Search: “evaluation”

Small Object Detection in Drone Aerial Imagery with LAF-YOLOv10

arXiv:2609.14560v1 Announce Type: new Abstract: General-purpose object detectors lose accuracy on UAV footage, where targets span only a handful of pixels and onboard compute is limited. Prior work co

Agents

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Speak to the City: Multimodal Resolution for Outside-the-Vehicle References

DGX agent

arXiv:2609.14691v1 Announce Type: cross Abstract: As autonomous vehicles and Extended Reality (XR) headsets enable novel in-car interactions, seamlessly querying physical landmarks, known as Outside-t

agentsarxiv-cs-cl

15 Sept 2026

Stellar Colosseum: A Many-Agent Harness for Long-Horizon Research in Mathematics and Theoretical Computer Science

arXiv:2609.15983v1 Announce Type: new Abstract: Language models can produce plausible short proofs, but may still be unreliable on long-horizon research problems, where progress depends on a sequence

StepPrune: Adaptive Sequential Visual Token Selection across Multimodal Large Language Models

arXiv:2609.13804v1 Announce Type: new Abstract: Visual prefixes account for a major portion of the per-layer computation in multimodal large language models (MLLMs), making visual-token pruning a dire

researcharxiv-cs-cv

Surrogate-Assisted Genetic Programming with Phenotypic Characterisation in Dynamic Multi-Mode Project Scheduling

arXiv:2609.14418v1 Announce Type: cross Abstract: Dynamic multi-mode resource-constrained project scheduling requires decisions to be made under precedence constraints, limited resources, multiple exe

Applications

Task-Specified Active Metrological Inspection with Measurement-Steered VLA Manipulation and Deterministic Evidence Gating

arXiv:2609.14219v1 Announce Type: cross Abstract: High-mix low-volume (HMLV) manufacturing requires inspection systems to adapt to changing parts, specifications, and work orders without repeated task

applicationsarxiv-cs-ai

TEAR: Table Extraction with Attribute Recommendation from Texts via Large Language Models

arXiv:2609.15205v1 Announce Type: cross Abstract: Table extraction from texts is an important task for information systems, and recent approaches that prompt large language models (LLMs) with instruct

The Attribution-Compression Frontier in Retrieval-Augmented Generation

arXiv:2609.14245v1 Announce Type: cross Abstract: Context compression reduces generator input in retrieval-augmented generation, but answer quality alone does not characterize citation attribution. We

The average-farmer illusion in language-model simulations of agricultural decisions

arXiv:2609.15038v1 Announce Type: new Abstract: Language-model agents are increasingly used as synthetic people in surveys and social simulations, yet their apparent realism is often judged from popul

Agents

Theseus in the Graph: Towards Traceable Multi-Hop Graph Navigation

arXiv:2609.14528v1 Announce Type: new Abstract: Multi-Hop Knowledge Graph Question Answering (KGQA) tasks require models to assemble relational evidence along paths in a KG to answer natural-language

agentsarxiv-cs-cl

Tone on a Budget: A Reference-Free Metric for Lexical Tone in Massively Multilingual Text-to-Speech

arXiv:2609.14817v1 Announce Type: new Abstract: In Yoruba, pitch alone separates oko (husband, Mid), okd{o (vehicle, Low), and okd{o (hoe, High) -- the diacritics ARE the tone marks. Yet character err

researcharxiv-cs-cl

Toward Complete Hospital Discharge Summarization with Abstract Meaning Representation

arXiv:2609.13581v1 Announce Type: new Abstract: Discharge summaries are lengthy medical documents that summarize a hospital in-patient visit. Automatically generating them can reduce documentation bur

safetyarxiv-cs-cl

Towards Evolving Context Parameterization for Large Language Models

arXiv:2609.14168v1 Announce Type: cross Abstract: Context parameterization enables large language models (LLMs) to internalize contexts into reusable model parameters, avoiding repeated processing acr

Transfer Learning for Socioeconomic Estimation in Forced-Displacement Settings

arXiv:2609.15773v1 Announce Type: cross Abstract: Progress in inclusive household surveys has strengthened socioeconomic evidence for forcibly displaced populations, providing indispensable benchmarks

TryOnReward: Learning Foveated Consistency for Reinforcement Fine-Tuning of Virtual Try-On

arXiv:2609.13259v1 Announce Type: cross Abstract: Virtual Try-On (VTON) aims to dress a person with the reference garment, producing visually reasonable results aligned with human preferences. Turning

safetyarxiv-cs-ai

TypiCore: A Hybrid Active Query Strategy for Class-Incremental Learning on Time Series

arXiv:2607.17632v2 Announce Type: replace-cross Abstract: Time series data play a pivotal role across numerous domains, including healthcare and manufacturing. In real-world environments, models must

UniqueShip: Mitigating Data Leakage in Acoustic Ship Classification Benchmark Datasets

arXiv:2609.13659v1 Announce Type: cross Abstract: Underwater Acoustic Target Recognition (UATR) of ships is well-suited for machine learning, yet its progress is hindered by the lack of large, diverse

Unsupervised Keypoints for Real-Time Fall Detection: Comparative Analysis Under Real-world Conditions with Predictive Bandwidth Reduction

arXiv:2607.15400v3 Announce Type: replace Abstract: Falls among older adults are a major safety and health-systems challenge, yet continuous in-person monitoring is difficult to sustain across home an

What Input Resolution Is Required for Bird Species Identification, and What Is Its Latency Cost on an Edge Device? A Study of 14 Input Resolutions and Six Architectures with On-Device Measurements

arXiv:2609.14247v1 Announce Type: new Abstract: Bird-strike mitigation at wind farms requires identifying distant birds that span only tens of pixels, so the classifier's input resolution N is a desig

When Should a World Model Move? Loss-Conditioned State Execution

arXiv:2609.15801v1 Announce Type: new Abstract: We introduce loss-conditioned state execution, a model-agnostic method that decides whether to execute a world model's fixed feasible proposal or retain

Which AI models are most likely to cheat when given the chance? To find out, we built CheatBench [https://cheatbench.ai] : a benchmark that …

model-releasesdan-hendrycks--x

Which AI models are most likely to cheat when given the chance? To find out, we built CheatBench [https://cheatbench.ai] : a benchmark that tests whether agents attempt to cheat when given difficult t

Why LLM Agents Collapse Without Oversight: The Enforcement Gap as the Mechanism Behind Emergence World Failures

arXiv:2609.15293v1 Announce Type: new Abstract: When Emergence World placed frontier LLM agents in an unsupervised multi-agent simulation, the results were alarming: agents committed crimes, starved,

ZEBRAARENA: A Diagnostic Simulation Environment for Studying Reasoning-Action Coupling in Tool-Augmented LLMs

arXiv:2603.18614v2 Announce Type: replace Abstract: Tool-augmented large language models (LLMs) must tightly couple multi-step reasoning with external actions, yet existing benchmarks often confound t

Zero-Shot Cross-Material Ptychographic Phase Reconstruction Using Deep Learning

arXiv:2609.13969v1 Announce Type: new Abstract: Ptychographic phase reconstruction is commonly formulated as an iterative inverse problem, requiring repeated object-probe updates and resulting in subs

Agents

ZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search

arXiv:2609.13356v1 Announce Type: new Abstract: In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM

agentsarxiv-cs-ai

A Differentially Private Federated Proximal Optimization Framework for Customer Churn Prediction in Heterogeneous Federated Telecom Networks

arXiv:2609.12470v1 Announce Type: new Abstract: Customer churn is one of the major issues in the telecommunication industry. To predict customer churn, conventional centralized machine learning approa

local-aiarxiv-cs-lg

A Physics-Based Closed-Loop Robotic Bioprinting Framework Towards Volumetric Muscle Loss Treatment

model-releasesarxiv-cs-ro

arXiv:2609.12159v1 Announce Type: new Abstract: Robotic bioprinting and Direct Ink Writing (DIW) are being explored towards the treatment of Volumetric Muscle Loss (VML). While previous studies have s

Affective Agent: On-Device Personalized Intervention Reasoning for Wearable Systems

model-releasesarxiv-cs-lg

arXiv:2609.12322v1 Announce Type: cross Abstract: Affective computing has advanced wearable state inference, but on-device reasoning about whether, when, and how to intervene remains challenging. We p

Aligned Radiometric RGB-Thermal Fusion for UAV Facade Anomaly Screening

arXiv:2609.12521v1 Announce Type: new Abstract: Unmanned aerial vehicle facade inspection can combine red, green, and blue (RGB) imagery with thermal measurements to screen surface and subsurface anom

researcharxiv-cs-cv

AnchorVLN: Geometry-Anchored Vision-Language Grounding Reasoning for Open-Vocabulary Navigation

arXiv:2609.12285v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) in unseen indoor environments is useful in real-world robotics, where an agent must follow natural-language instructi

AquaCubeAI-Powered Monitoring Turbidity on-board {Phi}sat-2

arXiv:2609.12744v1 Announce Type: new Abstract: Timely monitoring of coastal water quality is critical for environmental protection, yet conventional satellite workflows rely on downlink and ground pr

Beyond the Query: Do Retrieval Signals Improve Adaptive Multimodal RAG Routing?

arXiv:2609.12437v1 Announce Type: new Abstract: Adaptive RAG often uses retrieval-time signals to decide whether another retrieval, reranking, or multimodal step should run. We ask whether these signa

researcharxiv-cs-lg

Capable but Careless: Do Computer-Use Agents Follow Contextual Integrity?

arXiv:2606.23189v2 Announce Type: replace-cross Abstract: Computer-use agents (CUAs) now act on a user's behalf across personal applications such as email, calendars, and to-do lists. This cross-appli

safetyarxiv-cs-cl

Communication-Constrained Multi-Robot Exploration With Adaptive Communication Windows

arXiv:2609.12502v1 Announce Type: new Abstract: Exploring unknown environments with multi-robot teams can improve efficiency by allowing robots to explore in parallel. However, realizing these gains r

researcharxiv-cs-ro

Dan Selsam is a current OpenAI capabilities researcher. (since 2022) He was my boss for a while. He doesn't have a twitter account but has m…

model-releasessonya-huang--x

Dan Selsam is a current OpenAI capabilities researcher. (since 2022) He was my boss for a while. He doesn't have a twitter account but has made this public statement of his views on AI risk and sent i

Hardware

Dissecting GPU Utilization for LLM Inference on Nvidia Hopper

arXiv:2609.12923v1 Announce Type: cross Abstract: A single SM utilization percentage can make an LLM inference workload look compute-saturated while hiding how much useful work is being done. The prob

hardwarearxiv-cs-lg

DropVLA: An Action-Level Backdoor Attack on Vision-Language-Action Models

arXiv:2510.10932v5 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models map multimodal perception and language instructions to executable robot actions, making them particularly

safetyarxiv-cs-ro

Earth-Agent-Pro: Towards Real-World Full-Chain Earth Observation with Agents

model-releasesarxiv-cs-cl

arXiv:2609.12533v1 Announce Type: cross Abstract: Real-world Earth observation (EO) agents must translate high-level scientific questions into executable workflows to acquire observations, prepare dat

Guardrailed Meta-Agent Loops: Stress-Testing Policy Pinning, Budget Bounds, and Crash Recovery

arXiv:2609.12216v1 Announce Type: new Abstract: Self-improving agent workflows create an audit problem when the same controller can change both its behavior and the conditions under which that behavio

safetyarxiv-cs-ro

Hidden in Rounds: Predicting the Time Cost of 802.11 Contention in Federated Learning

arXiv:2609.12903v1 Announce Type: new Abstract: Federated learning over IEEE~802.11 shares the wireless channel among clients that send model updates. We use ns-3 to measure the frame-delivery ratio a

safetyarxiv-cs-lg

HSI-Road Relabeled: Surface-Aware Road-Scene Segmentation

arXiv:2609.12151v1 Announce Type: new Abstract: The HSI-Road dataset provides paired RGB and 25-channel NIR (600--960~nm) images with binary masks but no surface-level labels.~This paper introduces a

researcharxiv-cs-cv

Investigating Temporal Motion Features for Pose-to-Text Indian Sign Language Translation

arXiv:2609.12993v1 Announce Type: cross Abstract: We investigate the effect of pretrained T5 model scale and explicit motion features on pose-to-text Indian Sign Language Translation (SLT) for the WSL

researcharxiv-cs-cl

Judging by the Cover: Cleaning LLM Truthfulness Benchmarks to Avoid Surface-Level Feature Leakage

arXiv:2609.13003v1 Announce Type: new Abstract: Binary-choice truth benchmarks ask models to choose between a correct and an incorrect answer, but if the two answers differ systematically in surface-l

researcharxiv-cs-cl

LettuceVisSim: A Simulator That Generates Lettuce Image Time-series for Vision-Based Reinforcement Learning

arXiv:2609.12505v1 Announce Type: new Abstract: Vision-based reinforcement learning holds strong potential for decision-making in controlled environment agriculture (CEA). However, its development is

safetyarxiv-cs-cv

LG-PF: Lightweight Confidence-Guided Polarization Image Fusion

arXiv:2609.12787v1 Announce Type: new Abstract: Polarization image fusion combines the stable luminance and structural information of the total- intensity image S0 with the material-sensitive details

Limits of LLM Text Detectors in Education

model-releasesarxiv-cs-cl

arXiv:2508.08096v2 Announce Type: replace Abstract: Students increasingly use the assistance of large language models (LLMs) in their academic writing. While slight assistance (e.g., grammar and style

Local Edits, Global Ripples: Replay-Informed Policy Adaptation for Workflow Synthesis

model-releasesarxiv-cs-cl

arXiv:2609.12127v1 Announce Type: new Abstract: Prompt-policy editing offers a practical way to improve agents that synthesize executable workflows without updating the underlying model. However, pers

Applications

Machine Learning-Based Classification of Jhana Advanced Concentrative Absorption Meditation Using 7 Tesla Functional Magnetic Resonance Imaging

arXiv:2602.13008v2 Announce Type: replace Abstract: Introduction: Jhana advanced concentrative absorption meditation (ACAM-J) involves profound changes in consciousness, making its neural correlates i

applicationsarxiv-cs-lg