circuit to a service provider's proprietary backend hardware. While providers may

RSPO: Reward-Swap Policy Optimization for Multi-Turn LLM Agents

arXiv:2607.04713v1 Announce Type: cross Abstract: Reinforcement learning holds significant potential for training large language models (LLMs) to handle multi-turn interactive tasks. However, in long-

RSTNet: Enhancing Small-Target Recognition in Noisy SAR Imagery via Robust Feature Learning and Distribution-Aware Regression

arXiv:2602.23820v2 Announce Type: replace Abstract: SAR supports all-day-and-night oceanic observation, yet vessel identification from SAR images is hampered by speckle noise, intricate land-sea backg

RUFNet: Query-Guided Support Mask Refinement and Uncertainty Fusion based on Hybrid Mamba for Few-Shot Brain Tumor Segmentation

arXiv:2607.05035v1 Announce Type: cross Abstract: Few-shot brain tumor segmentation remains challenging due to noisy support masks, inter-patient variations between support and query images, and the l

RustMizan: A Compilable, Contamination-Aware Benchmarking Framework for Rust Vulnerabilities

model-releasesarxiv-cs-ai

arXiv:2607.04729v1 Announce Type: cross Abstract: LLM agents are increasingly applied to vulnerability analysis, but existing benchmarks have not kept pace. They typically rely on small non-compilable

S-DiverSe: Spanish Diverse Speech

arXiv:2607.03207v1 Announce Type: new Abstract: Automatic speech recognition (ASR) has advanced remarkably for standard speech, yet speech affected by neurological conditions remains a challenge. We p

researcharxiv-cs-cl

S-EMBER: A Large-Scale Benchmark for Streaming Egocentric Memory Retrieval

model-releasesarxiv-cs-ai

arXiv:2607.02689v1 Announce Type: cross Abstract: As wearable devices enable continuous first-person recording, AI assistants must reason across long time horizons to recall past experiences-a capabil

SA-ResGS: Self-Augmented Residual 3D Gaussian Splatting for Next Best View Selection

arXiv:2601.03024v3 Announce Type: replace Abstract: We propose Self-Augmented Residual 3D Gaussian Splatting (SA-ResGS), a novel framework to stabilize uncertainty quantification and enhancing uncerta

SABLE: An NDA-Safe Closed-Loop LLM Framework for Analog Circuit Optimization in Industrial EDA Flows

arXiv:2607.03701v1 Announce Type: cross Abstract: Large language models (LLMs) can propose circuit-optimization decisions, but industrial analog flows cannot expose foundry PDK content, proprietary sc

SAD-LoRA: Spectral Alignment for Low-Rank Knowledge Distillation

arXiv:2607.04306v1 Announce Type: cross Abstract: Distilling a fine-tuned teacher into a LoRA-adapted student is a standard recipe for parameter-efficient compression, but output-level KD does not exp

SAF3R: Dynamic Sparse Attention for Feed-Forward 3D Reconstruction Transformers

arXiv:2607.03612v1 Announce Type: new Abstract: Feed-forward 3D reconstruction (F3R) transformers have recently achieved remarkable success. However, scaling them to long image sequences remains chall

Safe Inference-Time Alignment via Lagrangian Reward Augmentation

arXiv:2607.02781v1 Announce Type: cross Abstract: Inference-time alignment steers a frozen language model during decoding using auxiliary reward signals, avoiding the cost of repeated weight updates.

Safe RLHF Beyond Expectation: Stochastic Dominance for Universal Spectral Risk Control

arXiv:2603.10938v2 Announce Type: replace-cross Abstract: Safe Reinforcement Learning from Human Feedback (RLHF) typically enforces safety through expected cost constraints, but the expectation captur

SafeGuard: A Multi-Agent Perception-Reasoning Framework for Social-Risk AI-Generated Video Detection

arXiv:2607.03069v1 Announce Type: new Abstract: As video generation paradigms evolve from localized manipulation to full-scene synthesis, AI-generated video detection becomes increasingly challenging,

SAGE: Synchronized Action-Gaze Recognition and Anticipation for Human Behavior Understanding

arXiv:2607.04017v1 Announce Type: new Abstract: Human object interaction (HOI), gaze pattern, and their anticipation are intricately linked, providing valuable insights into cognitive processes, inten

SalAngaBhava: A Sinhala Market Dataset for Aspect-based Sentiment Analysis

model-releasesarxiv-cs-cl

arXiv:2607.05259v1 Announce Type: new Abstract: Sentiment analysis has been a primary domain under Natural Language Processing (NLP) from its inception as it plays a vital role in both real-world and

Sample-Efficient Pareto Front Modeling for Energy-Aware Reinforcement Learning Using Bayesian Optimization

arXiv:2607.03140v1 Announce Type: new Abstract: Industrial automation increasingly demands control strategies that balance operational performance with strict energy efficiency requirements. A common

Sangam: Efficiently Serving Diffusion LLMs with the AR Stack

arXiv:2607.04206v1 Announce Type: cross Abstract: Diffusion language models (dLLMs) generate text by iteratively denoising a masked response and can commit multiple output positions per model invocati

Applications

SAVER: Mitigating Hallucinations in Large Vision-Language Models via Style-Aware Visual Early Revision

arXiv:2508.03177v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) recently achieve significant breakthroughs in understanding complex visual-textual contexts. However, hallucina

applicationsarxiv-cs-cv

SAVER: Stochastic Adaptive Variance-Driven Exploration and Reconstruction for Low-Dose Computed Tomography

arXiv:2607.03761v1 Announce Type: new Abstract: Computed Tomography (CT) is indispensable in clinical diagnostics, yet minimizing radiation dose without compromising image quality remains a critical c

Saving GPU Hours in LLM Inference System Development and Online Workloads with Simulation and DBMS-Inspired Cache Replacement Policies

arXiv:2411.07447v5 Announce Type: replace-cross Abstract: LLMs are increasingly used world-wide from daily tasks to agentic systems and data analytics, requiring significant GPU resources. While LLM i

Scalable Cross-Attention Transformer for Cooperative Multi-AP OFDM Uplink Reception

arXiv:2602.04728v3 Announce Type: replace-cross Abstract: We propose a cross-attention Transformer for joint decoding of uplink OFDM signals received by multiple coordinated access points. A shared pe

Scalable Dexterous Robot Learning with AR-based Remote Human-Robot Interactions

arXiv:2602.07341v2 Announce Type: replace Abstract: This paper focuses on the scalable robot learning for manipulation in the dexterous robot arm-hand systems, where the remote human-robot interaction

Scalable Differentially Private Data Compression via Diffusion and Stochastic Codes

arXiv:2607.03392v1 Announce Type: cross Abstract: The ever-increasing collection of personal data has created mounting pressure to develop technologies that protect sensitive aspects of individual ide

Scalable Maximal Frequent Episode Mining with Desbordante

arXiv:2607.03188v1 Announce Type: cross Abstract: Episode mining aims to extract subsequences of events that possess certain distinctive properties and constitute facts valuable to the user. Maximal f

Scalable Semantic Steering of Embedding Projections

arXiv:2607.03978v1 Announce Type: cross Abstract: Low-dimensional projections support interactive visual analysis of high-dimensional data embeddings, but their structure often does not align with ana

Hardware

Scaling Weisfeiler-Leman Expressiveness Analysis to Massive Graphs with GPUs

arXiv:2607.02603v1 Announce Type: cross Abstract: The stable coloring of the Weisfeiler-Leman (1-WL) test is a cornerstone of Graph Neural Networks because it provides an upper bound to the expressive

hardwarearxiv-cs-lg

SceneFrom3D: Geometry-Conditioned Outdoor 3D Scene Generation via View Scheduling with Object-Level Control

arXiv:2607.04540v1 Announce Type: cross Abstract: Geometry-conditioned 3D scene generation enables the creation of 3D environments from user-provided geometry, offering direct control over scene struc

Schedulable Job-Level Dependencies for Cause-Effect Chains via Graph Neural Networks

arXiv:2607.02624v1 Announce Type: cross Abstract: Modern automotive software architectures comprise large sets of mixed-criticality functions executing on shared multi-core platforms with strict real-

Score Distributions, Not Cells: Evaluating Single-Cell Perturbations Under Class Overlap

arXiv:2607.04595v1 Announce Type: new Abstract: Most classification problems assume the classes are roughly separable, so that an individual sample can usually be assigned to one class. Single-cell pe

Score-Regularized Joint Sampling with Importance Weights for Flow Matching

arXiv:2511.17812v3 Announce Type: replace-cross Abstract: Flow matching models effectively represent complex distributions, yet estimating expectations of functions of their outputs remains challengin

Applications

SE-UNet: Singular Equivariant Imaging for Real-World Constrained Generation

arXiv:2607.02628v1 Announce Type: new Abstract: While diffusion models have revolutionized image synthesis, their application to real-world inverse problems is often hampered by the need for massive d

applicationsarxiv-cs-cv

SEAM: Smooth Execution of Action-Chunked Motion for Vision-Language-Action Policies

arXiv:2607.04609v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies that execute fixed-length action chunks can exhibit multimodal bifurcation: a cross-chunk inconsistency in which a

safetyarxiv-cs-ro

Agents

Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation

arXiv:2607.05382v1 Announce Type: cross Abstract: Visual generators excel at rendering, but they confidently fabricate what they do not know. User requests are unbounded, evolving, and deeply long-tai

agentsarxiv-cs-ai

Securing Multi-Tool AI Agent Chains With Dynamic, Real-Time Compositional Policies

arXiv:2607.03423v1 Announce Type: cross Abstract: Modern AI agent implementations such as frontier coding agents chain multiple tools at runtime that create a security surface that per-tool guardrails

Seduced by the Narrative: Assessing Rule Adherence in Semi-Open Textual Sandboxes

model-releasesarxiv-cs-ai

arXiv:2607.02802v1 Announce Type: cross Abstract: As LLMs are increasingly deployed as autonomous adjudicators in semi-open textual game environments, robust rule adherence becomes critical when user

See the Emotion: A Facial Emoji Proxy Modeling for EEG Emotion Recognition

arXiv:2607.02912v1 Announce Type: new Abstract: Despite the high accuracy of EEG-based emotion recognition, existing models remain opaque 'black boxes', lacking semantic grounding between abstract neu

Seeing Once is Enough? Online Geometry-Aware Token Pruning for 3D Question Answering

arXiv:2607.04079v1 Announce Type: cross Abstract: Recent Multi-modal Large Language Models (MLLMs) have demonstrated remarkable performance on 2D question answering tasks. However, extending these mod

Tutorials

Seeing Through WiFi: Lightweight Human Pose Estimation with Dynamic Kernel Attention

arXiv:2607.03196v1 Announce Type: new Abstract: WiFi-based human pose estimation (HPE) enables the detection and interpretation of human body positions and movements without the need for wearable devi

tutorialsarxiv-cs-cv

SeeMe: Mitigating Hallucinations in Large Vision-Language Models through Effective Visual Token Engineering

arXiv:2607.04163v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in visual understanding tasks such as image captioning and visual question answ

Selecting Samples on Graphs: A Unified Dataset Pruning Framework for Lossless Training Acceleration

arXiv:2606.12913v2 Announce Type: replace-cross Abstract: The rapid growth of modern training datasets has significantly increased computational cost, motivating dataset pruning~(DP) methods which ret

Selective Disclosure Watermarking for Large Language Models

arXiv:2607.05353v1 Announce Type: cross Abstract: Watermarking methods embed imperceptible and verifiable signals into text generated by large language models (LLMs). Existing approaches include zero-

Selective Mask Propagation for Multi-Object Tracking

arXiv:2606.13033v2 Announce Type: replace Abstract: Multi-object tracking has a heavy-tailed difficulty distribution: most frames are easy for a lightweight base tracker, while a small fraction are in

Selectivity Estimation for Linear Queries via Online Learning

arXiv:2607.02895v1 Announce Type: cross Abstract: Learning-based approaches for selectivity estimation in databases have gained significant traction in recent years. However, theoretical studies of th