Search: “benchmark”

SAM2Dual: Training-Free, Dual Memory for Long-Term Video Object Segmentation

arXiv:2608.18640v1 Announce Type: new Abstract: Long-term video object segmentation (VOS) remains challenging due to error accumulation under extended occlusions, re-appearance, and scene changes. Alt

researcharxiv-cs-cv

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SCORE: Subject Coordinate Recovery for Label-Free Cross-Subject EEG-to-Image Retrieval

DGX agent

arXiv:2608.19134v1 Announce Type: new Abstract: Accurate visual decoding can reveal how the brain represents visual information and recover perceived content from neural signals such as electroencepha

safetyarxiv-cs-lg

20 Aug 2026

Score the Algebra, Not the Span: Dimension Reduction for Transfer Operator Models of Dynamical Systems

model-releasesarxiv-cs-lg

arXiv:2608.18918v1 Announce Type: new Abstract: Dimension reduction for dynamical systems is standard practice, and the standard route is spectral: model the transfer (Koopman) operator by its leading

Shared Circuits for Shared Grammar: Tracing Subject-Verb Agreement Across Languages

arXiv:2608.18545v1 Announce Type: new Abstract: Multilingual large language models often generalize across languages, and prior work suggests that their internal mechanisms can overlap cross-lingually

researcharxiv-cs-cl

SkillGate: Training In-Policy Skill Selection in Long-Horizon Agents

arXiv:2608.18852v1 Announce Type: new Abstract: Agent frameworks increasingly package procedural knowledge as skills: instruction files an agent reads on demand, while public libraries now hold thousa

SkillNet: Create, Evaluate, and Connect AI Skills

arXiv:2603.04448v2 Announce Type: replace Abstract: Current AI agents can flexibly invoke tools and execute complex tasks, yet their long-term advancement is hindered by the lack of systematic accumul

SPK: Eliciting Structured Prior Knowledge for Interpretable Out-of-Distribution Detection in Real-Time Object Detection

arXiv:2608.19080v1 Announce Type: new Abstract: Object detectors often produce over-confident predictions for objects outside their training categories, leading to so-called out-of-distribution (OoD)

safetyarxiv-cs-cv

Stability-Aware Feature Design for Robust Watermark Detection in Machine-Generated Text

model-releasesarxiv-cs-cl

arXiv:2608.18102v1 Announce Type: new Abstract: The widespread adoption of large language models (LLMs) has intensified the demand for principled methods to distinguish human from machine-generated te

The Embodiment Gap in Robot Foundation Models

arXiv:2608.18433v1 Announce Type: new Abstract: Robot foundation models (RFMs), including vision-language-action (VLA) policies, are often discussed through a scaling view: more data, larger models, a

researcharxiv-cs-ro

Agents

Training-Free Inference-Time Self-Reflection and Cost-Bounded Early Stopping for Large Language Models

arXiv:2608.18884v1 Announce Type: new Abstract: Reinforcement-learning training of reasoning LLMs (e.g., GRPO) is expensive and requires a controllable environment, committing every contribution to a

agentsarxiv-cs-ai

Applications

Transportable Causal Effect Estimation across Networks under Interference

arXiv:2608.18932v1 Announce Type: new Abstract: Estimating causal effects under network interference typically assumes that the network used for training and the network used for deployment coincide.

applicationsarxiv-cs-lg

Verifiable abstention makes AI leak diagnosis accountable in water distribution networks

arXiv:2608.18836v1 Announce Type: new Abstract: Utilities lose a substantial share of treated water to leakage, yet rarely trust artificial-intelligence localizers to dispatch crews: guessing everywhe

When Do LLMs Actually Help? Evaluating LLMs as Data Quality Annotators

arXiv:2608.18158v1 Announce Type: cross Abstract: LLMs have been increasingly used to catch data quality issues automatically, but we know very little about how consistent these judgments actually are

When Safety Overrides Vision: Exploring Dynamics between Vision Influence and Safety Alignment in Vision-Language Models

arXiv:2608.18628v1 Announce Type: cross Abstract: Aligned vision-language models (VLMs) are designed to balance grounded visual reasoning with safe generation behavior. However, we observe a striking

safetyarxiv-cs-cl

Tutorials

X-LMC: Cross-View Spatiotemporal Collateral Circulation Scoring from DSA

arXiv:2608.18986v1 Announce Type: new Abstract: Digital subtraction angiography (DSA) is the reference standard for leptomeningeal collateral (LMC) assessment, providing critical prognostic insights t

tutorialsarxiv-cs-cv

You Are What You Prompt: Prompt Quality, Domain Shift, and Uncertainty in Agrifood Vision-Language Models

arXiv:2608.18116v1 Announce Type: new Abstract: Vision-language models enable zero-shot classification through natural language prompts, but performance is sensitive to prompt formulation, especially

safetyarxiv-cs-cl

Zero-Shot SAM2 Segmentation and Vision Transformer-Based Recognition of Elamite Cuneiform Symbols from Degraded Tablet Images

arXiv:2608.18544v1 Announce Type: new Abstract: Automated recognition of ancient cuneiform script poses a compound signal-degradation problem: the three-dimensional relief of clay tablets creates spat

Advancing Health Equity through Multi-Level Fairness in Health Informatics

arXiv:2608.16902v1 Announce Type: cross Abstract: The increasing integration of machine learning in healthcare has highlighted critical challenges related to fairness, transparency, and health equity.

safetyarxiv-cs-lg

Against Political Polarization: A Unified Framework for Tracing Evolving Political Ideologies on Social Media

arXiv:2608.17987v1 Announce Type: cross Abstract: The rapid growth of social media has greatly influenced political discourse, highlighting the need to understand individual political ideologies and t

Local Ai

AntLing’ve open-sourced 6 Base Model checkpoints for Ling-3.0-tiny & Ling-3.0-flash, covering pre-trained, mid-trained, and WSM-merged stages.

None has undergone post-training, giving researchers flexible starting points for continued pre-training, fine-tuning, and further research. Two key highlights: - They use WSM to replace LR decay with

local-air-localllama

B-Spline Embedded Structure Learning for 3D Tooth Segmentation

arXiv:2608.17291v1 Announce Type: new Abstract: Accurate 3D tooth segmentation forms the cornerstone of digital dentistry, yet it remains a formidable challenge due to the inherent intricacy of real-w

Beyond Instrument Motion: Recognizing Tissue Tension Toward Surgical Skill Assessment

arXiv:2608.17935v1 Announce Type: new Abstract: Surgical performance assessment in minimally invasive surgery largely relies on manual expert review, making it time-consuming, subjective, and difficul

Local Ai

Causal Local States: Scalable Simultaneous Causal Network Inference and Forecasting for Dynamical Systems

arXiv:2608.17452v1 Announce Type: new Abstract: Machine learning methods predict many real-world systems with remarkable accuracy, but they are typically treated as black boxes that offer no insight i

local-aiarxiv-cs-lg

Code as Representation: A Compilable Parsing Paradigm for Academic Documents

model-releasesarxiv-cs-cl

arXiv:2608.17550v1 Announce Type: cross Abstract: Academic papers are a primary carrier of scientific knowledge, yet most of this knowledge remains locked in PDFs that are optimized for human reading

Cognitive Graph Intelligence for Adaptive and Robust DDoS Attack Detection in Next Generation Networks

arXiv:2608.17352v1 Announce Type: new Abstract: Distributed Denial-of-Service (DDoS) attacks threaten network availability, requiring a cognitive detection process that senses traffic, infers intent,

CoinVE-200K: A Large-Scale High-Quality Dataset for Compositional Instruction-Guided Video Editing

arXiv:2608.17566v1 Announce Type: new Abstract: The quality and diversity of instruction-based video editing datasets are steadily improving, yet existing datasets mainly focus on single editing opera

COMIC: Reference-Aware Safety Gating for Multimodal Large Language Models

arXiv:2608.17234v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly used to interact with screenshots, scanned documents, diagrams, and other visually grounded

Community Concealment from Graph Neural Networks

arXiv:2602.12250v2 Announce Type: replace Abstract: Graph neural networks (GNNs) enable powerful unsupervised learning of communities. However, such inference may inadvertently expose sensitive group

researcharxiv-cs-lg

Comparative Study of Out-of-the-Box Technology for Automatic Target Detection and Recognition

arXiv:2608.17917v1 Announce Type: cross Abstract: Automatic Target Detection and Recognition (ATD/R) is critical for military decision support and (semi-)autonomous operations. Recent advances in obje

CompCPZ: Preserving Multi-Modal Intent in Language-Guided Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.17717v1 Announce Type: new Abstract: A robot asked to 'place the cup near the red plate or the blue plate' may reach the centroid between them and appear geometrically successful, while sat

Continuity-Driven Representation Learning for Industrial Defect Detection

arXiv:2608.17362v1 Announce Type: new Abstract: Industrial defect detection differs from natural-image object detection because inspection images are captured under controlled conditions and contain l

Cross-Domain Generalization in Machine Unlearning via Label-Conditioned Energy Magnitude Regularization

arXiv:2608.17942v1 Announce Type: new Abstract: Machine unlearning removes the influence of specific data from a trained model. However, most methods treat the forgotten concept as isolated. In this p

Agents

D^2ACCI: A Dual-Loop Diagnostic Protocol for Evidence-Preserving Agent Memory

arXiv:2608.17756v1 Announce Type: new Abstract: Memory is a key capability of LLM agents. Persistent memory extends this across sessions---enabling recall, revision, and personalization. Yet its multi

agentsarxiv-cs-ai

Agents

DeAR: Decentralized Agentic Reasoning via Capability Grounding and Collaborative Thought Navigation

arXiv:2608.17282v1 Announce Type: new Abstract: Existing agentic reasoning systems typically rely on centralized protocols. This design introduces routing bottlenecks and static role allocations that

agentsarxiv-cs-ai

Deep Academic Survey: Stateful Agentic Closed-Loop Paradigm for Academic Survey Automation

arXiv:2608.18034v1 Announce Type: new Abstract: Academic surveys play a central role in organizing rapidly expanding scholarly literature, yet their construction requires extensive paper analysis, coh

Hardware

Developing NVIDIA Holoscan Applications with CLI, Skills, and AI Coding Agents

The blog describes the iterative development of a real‑time endoscopic tool‑segmentation application using NVIDIA Holoscan, HoloHub, and an AI coding agent. Each cycle consisted of engineering-defined

hardwarenvidia-developer

Dijkstra as an Oracle for Online Stochastic Shortest Path Navigation with Provable Guarantees

arXiv:2608.17703v1 Announce Type: cross Abstract: Mobile robots that operate in side by side with humans and critical facilities must reach their goals at low cost, despite often unknown true traversa

researcharxiv-cs-ai

DiSCO: Defending text-to-image generation through distribution-guided contrastive prompt optimization

arXiv:2608.17067v1 Announce Type: new Abstract: As text-to-image generative models advance, they raise critical safety concerns, particularly the generation of Not-Safe-For-Work (NSFW) content such as

DistillPath: An Efficient 22M Distilled Pathology Encoder Approaching Large Foundation Model Performance

arXiv:2608.17872v1 Announce Type: new Abstract: Many high-performing pathology tile encoders are now foundation models with hundreds of millions to over a billion parameters. Encoding and storing the

Do LLMs Know a Good Hypothesis When They See One? Logit-Based Energy Scoring Outperforms Prompted LLM-as-Judge for Scientific Hypothesis Ranking

arXiv:2608.17270v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for scientific hypothesis generation. However, evaluating generated hypotheses remains a challenge fo

Dripper: Token-Efficient Main HTML Extraction with a Lightweight LM

model-releasesarxiv-cs-cl

arXiv:2511.23119v3 Announce Type: replace Abstract: High-quality main content extraction from web pages is a critical prerequisite for constructing large-scale training corpora. While traditional heur

Dynamic Entanglement-Weighted Pruning for Quantum Federated Unlearning in Supply-Chain Risk Prediction

model-releasesarxiv-cs-lg

arXiv:2608.17069v1 Announce Type: cross Abstract: Federated deployments of variational quantum classifiers are attractive for cross-organisation risk prediction in supply chains, because raw data neve

Efficient RLVR Scheduling via Graph-Structured Online Difficulty Estimation

arXiv:2608.17941v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models but relies on costly rollout explor

researcharxiv-cs-ai

Hardware

Evaluating AI Agent Skill Performance with NVIDIA SkillEvaluator

NVIDIA SkillEvaluator is an open‑source framework that measures how pre‑verified “skills” improve AI agent performance through static checks, distinctiveness analysis, and live task runs in isolated e

hardwarenvidia-developer

Exact Reformulation and Optimization for Direct Metric Optimization in Binary Imbalanced Classification

model-releasesarxiv-cs-lg

arXiv:2507.15240v2 Announce Type: replace Abstract: For classification with imbalanced class frequencies, i.e., imbalanced classification (IC), standard accuracy is known to be misleading as a perform

FetchMan: Learning Visual Humanoid Loco-Manipulation Policies from Simulated Experiences

model-releasesarxiv-cs-ro

arXiv:2608.17027v1 Announce Type: new Abstract: Visual loco-manipulation policies that can generalize to novel scenes and objects have long been a goal of robotics research. However, today's data-hung

Fool's Gold: Defensive Deception Against Safety-Removal Attacks on Open-Weight Models

arXiv:2608.17202v1 Announce Type: new Abstract: Safety alignment in open-weight language models is trivially removable: abliteration projects a refusal-mediating direction out of the weights in minute

From Abductive Explanations to Global Logical Rules for Node Classification in SGCs

arXiv:2608.17103v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) have achieved remarkable performance in node classification tasks, motivating growing interest in methods capable of expl