Search: “evaluation”

Quantifying and Mitigating Socially Desirable Responding in LLMs: A Desirability-Matched Graded Forced-Choice Psychometric Study

model-releasesarxiv-cs-cl

arXiv:2602.17262v2 Announce Type: replace Abstract: Human self-report questionnaires are increasingly used in NLP to benchmark and audit large language models (LLMs), from persona consistency to safet

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Safety

Reinforcement Learning for Testing Interdependent Requirements in Autonomous Vehicles: An Empirical Study

DGX agent

arXiv:2502.15792v2 Announce Type: replace-cross Abstract: Autonomous vehicles (AVs) make driving decisions without humans, making dependability assurance critical. Scenario-based testing is widely use

safetyarxiv-cs-lg

29 Apr 2026

RISE: Self-Improving Robot Policy with Compositional World Model

arXiv:2602.11075v2 Announce Type: replace Abstract: Despite the sustained scaling on model capacity and data acquisition, Vision-Language-Action (VLA) models remain brittle in contact-rich and dynamic

safetyarxiv-cs-ro

ShapeY: A Principled Framework for Measuring Shape Recognition Capacity via Nearest-Neighbor Matching

arXiv:2604.25065v1 Announce Type: new Abstract: Object recognition (OR) in humans relies heavily on shape cues and the ability to recognize objects across varying 3D viewpoints. Unlike humans, deep ne

researcharxiv-cs-cv

Tutorials

The Surprising Effectiveness of Canonical Knowledge Distillation for Semantic Segmentation

arXiv:2604.25530v1 Announce Type: new Abstract: Recent knowledge distillation (KD) methods for semantic segmentation introduce increasingly complex hand-crafted objectives, yet are typically evaluated

tutorialsarxiv-cs-cv

Unrequited Emotions: Investigating the Gaps in Motivation and Practice in Speech Emotion Recognition Research

arXiv:2604.25776v1 Announce Type: new Abstract: Critical analyses of emotion recognition technology have raised ethical concerns around task validity and potential downstream impacts, urging researche

safetyarxiv-cs-cl

An Automatic Ground Collision Avoidance System with Reinforcement Learning

arXiv:2604.24403v1 Announce Type: new Abstract: This article evaluates an artificial intelligence (AI)-based Automatic Ground Collision Avoidance System (AGCAS) designed for advanced jet trainers to e

safetyarxiv-cs-lg

AutoGUI-v2: A Comprehensive Multi-Modal GUI Functionality Understanding Benchmark

model-releasesarxiv-cs-cv

arXiv:2604.24441v1 Announce Type: new Abstract: Autonomous agents capable of navigating Graphical User Interfaces (GUIs) hold the potential to revolutionize digital productivity. However, achieving tr

Bellman Residual Minimization for Control: Geometry, Stationarity, and Convergence

arXiv:2601.18840v3 Announce Type: replace Abstract: Markov decision problems are most commonly solved via dynamic programming. Another approach is Bellman residual minimization, which directly minimiz

safetyarxiv-cs-lg

Applications

Bridging the Domain Divide: Supervised vs. Zero-Shot Clinical Section Segmentation from MIMIC-III to Obstetrics

arXiv:2602.17513v2 Announce Type: replace Abstract: Clinical free-text notes contain vital patient information. They are structured into labelled sections; recognizing these sections has been shown to

applicationsarxiv-cs-cl

ClawMark: A Living-World Benchmark for Multi-Turn, Multi-Day, Multimodal Coworker Agents

model-releasesarxiv-cs-cv

arXiv:2604.23781v1 Announce Type: new Abstract: Language-model agents are increasingly used as persistent coworkers that assist users across multiple working days. During such workflows, the surroundi

Continual Calibration: Coverage Can Collapse Before Accuracy in Lifelong LLM Fine-Tuning

arXiv:2604.23987v1 Announce Type: new Abstract: Continual learning for large language models is typically evaluated through accuracy retention under sequential fine-tuning. We argue that this perspect

Culture-Aware Machine Translation in Large Language Models: Benchmarking and Investigation

arXiv:2604.24361v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance in general machine translation, yet their ability in culture-aware scenarios remains poorl

researcharxiv-cs-cl

Do Synthetic Trajectories Reflect Real Reward Hacking? A Systematic Study on Monitoring In-the-Wild Hacking in Code Generation

arXiv:2604.23488v1 Announce Type: new Abstract: Reward hacking in code generation, where models exploit evaluation loopholes to obtain full reward without correctly solving the tasks, poses a critical

safetyarxiv-cs-lg

Does Machine Unlearning Preserve Clinical Safety? A Risk Analysis for Medical Image Classification

arXiv:2604.23854v1 Announce Type: new Abstract: The application of Deep Learning in medical diagnosis must balance patient safety with compliance with data protection regulations. Machine Unlearning e

Domain-Adapted Fine-Tuning of ECG Foundation Models for Multi-Label Structural Heart Disease Screening

model-releasesarxiv-cs-lg

arXiv:2604.23385v1 Announce Type: new Abstract: Transthoracic echocardiography is the reference standard for confirming structural heart disease (SHD), but first-line screening is limited by cost, wor

Energy-Arena: A Dynamic Benchmark for Operational Energy Forecasting

model-releasesarxiv-cs-lg

arXiv:2604.24705v1 Announce Type: cross Abstract: Energy forecasting research faces a persistent comparability gap that makes it difficult to measure consistent progress over time. Reported accuracy g

Agents

Escher-Loop: Mutual Evolution by Closed-Loop Self-Referential Optimization

arXiv:2604.23472v1 Announce Type: new Abstract: While recent autonomous agents demonstrate impressive capabilities, they predominantly rely on manually scripted workflows and handcrafted heuristics, i

agentsarxiv-cs-ai

Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach

model-releasesarxiv-cs-lg

arXiv:2601.18399v2 Announce Type: replace Abstract: Separating liquid-liquid dispersions in gravity settlers is critical in chemical, pharmaceutical, and recycling processes. The dense-packed zone hei

Exploring Audio Hallucination in Egocentric Video Understanding

arXiv:2604.23860v1 Announce Type: cross Abstract: Egocentric videos provide a distinctive setting in which sound serves as crucial cues to understand user activities and surroundings, particularly whe

researcharxiv-cs-ai

Exploring the Impact of Dataset Statistical Effect Size on Model Performance and Data Sample Size Sufficiency

arXiv:2501.02673v4 Announce Type: replace Abstract: Having a sufficient quantity of quality data is a critical enabler of training effective machine learning models. Being able to effectively determin

Exploring the Secondary Risks of Large Language Models

arXiv:2506.12382v5 Announce Type: replace-cross Abstract: Ensuring the safety and alignment of Large Language Models is a significant challenge with their growing integration into critical application

Governing What You Cannot Observe: Adaptive Runtime Governance for Autonomous AI Agents

arXiv:2604.24686v1 Announce Type: new Abstract: Autonomous AI agents can remain fully authorized and still become unsafe as behavior drifts, adversaries adapt, and decision patterns shift without any

Graph Memory Transformer (GMT)

arXiv:2604.23862v1 Announce Type: cross Abstract: We investigate whether the Feed-Forward Network (FFN) sublayer in a decoder-only transformer can be replaced by an explicit learned memory graph while

GSAR: Typed Grounding for Hallucination Detection and Recovery in Multi-Agent LLMs

arXiv:2604.23366v1 Announce Type: new Abstract: Autonomous multi-agent LLM systems are increasingly deployed to investigate operational incidents and produce structured diagnostic reports. Their trust

IntentVLM: Open-Vocabulary Intention Recognition through Forward-Inverse Modeling with Video-Language Models

arXiv:2604.24002v1 Announce Type: cross Abstract: Improving the effectiveness of human-robot interaction requires social robots to accurately infer human goals through robust intention understanding.

researcharxiv-cs-ai

Knowledge Lever Risk Management for Software Engineering: A Stochastic Framework for Mitigating Knowledge Loss

arXiv:2604.23257v1 Announce Type: cross Abstract: Software engineering (SE) organizations operate in a knowledge-intensive domain where critical assets -- architectural expertise, design rationale, an

Tutorials

Learn&Drop: Fast Learning of CNNs based on Layer Dropping

arXiv:2604.23403v1 Announce Type: cross Abstract: This paper proposes a new method to improve the training efficiency of deep convolutional neural networks. During training, the method evaluates score

tutorialsarxiv-cs-ai

MetaGAI: A Large-Scale and High-Quality Benchmark for Generative AI Model and Data Card Generation

arXiv:2604.23539v1 Announce Type: new Abstract: The rapid proliferation of Generative AI necessitates rigorous documentation standards for transparency and governance. However, manual creation of Mode

On Emergent Social World Models -- Evidence for Functional Integration of Theory of Mind and Pragmatic Reasoning in Language Models

arXiv:2602.10298v2 Announce Type: replace Abstract: This paper investigates whether LMs recruit shared computational mechanisms for general Theory of Mind (ToM) and language-specific pragmatic reasoni

researcharxiv-cs-cl

OS-SPEAR: A Toolkit for the Safety, Performance,Efficiency, and Robustness Analysis of OS Agents

arXiv:2604.24348v1 Announce Type: new Abstract: The evolution of Multimodal Large Language Models (MLLMs) has shifted the focus from text generation to active behavioral execution, particularly via OS

safetyarxiv-cs-cl

Perfecting Aircraft Maneuvers with Reinforcement Learning

arXiv:2604.24338v1 Announce Type: new Abstract: This paper evaluates an advanced jet trainer's utilization of artificial intelligence (AI)-based aircraft aerobatic maneuvers with the intention of deve

Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface

arXiv:2604.24415v1 Announce Type: cross Abstract: Quantitative analysis of the kinematic chain in sports motion is essential for performance evaluation and injury prevention. Conventional methods such

researcharxiv-cs-cv

PhysCodeBench: Benchmarking Physics-Aware Symbolic Simulation of 3D Scenes via Self-Corrective Multi-Agent Refinement

arXiv:2604.23580v1 Announce Type: cross Abstract: Physics-aware symbolic simulation of 3D scenes is critical for robotics, embodied AI, and scientific computing, requiring models to understand natural

Applications

Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data

arXiv:2503.05587v3 Announce Type: replace-cross Abstract: Robustness has become a critical attribute for the deployment of RAG systems in real-world applications. Existing research focuses on robustne

applicationsarxiv-cs-ai

RealFin: How Well Do LLMs Reason About Finance When Users Leave Things Unsaid?

arXiv:2602.07096v2 Announce Type: replace-cross Abstract: Reliable financial reasoning requires knowing not only how to answer, but also when an answer cannot be justified. In real financial practice,

Risk-Aware Robust Learning: Reducing Clinical Risk under Label Noise in Medical Image Classification

arXiv:2604.23875v1 Announce Type: cross Abstract: Noisy labels are a pervasive challenge in medical image classification, where annotation errors arise from inter-observer variability and diagnostic a

Scoring, Reasoning, and Selecting the Best! Ensembling Large Language Models via a Peer-Review Process

arXiv:2512.23213v3 Announce Type: replace-cross Abstract: We propose LLM-PeerReview, an unsupervised LLM Ensemble method that selects the most ideal response from multiple LLM-generated candidates for

researcharxiv-cs-ai

Sphere-Depth: A Benchmark for Depth Estimation Methods with Varying Spherical Camera Orientations

arXiv:2604.23432v1 Announce Type: cross Abstract: Reliable depth estimation from spherical images is crucial for 360{eg} vision in robotic navigation and immersive scene understanding. However, the on

Stochastic simultaneous optimistic optimization

arXiv:2604.24537v1 Announce Type: new Abstract: We study the problem of global maximization of a function f given a finite number of evaluations perturbed by noise. We consider a very weak assumption

TextGround4M: A Prompt-Aligned Dataset for Layout-Aware Text Rendering

model-releasesarxiv-cs-cv

arXiv:2604.24459v1 Announce Type: new Abstract: Despite recent advances in text-to-image generation, models still struggle to accurately render prompt-specified text with correct spatial layout -- esp

The Consensus Trap: Dissecting Subjectivity and the 'Ground Truth' Illusion in Data Annotation

arXiv:2602.11318v3 Announce Type: replace Abstract: In machine learning, 'ground truth' refers to the assumed correct labels used to train and evaluate models. However, the foundational 'ground truth'

Translate or Simplify First: An Analysis of Cross-lingual Text Simplification in English and French

arXiv:2604.23844v1 Announce Type: new Abstract: Cross-Lingual Text Simplification (CLTS) aims to make content more accessible across languages by simultaneously addressing both linguistic complexity a

researcharxiv-cs-cl

Z^2-Sampling: Zero-Cost Zigzag Trajectories for Semantic Alignment in Diffusion Models

arXiv:2604.23536v1 Announce Type: new Abstract: Diffusion models have achieved unprecedented success in text-aligned generation, largely driven by Classifier-Free Guidance (CFG). However, standard CFG

safetyarxiv-cs-cv

Adversarial Malware Generation in Linux ELF Binaries via Semantic-Preserving Transformations

arXiv:2604.22639v1 Announce Type: cross Abstract: Malware development and detection have undergone significant changes in recent years as modern concepts, such as machine learning, have been used for

Local Ai

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond

arXiv:2604.22748v1 Announce Type: new Abstract: As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment dynamics becomes a centra

local-aiarxiv-cs-ai

AgentSearchBench: A Benchmark for AI Agent Search in the Wild

arXiv:2604.22436v1 Announce Type: new Abstract: The rapid growth of AI agent ecosystems is transforming how complex tasks are delegated and executed, creating a new challenge of identifying suitable a

Hardware

Beyond Land Surface Temperature: Explainable Spatial Machine Learning Reveals Urban Morphology Effects on Human-Centric Heat Stress

arXiv:2604.22433v1 Announce Type: new Abstract: Heat exposure connects the built environment and public health, directly shaping the livability and sustainability of urban areas. Understanding the spa

hardwarearxiv-cs-lg