Search: “framework”

arXiv:2608.18714v1 Announce Type: cross Abstract: Machine-learned models are replacing first-principles calculations across materials discovery, and physical symmetry is the central guarantee built in

tutorialsarxiv-cs-lg

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Agents

Adversarial Review: Structured Disagreement for Grounded Agentic Code Review

DGX agent

arXiv:2608.18167v1 Announce Type: new Abstract: Early multi-agent LLM systems often used role-separated teams, yet scaling agent count yields diminishing returns on repository-level coding tasks. Rece

agentsarxiv-cs-ai

20 Aug 2026

AlphaClifford: Efficient Clifford Synthesis and Transpilation with Model-based RL

arXiv:2608.18946v1 Announce Type: cross Abstract: Clifford circuits play a foundational role in quantum computing, particularly due to their importance in quantum error correction and fault-tolerant l

researcharxiv-cs-ai

Beyond Predictive Fairness: Quantifying Attribution Consistency Across Demographic Groups in Diabetic Retinopathy Screening

arXiv:2608.18759v1 Announce Type: cross Abstract: Fairness in medical imaging is commonly evaluated through subgroup performance metrics, yet it remains unclear whether models rely on consistent visua

Bidirectional representational alignment between biological and artificial neural networks

arXiv:2608.18244v1 Announce Type: cross Abstract: Recent work has shown that representational alignment between biological and artificial neural networks is asymmetric: model representations predict n

Can a Lightweight Multimodal Model Estimate LLM Reasoning Performance? A Study for Compute-Optimal Document Inference

model-releasesarxiv-cs-ai

arXiv:2608.18591v1 Announce Type: new Abstract: Uniformly allocating inference reasoning budgets to LLMs is expensive and prone to over-thinking penalties; especially in document tasks where visual la

Candidate-Fate Accounting for Transparent Sensor Diagnostic Pipeline Search

arXiv:2608.18665v1 Announce Type: new Abstract: Industrial sensor diagnostics relies on preprocessing, representation, and classification pipelines, making automated pipeline search useful for reducin

applicationsarxiv-cs-ai

Agents

CentaurBench: Benchmarking LLM Capabilities on Augmenting vs. Automating Real-World Work Tasks

arXiv:2608.18554v1 Announce Type: cross Abstract: Most LLM benchmarks rank models on their ability to automate work tasks. In practice, however, models are often used to assist other (human or LLM) ag

agentsarxiv-cs-ai

Clinically Structured Surrogate Rewards for Post-SFT Medical Image Captioning

arXiv:2608.18654v1 Announce Type: new Abstract: Medical image captioning requires translating heterogeneous visual evidence into concise clinical descriptions, where errors in findings, assertion stat

Tutorials

Composed Historical Image Retrieval by Modeling Temporal Representations

arXiv:2608.18694v1 Announce Type: cross Abstract: While time evolves linearly, the geometry of neural embedding spaces is inherently multi-dimensional, often chaotic, and difficult to interpret. In pr

tutorialsarxiv-cs-ai

DART-SD: Diamond-topology Aware Retrieval and Tuning for Self-Distillation of Multi-Turn Tool-Calling Agents

arXiv:2608.18524v1 Announce Type: cross Abstract: Equipping Large Language Models (LLMs) with multi-turn tool-calling capabilities is essential for building autonomous agents. However, progress is fun

Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements

arXiv:2608.18294v1 Announce Type: cross Abstract: An increasing number of scholars use AI to measure variables they subsequently include in downstream analyses. Although AI-measured variables are ofte

DynCur-Geo: Dynamic Curiosity Reward Shaping for Multimodal Active Geo-Localization

arXiv:2608.18673v1 Announce Type: new Abstract: Active geo-localization enables low-altitude UAVs to search for specified targets from limited local aerial observations, supporting time-sensitive appl

Evaluation of Image Matching Methods for Visual Odometry on UAVs

arXiv:2608.18624v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) are becoming a powerful tool for many environmental monitoring and transport applications. Yet, their reliance on Global

researcharxiv-cs-cv

Execution-grounded evaluation reveals hidden failures in language-model calculations for environmental science

model-releasesarxiv-cs-cl

arXiv:2608.18726v1 Announce Type: new Abstract: Large language models are increasingly used for quantitative work in the environmental sciences, yet existing evaluations score only final answers, leav

extsc{TestifAI}: Tomography-Based Testing for Deep Learning Systems

arXiv:2608.18900v1 Announce Type: new Abstract: As AI systems are increasingly deployed in safety-critical application domains (e.g., autonomous driving), associated risks increase too. Deep learning

Eyes on the Image: Gaze Supervised Multimodal Learning for Chest X-ray Diagnosis and Report Generation

model-releasesarxiv-cs-cv

arXiv:2508.13068v2 Announce Type: replace Abstract: Medical vision-language models still struggle to match radiologists' attention and to verbalize findings with explicit spatial grounding. We address

Fair Multi-View Determinantal Coresets via Adaptive NEPv

arXiv:2608.18181v1 Announce Type: cross Abstract: Selecting a small, diverse subset from a large candidate pool often means balancing several incompatible notions of diversity. In trademark curation,

FairGlucose: A CGM Fairness Benchmark Reveals Subgroup Disparities Hidden in Population-Level Validation

model-releasesarxiv-cs-ai

arXiv:2608.18296v1 Announce Type: cross Abstract: As CGM-based AI tools approach clinical deployment, whether their accuracy is equitable across patient demographics remains insufficiently tested. To

FD-CanKD: Frequency-Decoupled Cross-Attention Distillation as a Refinement Prior for Compact Object Detectors

arXiv:2608.18590v1 Announce Type: new Abstract: Compact object detectors are suitable for resource-constrained visual perception, but their limited representation capacity creates an accuracy gap rela

GAPL: Grounded Action-effect Policy Learning for LLM-Based Trajectory Planning

arXiv:2608.18254v1 Announce Type: new Abstract: Trajectory planning for autonomous driving requires both high-level reasoning and precise low-level control. Large Language Models (LLMs) offer semantic

safetyarxiv-cs-ro

GCNO: Gramian Chebyshev Neural Operator for Physics-Based Compression of Wireless Channels

arXiv:2608.18522v1 Announce Type: cross Abstract: Large antenna arrays allow wireless systems to serve more users and achieve higher data rates, but they also make channel feedback expensive: the rece

researcharxiv-cs-ai

Geometric Data Perturbation with Noisy-Anchor Alignment for Privacy-Preserving Collaborative Learning

arXiv:2608.18749v1 Announce Type: new Abstract: Geometric Data Perturbation (GDP) enables one-shot, privacy-preserving collaborative learning: each participant applies a distance-preserving transforma

safetyarxiv-cs-lg

GrabVG: Graph-Attentive Binding for Visual Grounding in UAV Imagery

arXiv:2608.18996v1 Announce Type: cross Abstract: Visual grounding in Unmanned Aerial Vehicle (UAV) imagery aims to localize a target object in complex bird's-eye-view scenes according to a natural la

GraphK: Variable-Size Graph Generation with Efficient Edge Construction

arXiv:2608.18777v1 Announce Type: new Abstract: Graph generation models have advanced significantly with deep learning, yet they remain limited in scalability, flexibility, and ability to model underl

applicationsarxiv-cs-lg

High-Flux Count-Free Single-Photon 3D Cameras

arXiv:2608.18306v1 Announce Type: new Abstract: Single-photon cameras based on single-photon avalanche diode (SPAD) technology are gaining popularity for 3D sensing, thanks to their extreme sensitivit

applicationsarxiv-cs-cv

Hardware

How Generative Recommenders Are Redefining RecSys at Scale

Generative recommenders (GRs) replace traditional embedding‑based methods with transformer‑style sequence models like HSTU and Semantic IDs, addressing scalability, cold‑start, and long‑tail issues in

hardwarenvidia-developer

I built a visual multi-agent workflow editor that exports runnable CrewAI code — here’s a 5-agent workflow running locally with Ollama

I've been building AgentGraph Studio, a visual editor for designing multi-agent workflows and exporting them as runnable Python code. One thing I wanted to verify was whether the generated code actual

model-releasesr-ollama

Improving Rural Medication Safety with AI: A Scoping Review

arXiv:2608.18135v1 Announce Type: new Abstract: Introduction: Medication errors (MEs) represent a significant threat to global healthcare systems, contributing to patient harm. Introducing artificial

Institutional Prestige as Geographic Bias in Large Language Models: Evidence from Three Factorial Experiments with Bootstrap Confidence Intervals

arXiv:2608.18107v1 Announce Type: cross Abstract: We investigate whether large language models (LLMs) systematically discriminate in candidate evaluations based on applicant name ethnicity and/or inst

Language Models for Portuguese: A Systematic Mapping Study

arXiv:2608.18138v1 Announce Type: cross Abstract: In recent years, the rapid development of language models has transformed the field of Natural Language Processing through a wide range of application

researcharxiv-cs-ai

Learning Canonical Register Automata over Ordered Data Domains

arXiv:2608.18765v1 Announce Type: new Abstract: Register automata are finite automata equipped with memory that recognize data languages over infinite alphabets. In this work, we investigate active le

researcharxiv-cs-cl

LongNovel: A Multi-Scale Benchmark for Hallucination Detection in Long-Context Novel Summarization

model-releasesarxiv-cs-cl

arXiv:2608.18082v1 Announce Type: new Abstract: Although context windows have expanded significantly in recent years, hallucinations in long-context summarization remain a challenge. Long novels are b

Many Optimizers But Only One Training Path: Repeated Resampling for Adaptive Optimizer Selection

arXiv:2608.18810v1 Announce Type: new Abstract: An optimizer is usually chosen before training a deep neural network and then kept fixed. Treating optimizer choice as a hyperparameter could boost perf

NanoSleep: A Parameter-Efficient Hybrid Temporal Convolutional Network for Single-Channel Sleep Stage Classification

model-releasesarxiv-cs-lg

arXiv:2608.18571v1 Announce Type: new Abstract: Sleep stage classification from single-channel electroencephalography (EEG) is essential for wearable and home-based sleep monitoring. However, many dee

Off-Manifold Collapse in Guided Protein Language Models

arXiv:2608.18597v1 Announce Type: new Abstract: Protein language models are widely used priors for protein sequence design, and a growing body of work controls them at inference time as an alternative

Online Learning for Dynamic Constellation Topologies

arXiv:2603.25954v2 Announce Type: replace Abstract: The use of satellite networks has increased significantly in recent years due to their advantages over purely terrestrial systems, such as higher av

Operationalizing Narrative Entropy (Sn): A Two-Scene Registered Pilot Report and Pre-Validation Protocol

arXiv:2608.18109v1 Announce Type: new Abstract: Narrative Entropy (S_n) is a proposed quantitative descriptor within the Bulut Doctrine, intended to capture the rate at which a narrative text imposes

researcharxiv-cs-cl

Local Ai

Optic Disc Segmentation in Fundus Images: From Classical Image Processing and Deformable Models to Modern AI

arXiv:2608.18367v1 Announce Type: cross Abstract: Accurate localization and segmentation of the optic disc (OD) are important for retinal image analysis and glaucoma assessment, yet remain challenging

local-aiarxiv-cs-cv

Performance Drift Detection in Machine Learning as a Service (MLaaS) for IoT Environments

arXiv:2608.18555v1 Announce Type: cross Abstract: Machine Learning as a Service (MLaaS) is a powerful cloud paradigm enabling data-driven intelligent applications in Internet of Things (IoT) environme

applicationsarxiv-cs-ai

Personalized Autonomous Driving via Optimal Control with Clearance Constraints from Questionnaires

arXiv:2602.08326v2 Announce Type: replace Abstract: Driving without considering the preferred separation distance from surrounding vehicles may cause discomfort for users. To address this limitation,

safetyarxiv-cs-ro

PLASMA: A Layout-Aware Benchmark Reveals Memory Layout Matters for Graph-based ANNS on GPU

model-releasesarxiv-cs-cv

arXiv:2508.15436v2 Announce Type: replace-cross Abstract: We propose a extbf{P}latform for extbf{L}ayout-extbf{A}ware extbf{S}earch and extbf{M}emory extbf{A}rrangement (extbf{PLASMA}), a unified eval

Position: Current Model Cards Are Insufficient for Downstream Governance of Open-Weight Foundation Models

arXiv:2608.18086v1 Announce Type: new Abstract: The growth of open-weight foundation models (OWFMs) has prompted the AI community to re-evaluate strategies for effective downstream governance. Althoug

Agents

Professional Software Developers Don't Vibe, They Control: AI Agent Use for Coding in 2025

arXiv:2512.14012v2 Announce Type: replace-cross Abstract: The rise of AI agents is transforming how software can be built. The promise of agents is that developers might write code quicker, delegate m

agentsarxiv-cs-ai

ReX-Shot: Single-Image Rephotography via Geometry- and Camera-Grounded Generation

arXiv:2608.18593v1 Announce Type: new Abstract: Single-image rephotography aims to synthesize new shots of a scene from a single reference image with specified viewpoints, focal lengths, and photograp

Scalable Geospatial Machine Learning for Power-Line Asset Risk: Integrating Remote Sensing for Lightning and Vegetation Risk Modelling

arXiv:2608.18611v1 Announce Type: new Abstract: Electric power networks are increasingly exposed to weather-sensitive failure mechanisms that require asset-level, spatially explicit risk modelling for

Seasonal false alarms in customer churn and decline early-warning systems: adjacent-window labels confound seasonality with decline, and a year-over-year correction

arXiv:2608.18174v1 Announce Type: cross Abstract: Customer decline early-warning systems feed account-manager action lists, and every flagged account consumes intervention capacity. In a deployed busi

applicationsarxiv-cs-lg

SED-FOD: Scattering-Aware Expert Decomposition for Few-Shot Cross-Sensor SAR Object Detection

arXiv:2608.18755v1 Announce Type: new Abstract: Synthetic aperture radar (SAR) object detection is an important part of remote sensing interpretation. However, because of variations in frequency band,