Search: “evaluation”

APGEM: Adaptive Policy-Guided Error Mitigation for Quantum Reinforcement Learning on a Real-World CVRP Case Study

arXiv:2609.18219v1 Announce Type: cross Abstract: Quantum Reinforcement Learning (QRL) represents policies as variational quantum circuits (VQCs), making it attractive for combinatorial optimization s

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Attention Dispersion as a Diagnostic Signal for Hallucination in Large Language Models

DGX agent

arXiv:2609.18320v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently exhibit hallucinations, presenting a major barrier to reliability in complex reasoning tasks. While traditional

safetyarxiv-cs-cl

17 Sept 2026

Audio for Sports Highlight Detection: A Comparative Empirical Study

model-releasesarxiv-cs-cv

arXiv:2609.17923v1 Announce Type: new Abstract: Sports highlight detection aims to identify the most exciting and meaningful moments from long sports videos. While existing methods often emphasize vis

Behavior2Value: Benchmarking and Empowering LLMs for Consumer Value Measurement from E-commerce Behaviors

model-releasesarxiv-cs-cl

arXiv:2609.18203v1 Announce Type: new Abstract: Human values are deep motivational orientations that shape human behaviors. In e-commerce, they reveal the stable drivers behind users' purchase decisio

Benchmarking Tabular Foundation Models as Surrogates in Expensive Evolutionary Optimization

arXiv:2609.18130v1 Announce Type: cross Abstract: Surrogate-assisted evolutionary algorithms (SAEAs) are effective methods for solving expensive optimization problems (EOPs), where surrogate models re

Beyond Accuracy: How Procedural Traces Shift the Decision Criterion of LLM Overseers

arXiv:2609.18204v1 Announce Type: cross Abstract: Organizations increasingly use oversight loops where one large language model (LLM) audits another's outputs alongside procedural traces of claimed st

researcharxiv-cs-ai

Beyond Direct Sensing: Harnessing Indirect Observations from Third-Party Sensors in Vehicle Tracking

arXiv:2609.18173v1 Announce Type: cross Abstract: Vehicle tracking is fundamental to applications ranging from urban mobility and public safety to security and defense. Conventional tracking relies on

safetyarxiv-cs-lg

Beyond frequency measures: Can contextual embeddings capture meaning change in scientific texts?

arXiv:2609.18804v1 Announce Type: new Abstract: Identifying technological trends is a core scientometric task, yet traditional frequency-based approaches struggle to capture substantial meaning shifts

researcharxiv-cs-cl

CALIPER: Metric-Grounded Model-Free Recognition of Visually Similar Industrial Parts

arXiv:2609.17820v1 Announce Type: new Abstract: Fine-grained recognition of visually similar industrial parts is challenging when classes differ primarily in physical dimensions. Normalizing detected

researcharxiv-cs-cv

CALOS: Control-Affine Lyapunov On-manifold Safety Layer for Safe Deep Reinforcement Learning for Quadrotors

arXiv:2609.17758v1 Announce Type: cross Abstract: Deep Reinforcement Learning has demonstrated remarkable capability in quadrotor control, yet learned policies offer no guarantee of respecting safety

Can VLMs Reliably Assess Sidewalk Accessibility Attributes from Pedestrian-Level Imagery?

arXiv:2609.17882v1 Announce Type: cross Abstract: An important component of urban accessibility, particularly for wheelchair users and people with reduced mobility, is sidewalk compliance with measura

CANTABILE: Learning Expressive Dynamics for Robotic Piano Performance

model-releasesarxiv-cs-ro

arXiv:2609.18213v1 Announce Type: new Abstract: Robotic piano playing has emerged as a standard benchmark for dexterous bimanual manipulation, yet progress on it has been measured almost entirely by n

CARA: Collision-Aware Resolution Adaptation for Multiresolution Hash Encoding Based Image Fitting

model-releasesarxiv-cs-cv

arXiv:2609.18554v1 Announce Type: new Abstract: Multiresolution hash encodings have recently enabled fast and high-fidelity implicit neural representations by storing multi-scale features in fixed-siz

CaSCo: Cascade-Aware Soft-Collision Motion Planning

arXiv:2609.18910v1 Announce Type: new Abstract: Conventional motion planning treats collision as a binary constraint, although contact with different objects can have drastically different consequence

researcharxiv-cs-ro

Agents

CERA-MoA: Co-Evolving Routing Mechanisms with Continually Learning LLM Agents

arXiv:2609.18779v1 Announce Type: new Abstract: Current Mixture-of-Agents (MoA) paradigms generally treat query routing and agent fine-tuning as separate processes, limiting their ability to respond t

agentsarxiv-cs-ai

Characterizing Replay Retention Under Dynamics Shift in Model-Based Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2609.18167v1 Announce Type: cross Abstract: Adapting to changes in robot dynamics requires learning from new data without discarding experience that may still be useful. In continual model-based

CoAtNet-DeepMoE: A Convolution-Attention Hybrid with DeepSeek Mixture-of-Experts for Parameter-Efficient Tomato Disease Classification

model-releasesarxiv-cs-cv

arXiv:2609.18038v1 Announce Type: new Abstract: The world population is growing rapidly, and technology is improving in parallel. Meeting the huge demand for food for these 7 billion people not only d

CompArt: Operationalizing Aesthetic Alignment in Text-to-Image Generation via Principles of Art

arXiv:2503.12018v2 Announce Type: replace-cross Abstract: Text-to-Image (T2I) diffusion models have made rapid progress on semantic alignment (generating what is described in the prompt), yet users st

COMPASS-ABS: Reducing Fragmentation in Shared GPU Clusters for Deep Learning Training Workloads

arXiv:2609.18519v1 Announce Type: cross Abstract: With the rapid advancement of deep learning technology, shared GPU clusters receive an increasing number of deep learning training (DLT) jobs. Yet res

safetyarxiv-cs-lg

CompileRover: Revolutionizing Virtual Machine Compiler Optimization with a Tri-Role LLM-Driven Framework

arXiv:2609.19004v1 Announce Type: cross Abstract: Code optimization plays a crucial role in the development of virtual machine compilers, with optimization frameworks significantly enhancing the perfo

researcharxiv-cs-cl

Agents

Composite-Gradient Learning for Shared Control Authority Between Deep Reinforcement Learning and Model Predictive Control

arXiv:2609.17697v1 Announce Type: new Abstract: Integrated deep reinforcement learning (DRL) and model predictive control (MPC) methods are increasingly used to control autonomous systems by combining

agentsarxiv-cs-lg

CoRe-MARL: Cooperative Redistribution Under Unknown Dynamics Using Recurrent Multi-Agent Reinforcement Learning

arXiv:2609.18639v1 Announce Type: cross Abstract: Emergency management assistance programs, such as relief distribution, are essential for delivering necessary supplies to affected communities. Howeve

CSWAM: Better Causal Semantic Representations for Out-of-Distribution Generalization in World Action Models

arXiv:2609.18462v1 Announce Type: cross Abstract: FastWAM-style world action models enable efficient action-only inference, but generalize poorly under visual distribution shifts. Their reconstruction

researcharxiv-cs-ai

Decoupling Vision, Language, and Action for Efficient Multi-Task Robot Policies

arXiv:2609.18374v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models attach an action module to a Vision-Language Model (VLM) with billions of parameters and pay for that backbone at ev

Derivative-Free Structured Updates for Muon

arXiv:2609.17759v1 Announce Type: cross Abstract: Muon updates matrix-valued neural-network parameters by orthogonalizing a gradient-based momentum matrix. Its reliance on derivatives limits its use w

Designing Agentic AI Workflow Portfolios under Imperfect Selection and Compute Cost

arXiv:2609.18126v1 Announce Type: new Abstract: Agentic AI systems often approach the same task through multiple workflows that differ in reasoning strategy, verification structure, and compute cost.

Tutorials

DiT-Garment: Garment Dynamics with Diffusion Transformers

arXiv:2609.18510v1 Announce Type: new Abstract: We present DiT-Garment to model dynamic 3D clothing over human body models in arbitrary motion. Unlike existing methods, DiT-Garment can animate garment

tutorialsarxiv-cs-cv

Divide and Conquer: A Hybrid Strategy Defeats Multimodal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2412.16555v4 Announce Type: replace Abstract: Large language models (LLMs) are widely applied in various fields of society due to their powerful reasoning, understanding, and generation capabili

Tutorials

Dreaming the Sound of Contact: Leveraging Video and Audio Generation for Zero-Shot Force-Aware Manipulation and Data Generation

arXiv:2609.19137v1 Announce Type: cross Abstract: Recent advances in video generation allow robots to learn manipulation trajectories from generated videos. However, these approaches produce purely ki

tutorialsarxiv-cs-ai

DRT&R: Direct Radar Teach & Repeat

arXiv:2609.17766v1 Announce Type: new Abstract: Radar-based navigation is appealing for its robustness to adverse conditions involving airborne particles, such as precipitation, dust, fog, and smoke,

researcharxiv-cs-ro

DynoFluxBench: Benchmarking Kinodynamic Space-Time Planners in Dynamic Environments

model-releasesarxiv-cs-ro

arXiv:2609.18549v1 Announce Type: new Abstract: Robots that leave structured, static environments must plan motions that are kinodynamically feasible and safe among moving obstacles. However, there ar

EDCT-Bench: Uncovering Faithfulness Gaps in VLMs via Explanation-Driven Counterfactual Testing

model-releasesarxiv-cs-ai

arXiv:2609.17953v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) can produce Natural Language Explanations (NLEs) that sound plausible yet remain inconsistent with the visual evidence t

EmboAlign: Aligning Video Generation with Compositional Constraints for Zero-Shot Manipulation

arXiv:2603.05757v2 Announce Type: replace Abstract: Video generative models (VGMs) pretrained on large-scale internet data can produce temporally coherent rollout videos that capture rich object dynam

End2Race: An End-to-End Learning Framework for Multi-Vehicle Autonomous Racing

arXiv:2509.16894v2 Announce Type: replace Abstract: Autonomous racing serves as a compelling testbed for advancing autonomous vehicle systems. The 1/10-scale F1Tenth platform is widely adopted for edu

Energy-Regularized Imitation Learning for Force- and Work-Aware Robotic Manipulation

arXiv:2609.18164v1 Announce Type: new Abstract: This paper studies energy-aware manipulation as a physically grounded learning problem. We define a joint-space mechanical-work proxy from joint torque

Applications

EPOFusion: Exposure aware Progressive Optimization Method for Infrared and Visible Image Fusion

arXiv:2603.16130v5 Announce Type: replace Abstract: Overexposure caused by strong daylight and oncoming headlights frequently overwhelms visible sensors, resulting in critical information loss in visu

applicationsarxiv-cs-cv

Every Fixed Metric Has a Blind Spot: A Learned Atmospheric Critic for Scoring Forecast Realism

arXiv:2609.18381v1 Announce Type: new Abstract: Despite their high accuracy on point-wise metrics, machine learning weather forecasting models can exhibit different failure modes such as blurring, per

EviGen: Predictive Evidence Scaffolding for Verifiable Clinical Rationale Generation

arXiv:2609.18852v1 Announce Type: new Abstract: Longitudinal electronic health records (EHRs) capture years of patient history across notes, codes, labs, and procedures, and contain evidence needed to

researcharxiv-cs-cl

EvolveTrade: Experience-Driven Policy Refinement for Self-Evolving LLM Trading Agents

arXiv:2609.17632v1 Announce Type: new Abstract: Large language model (LLM) trading agents can combine market data, news, and executable analysis, but their behavior is often controlled by static hand-

Fourier Analysis of Parametrized Interactive Quantum Classifiers

model-releasesarxiv-cs-lg

arXiv:2609.17991v1 Announce Type: cross Abstract: Interactive Quantum Classifiers (IQCs) constitute a family of quantum machine learning models inspired by open quantum systems, in which the interacti

From a River in Gilead to the Inference Distributions of Large Language Models: Covert Dialect Bias and Linguistic Profiling at Scale

arXiv:2609.18068v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains such as housing screening. While alignment techniques mitigate explicit

FuseFi: Combining Irregularly Sampled CSI from Diverse Communication Packets and Frequency Bands for Wi-Fi Sensing

model-releasesarxiv-cs-lg

arXiv:2512.22143v2 Announce Type: replace-cross Abstract: Existing Wi-Fi sensing systems rely on injecting high-rate probing packets to extract channel state information (CSI), leading to communicatio

G-Mamba: Sparse Graph-Guided Mamba for Audio-Visual Speech Enhancement

arXiv:2609.18009v1 Announce Type: cross Abstract: Lightweight audio-visual speech enhancement (AVSE) models face a critical trade-off between computational efficiency and cross-modal alignment accurac

safetyarxiv-cs-cl

GraphPoint: Semantic Entity Graphs and Point Trajectories for Compositional Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.18358v1 Announce Type: new Abstract: Robot manipulation policies often struggle to generalize beyond their demonstrations, even when new instructions involve familiar objects and behaviors.

Agents

HINT-Plan: Human Intention-Aware Robot Task Planning in Context-Rich Environments using Vision Language Models

arXiv:2609.17771v1 Announce Type: cross Abstract: Approaches to incorporating human awareness into mobile robot decision-making mainly focus on collision avoidance in low-level motion planning, often

agentsarxiv-cs-ai

How AI Assistants Respond to Repeated Abuse

model-releasesarxiv-cs-cl

arXiv:2609.17547v1 Announce Type: new Abstract: AI assistants are expected to remain useful during difficult interactions, but little is known about how repeated verbal abuse changes their engagement

How Dario Amodei's essays on AI safety and ethics help explain some AI fears; his regulatory stance evolved from wariness in January to embracing safety reviews (David Streitfeld/New York Times)

David Streitfeld / New York Times: How Dario Amodei's essays on AI safety and ethics help explain some AI fears; his regulatory stance evolved from wariness in January to embracing safety reviews — Da

safetytechmeme

Applications

Human Resilience in the AI Era -- What Machines Can't Replace

arXiv:2510.25218v2 Announce Type: replace-cross Abstract: AI is changing work and decision making faster than many institutions can adapt their operating practices. We argue that this adaptation gap m

applicationsarxiv-cs-ai