Search: “benchmark”

When Rates Are Geometric: Rate-Certificate Transfer for Contact Splittings in Optimization

arXiv:2607.23642v1 Announce Type: cross Abstract: Discrete optimization algorithms are often analyzed through continuous-time limiting ODEs, but a convergence certificate for the ODE is not automatica

researcharxiv-cs-lg

28 Jul 2026

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Model Releases

XMatchAD: A Cross-Modal Matching Perspective on Reconstruction-based Anomaly Detection

DGX agent

arXiv:2607.23658v1 Announce Type: new Abstract: The remarkable success of reconstruction-based methods in Unsupervised Anomaly Detection (UAD) lies in their ability to identify and localize anomalies

model-releasesarxiv-cs-cv

28 Jul 2026

XMix: Combating Extremely Noisy Labels via Local Smoothness in Self-Supervised Feature Space

arXiv:2607.23865v1 Announce Type: new Abstract: Supervised deep learning models rely on large, accurately labeled datasets, yet noisy annotations are often unavoidable and can severely degrade perform

researcharxiv-cs-lg

28 Jul 2026

Addressing the Orchestration Gap in Generalist Robots via Physical Agency

arXiv:2607.21725v1 Announce Type: new Abstract: General-purpose robots need to reason about their actions, combining perception, world knowledge, planning, success detection, recovery, and low-level c

safetyarxiv-cs-ro

Agentic Evaluation of Copyright Law Compliance

arXiv:2607.21799v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly perform commercial tasks that involve retrieving external content such as images and, where appropriate,

Tutorials

Alleviating Regional Shortcuts for Few-Shot Class-Incremental Learning

arXiv:2607.22072v1 Announce Type: new Abstract: Few-shot class-incremental learning (FSCIL) aims to incrementally learn novel classes with only a few samples while avoiding forgetting base classes. Ho

tutorialsarxiv-cs-cv

Are agent skills always worth using? The answer is no? This paper provides some important insights to understand this more. (bookmark it) Pa…

Are agent skills always worth using? The answer is no? This paper provides some important insights to understand this more. (bookmark it) Paper summary: Adding procedural skills to an agent is usually

agentsdair-ai--x

as the progenitor of the agent lab thesis which got the evals/routing/interactivity/ROI focus right i gotta say the biggest argument against…

as the progenitor of the agent lab thesis which got the evals/routing/interactivity/ROI focus right i gotta say the biggest argument against myself is that Claude Code got accidentally 'open sourced'

model-releasesswyx--x

Atlas 2 -- Foundation models for clinical deployment

arXiv:2601.05148v2 Announce Type: replace Abstract: Pathology foundation models substantially advanced the possibilities in computational pathology --- yet tradeoffs in terms of performance, robustnes

Automatic Map Density Selection for Locally-Performant Visual Place Recognition

arXiv:2602.21473v3 Announce Type: replace Abstract: A key challenge in translating Visual Place Recognition (VPR) from the lab to long-term deployment is ensuring a priori that a system can meet user-

CARA: Concept-Aware Risk Attention for Interpretable Collision Anticipation

arXiv:2607.22494v1 Announce Type: cross Abstract: Collision anticipation in autonomous driving requires not only accurate early warnings but also interpretable reasoning about what risk factors are be

agentsarxiv-cs-cv

CARE: Anti-entanglement Ultrasound Image Segmentation via Channel-Aware Region Extrication

arXiv:2508.13899v2 Announce Type: replace Abstract: Accurate ultrasound image segmentation is fundamentally challenged by target-context entanglement, where lesion cues are easily mixed with surroundi

Applications

CARNet Cycle-Conditioned Core Aggregation and Redistribution for Multivariate Time Series Forecasting

arXiv:2607.21681v1 Announce Type: new Abstract: Accurately modeling cross-variate dependencies remains a key challenge in multivariate time series forecasting, particularly in the presence of strong p

applicationsarxiv-cs-lg

Class-Balanced Softmax: A Bayes Theory-Based Method for Long-Tailed Recognition

arXiv:2607.22258v1 Announce Type: cross Abstract: Deep learning models using traditional softmax classifiers have achieved remarkable success in various classification tasks. However, their performanc

DB-VIO: Dual-Branch Visual Inertial Odometry with Enhanced Visual-Inertial Representation

arXiv:2607.22123v1 Announce Type: new Abstract: Visual inertial odometry (VIO) is essential for accurate 6-DoF motion estimation in mobile robotic systems. Recent learning-based VIO methods have shown

agentsarxiv-cs-ro

Tutorials

Deep Convolutional Large-Margin ell_p-SVDD for Visual Anomaly Detection

arXiv:2607.22212v1 Announce Type: new Abstract: Visual anomaly detection requires adaptive representations and reliable decision boundaries, particularly when anomalous training samples are scarce and

tutorialsarxiv-cs-cv

Diffusion Models in Medical Image Inpainting: Challenges, Solution Taxonomy, and Future Directions

arXiv:2607.21904v1 Announce Type: cross Abstract: Image inpainting aims to reconstruct missing or corrupted regions of an image while preserving as much as possible, visual and semantic consistency. I

researcharxiv-cs-cl

Do emulated quantum circuits change what CNNs look at? Performance and explainability comparison in medical image classification

arXiv:2607.21186v1 Announce Type: cross Abstract: Numerous studies have analyzed the use of hybrid quantum-classical convolutional neural networks as a promising alternative to classical deep learning

DWT-Fusion: A Signal-Based Framework for Training-Free LLM-Generated Text Detection

arXiv:2607.22026v1 Announce Type: new Abstract: Detecting LLM-generated text remains challenging under zero-shot and training-free conditions, especially when detectors must generalize across datasets

Dynamic Commonsense Coordination for Empathetic Response Generation

arXiv:2607.22136v1 Announce Type: new Abstract: Empathetic Response Generation (ERG) requires models to recognize users' emotions and generate empathetic responses. Commonsense knowledge has been show

Encoding Invisible Causation for Bridge Diagnostic Agents: Triple-Guided Retrieval-Augmented Fine-Tuning with QLoRA

arXiv:2607.21680v1 Announce Type: new Abstract: Bridge infrastructure deteriorates gradually, yet its root causes---salt intrusion, freezing, fatigue cracking, and others---remain invisible to the nak

Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers

arXiv:2607.22004v1 Announce Type: new Abstract: Energy natural gradient descent (ENGD) aligns parameter updates with the curvature of an underlying function-space energy, but existing formulations ass

Explainable quantum-compressed machine learning for complex fluid flows

arXiv:2607.21688v1 Announce Type: cross Abstract: Machine-learning surrogates of physical systems face a paradox: explainable models facing the challenge of expressivity to capture complex nonlinear f

FAIR: Feature-Augmented Implicit Regularization for AI-generated Fake Image Detection

arXiv:2607.22087v1 Announce Type: new Abstract: Generalization remains a critical bottleneck in AI-generated image detection. Because many modern generators are proprietary or adversarially modified,

Filling Before Advancing: Capability-Gap-Driven Post-Training for Scenario-Specialized Remote Sensing MLLMs

model-releasesarxiv-cs-cv

arXiv:2607.22205v1 Announce Type: new Abstract: Remote sensing multimodal large language models (RS-MLLMs) have improved general aerial-image understanding. However, Earth observation applications req

fMRI2Face: A Full-HD fMRI-Video Dataset and Geometry-Guided Neural Decoding Framework for Dynamic Human Face Reconstruction

model-releasesarxiv-cs-cv

arXiv:2607.22302v1 Announce Type: new Abstract: Reconstructing dynamic human faces from brain activity provides a powerful way to study how the mind perceives identity, expression, and facial motion.

Local Ai

FrED: External Data Influence Estimation via Domain Knowledge Graph Grounding

arXiv:2607.21615v1 Announce Type: cross Abstract: The rapid deployment of generative AI has amplified the critical need for Training Data Attribution to ensure transparency and accountability. However

local-aiarxiv-cs-lg

Generalized Gaussian Temporal Difference Error for Uncertainty-aware Reinforcement Learning

arXiv:2408.02295v4 Announce Type: replace Abstract: Conventional uncertainty-aware temporal difference (TD) learning often models TD errors as zero-mean Gaussian. This assumption can miss the heavy-ta

researcharxiv-cs-lg

Applications

Graph-Based Correlation Matrix Generation: A Convex Optimization Approach

arXiv:2607.22436v1 Announce Type: cross Abstract: This work addresses the generation of theoretical correlation matrices with prescribed sparsity patterns associated to graph structures. We propose a

applicationsarxiv-cs-lg

Great technical paper from Google. Great read on why context beats scale for agents working against unfamiliar APIs. (bookmark it) GPU kerne…

Great technical paper from Google. Great read on why context beats scale for agents working against unfamiliar APIs. (bookmark it) GPU kernel optimization has KernelBench to hillclimb on. TPUs had not

model-releasesdair-ai--x

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting

arXiv:2607.22299v1 Announce Type: cross Abstract: Forecasting multiple time-series with high-dimensional covariates presents a core challenge: unifying common temporal patterns while retaining meaning

safetyarxiv-cs-lg

Applications

Integrated Order Dispatching and Routing for Last-Mile Pickup via Deep Reinforcement Learning

arXiv:2607.22356v1 Announce Type: new Abstract: In recent years, the growing complexity of last-mile pickup operations has increased the need for fast and accurate decision-making on logistics platfor

applicationsarxiv-cs-lg

Interpretable EEG biomarkers with bag-of-waves: Spatial and temporal waveform dictionaries for low-data regimes

arXiv:2607.22508v1 Announce Type: new Abstract: Electroencephalography (EEG) is widely used to diagnose neurological conditions, but its analysis usually relies on either predefined spectral features

J-CoT: Chain-of-Thought in J-Space

arXiv:2607.21981v1 Announce Type: new Abstract: Chain-of-thought prompting improves language-model reasoning by carrying intermediate states across successive computation steps. However, relying on na

k{appa}-LoRA: Condition Numbers Reveal Which LoRA Matrices Worth Updating

arXiv:2607.22489v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has become a widely adopted technique for efficient neural network fine-tuning, decomposing model updates into low-rank matri

Language-Aware Distillation for Multilingual Instruction-Following Speech LLMs with ASR-Only Supervision

arXiv:2603.07025v2 Announce Type: replace Abstract: Speech Large Language Models (LLMs) that understand and follow instructions in many languages are useful for real-world interaction, but are difficu

Latent PDE mapping for efficient physics-informed learning across geometries with limited data

arXiv:2607.22215v1 Announce Type: new Abstract: In this study, we introduce latent PDE mapping, a broadly applicable physics-informed learning technique designed to enable efficient geometric generali

Layer-wise LoRA fine-tuning: a similarity metric approach

arXiv:2602.05988v2 Announce Type: replace Abstract: Pre-training Large Language Models (LLMs) on web-scale datasets becomes fundamental for advancing general-purpose AI. In contrast, enhancing their p

LeAct: Learning to Reason from Expert Actions

arXiv:2607.21856v1 Announce Type: cross Abstract: Modern reasoning models depend on reasoning data, today sourced from human annotations or distilled from stronger LLMs. However, a rich and largely un

LLM-Based Visual Explanation Evaluation Framework for Assessing the Explainability of Facial Skin Disease Classification Models

model-releasesarxiv-cs-cv

arXiv:2606.16794v2 Announce Type: replace Abstract: This study proposes a domain-specific LLM-based Visual Explanation Evaluation Framework for assessing visual attention explanations in facial skin d

MA-DAR: Manifold-Aligned Dynamic Adaptive Routing for Continual Temporal Knowledge Graph Reasoning

arXiv:2607.21949v1 Announce Type: new Abstract: Continual temporal knowledge graph (TKG) reasoning aims to continuously incorporate newly emerging facts while preserving previously acquired knowledge.

safetyarxiv-cs-lg

MedKGent: A Large Language Model Agent Framework for Constructing Temporally Evolving Medical Knowledge Graph

arXiv:2508.12393v3 Announce Type: replace Abstract: The rapid expansion of medical literature challenges the scalable structuring of domain knowledge. Knowledge Graphs (KGs) offer a solution, yet curr

agentsarxiv-cs-cl

Moving Beyond Diversity: Visual Token Pruning as Subspace Reconstruction for Efficient VLMs

arXiv:2606.18681v2 Announce Type: replace Abstract: Despite their remarkable performance, Vision Language Models (VLMs) incur substantial computational overhead due to the large number of visual token

Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Mode

arXiv:2607.22083v1 Announce Type: cross Abstract: We present Nanbeige4.2-3B, a compact general agentic model with 3B non-embedding parameters. It delivers strong performance across code-agent, office-

safetyarxiv-cs-cl

Neural Feature Governance: Extending Atom Prevalence

arXiv:2607.21671v1 Announce Type: new Abstract: Neural network compression and interpretability remain open challenges in modern deep learn- ing, where billion-parameter architectures deliver impressi

Hardware

NVIDIA Ising Enables Fully Automated Quantum Computer Calibration with Enhanced In-Context Learning

NVIDIA Ising Calibration 1.5 is a 31‑billion‑parameter vision‑language model that diagnoses and tunes quantum processors, delivering state‑of‑the‑art zero‑shot and in‑context learning on the QCalEval

hardwarenvidia-developer

Offline Vision-Language Navigation with Geometric Goal Localization for Outdoor Environments

model-releasesarxiv-cs-ro

arXiv:2607.22226v1 Announce Type: new Abstract: Foundation-model-based vision-language navigation (VLN) has advanced autonomous robot navigation by enabling robots to interpret natural-language instru

One Hand Watches The Other: Dynamic Multi-Agent Cooperation for Sample-Efficient Bimanual Manipulation in Dynamic Environments

arXiv:2607.22119v1 Announce Type: cross Abstract: Multi-stream robot manipulation policies achieve unparalleled sample efficiency and generalization by modeling actions relative to environmental refer