Search: “evaluation”

From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments

arXiv:2603.23964v2 Announce Type: replace Abstract: The remarkable progress of reinforcement learning (RL) is intrinsically tied to the environments used to train and evaluate artificial agents. Movin

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From Theory to Protocol: Executable Frameworks for Creative Emergence and Strategic Foresight

DGX agent

arXiv:2604.09597v1 Announce Type: cross Abstract: Creativity and strategic foresight have been extensively studied through descriptive theories -- Koestler's bisociation (1964), de Bono's lateral thin

model-releasesarxiv-cs-ai

14 Apr 2026

From Translation to Superset: Benchmark-Driven Evolution of a Production AI Agent from Rust to Python

arXiv:2604.11518v1 Announce Type: cross Abstract: Cross-language migration of large software systems is a persistent engineering challenge, particularly when the source codebase evolves rapidly. We pr

Agents

From Understanding to Creation: A Prerequisite-Free AI Literacy Course with Technical Depth Across Majors

arXiv:2604.09634v1 Announce Type: cross Abstract: Most AI literacy courses for non-technical undergraduates emphasize conceptual breadth over technical depth. This paper describes UNIV 182, a prerequi

agentsarxiv-cs-ai

Agents

GameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents

arXiv:2603.24329v2 Announce Type: replace-cross Abstract: Multimodal LLMs are increasingly deployed as perceptual backbones for autonomous agents in 3D environments, from robotics to virtual worlds. T

agentsarxiv-cs-ai

Generative UI: LLMs are Effective UI Generators

arXiv:2604.09577v1 Announce Type: cross Abstract: AI models excel at creating content, but typically render it with static, predefined interfaces. Specifically, the output of LLMs is often a markdown

GIANTS: Generative Insight Anticipation from Scientific Literature

arXiv:2604.09793v1 Announce Type: cross Abstract: Scientific breakthroughs often emerge from synthesizing prior ideas into novel contributions. While language models (LMs) show promise in scientific d

How Many Tries Does It Take? Iterative Self-Repair in LLM Code Generation Across Model Scales and Benchmarks

arXiv:2604.10508v1 Announce Type: cross Abstract: Large language models frequently fail to produce correct code on their first attempt, yet most benchmarks evaluate them in a single-shot setting. We i

Intelligent bear deterrence system based on computer vision: Reducing human bear conflicts in remote areas

arXiv:2503.23178v2 Announce Type: replace Abstract: Conflicts between humans and bears on the Tibetan Plateau present substantial threats to local communities and hinder wildlife preservation initiati

local-aiarxiv-cs-cv

Intra-finger Variability of Diffusion-based Latent Fingerprint Generation

arXiv:2604.10040v1 Announce Type: new Abstract: The primary goal of this work is to systematically evaluate the intra-finger variability of synthetic fingerprints (particularly latent prints) generate

researcharxiv-cs-cv

Knowing What to Stress: A Discourse-Conditioned Text-to-Speech Benchmark

arXiv:2604.10580v1 Announce Type: new Abstract: Spoken meaning often depends not only on what is said, but also on which word is emphasized. The same sentence can convey correction, contrast, or clari

LLM-based Realistic Safety-Critical Driving Video Generation

arXiv:2507.01264v2 Announce Type: replace-cross Abstract: Designing diverse and safety-critical driving scenarios is essential for evaluating autonomous driving systems. In this paper, we propose a no

LookBench: A Live and Holistic Open Benchmark for Fashion Image Retrieval

arXiv:2601.14706v3 Announce Type: replace Abstract: In this paper, we present LookBench (We use the term 'look' to reflect retrieval that mirrors how people shop -- finding the exact item, a close sub

LVSum: A Benchmark for Timestamp-Aware Long Video Summarization

arXiv:2604.10024v1 Announce Type: cross Abstract: Long video summarization presents significant challenges for current multimodal large language models (MLLMs), particularly in maintaining temporal fi

MLLM-as-a-Judge Exhibits Model Preference Bias

arXiv:2604.11589v1 Announce Type: new Abstract: Automatic evaluation using multimodal large language models (MLLMs), commonly referred to as MLLM-as-a-Judge, has been widely used to measure model perf

MonoEM-GS: Monocular Expectation-Maximization Gaussian Splatting SLAM

arXiv:2604.10593v1 Announce Type: new Abstract: Feed-forward geometric foundation models can infer dense point clouds and camera motion directly from RGB streams, providing priors for monocular SLAM.

safetyarxiv-cs-ro

MosaicMRI: A Diverse Dataset and Benchmark for Raw Musculoskeletal MRI

arXiv:2604.11762v1 Announce Type: new Abstract: Deep learning underpins a wide range of applications in MRI, including reconstruction, artifact removal, and segmentation. However, progress has been dr

NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: AI Flash Portrait (Track 3)

arXiv:2604.11230v1 Announce Type: new Abstract: In this paper, we present a comprehensive overview of the NTIRE 2026 3rd Restore Any Image Model (RAIM) challenge, with a specific focus on Track 3: AI

OOM-RL: Out-of-Money Reinforcement Learning Market-Driven Alignment for LLM-Based Multi-Agent Systems

arXiv:2604.11477v1 Announce Type: new Abstract: The alignment of Multi-Agent Systems (MAS) for autonomous software engineering is constrained by evaluator epistemic uncertainty. Current paradigms, suc

Please Make it Sound like Human: Encoder-Decoder vs. Decoder-Only Transformers for AI-to-Human Text Style Transfer

arXiv:2604.11687v1 Announce Type: new Abstract: AI-generated text has become common in academic and professional writing, prompting research into detection methods. Less studied is the reverse: system

Reproduction Beyond Benchmarks: ConstBERT and ColBERT-v2 Across Backends and Query Distributions

arXiv:2604.09982v1 Announce Type: cross Abstract: Reproducibility must validate architectural robustness, not just numerical accuracy. We evaluate ColBERT-v2 and ConstBERT across five dimensions, find

researcharxiv-cs-cl

RiTeK: A Dataset for Large Language Models Complex Reasoning over Textual Knowledge Graphs in Medicine

arXiv:2410.13987v3 Announce Type: replace Abstract: Answering complex real-world questions in the medical domain often requires accurate retrieval from medical Textual Knowledge Graphs (medical TKGs),

RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies

arXiv:2604.09860v1 Announce Type: cross Abstract: The pursuit of general-purpose robotics has yielded impressive foundation models, yet simulation-based benchmarking remains a bottleneck due to rapid

RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo

arXiv:2505.09368v2 Announce Type: replace Abstract: Standard benchmarks for optical flow, scene flow, and stereo vision algorithms generally focus on model accuracy rather than robustness to image cor

Seeing Through the Tool: A Controlled Benchmark for Occlusion Robustness in Foundation Segmentation Models

arXiv:2604.11711v1 Announce Type: new Abstract: Occlusion, where target structures are partially hidden by surgical instruments or overlapping tissues, remains a critical yet underexplored challenge f

Simulating Organized Group Behavior: New Framework, Benchmark, and Analysis

arXiv:2604.09874v1 Announce Type: new Abstract: Simulating how organized groups (e.g., corporations) make decisions (e.g., responding to a competitor's move) is essential for understanding real-world

Template-assisted Contrastive Learning of Task-oriented Dialogue Sentence Embeddings

arXiv:2305.14299v3 Announce Type: replace-cross Abstract: Learning high quality sentence embeddings from dialogues has drawn increasing attentions as it is essential to solve a variety of dialogue-ori

The Blind Spot of Agent Safety: How Benign User Instructions Expose Critical Vulnerabilities in Computer-Use Agents

arXiv:2604.10577v1 Announce Type: cross Abstract: Computer-use agents (CUAs) can now autonomously complete complex tasks in real digital environments, but when misled, they can also be used to automat

The Poisoned Apple Effect: Strategic Manipulation of Mediated Markets via Technology Expansion of AI Agents

arXiv:2601.11496v2 Announce Type: replace-cross Abstract: The integration of AI agents into economic markets fundamentally alters the landscape of strategic interaction. We investigate the economic im

Towards Green Wearable Computing: A Physics-Aware Spiking Neural Network for Energy-Efficient IMU-based Human Activity Recognition

arXiv:2604.10458v1 Announce Type: cross Abstract: Wearable IMU-based Human Activity Recognition (HAR) relies heavily on Deep Neural Networks (DNNs), which are burdened by immense computational and buf

Training Deep Visual Networks Beyond Loss and Accuracy Through a Dynamical Systems Approach

arXiv:2604.09716v1 Announce Type: cross Abstract: Deep visual recognition models are usually trained and evaluated using metrics such as loss and accuracy. While these measures show whether a model is

WearBCI Dataset: Understanding and Benchmarking Real-World Wearable Brain-Computer Interfaces Signals

arXiv:2604.09649v1 Announce Type: cross Abstract: Brain-computer interfaces (BCIs) have opened new platforms for human-computer interaction, medical diagnostics, and neurorehabilitation. Wearable BCI

Who Gets Which Message? Auditing Demographic Bias in LLM-Generated Targeted Text

arXiv:2601.17172v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly capable of generating personalized, persuasive text at scale, raising new questions about bias a

You Only Judge Once: Multi-response Reward Modeling in a Single Forward Pass

arXiv:2604.10966v1 Announce Type: cross Abstract: We present a discriminative multimodal reward model that scores all candidate responses in a single forward pass. Conventional discriminative reward m

Applications

Adaptive Candidate Point Thompson Sampling for High-Dimensional Bayesian Optimization

arXiv:2604.08891v1 Announce Type: new Abstract: In Bayesian optimization, Thompson sampling selects the evaluation point by sampling from the posterior distribution over the objective function maximiz

applicationsarxiv-cs-lg

Applications

AI Driven Soccer Analysis Using Computer Vision

arXiv:2604.08722v1 Announce Type: cross Abstract: Sport analysis is crucial for team performance since it provides actionable data that can inform coaching decisions, improve player performance, and e

applicationsarxiv-cs-ai

Aligned Agents, Biased Swarm: Measuring Bias Amplification in Multi-Agent Systems

arXiv:2604.08963v1 Announce Type: cross Abstract: While Multi-Agent Systems (MAS) are increasingly deployed for complex workflows, their emergent properties-particularly the accumulation of bias-remai

BadSkill: Backdoor Attacks on Agent Skills via Model-in-Skill Poisoning

arXiv:2604.09378v1 Announce Type: cross Abstract: Agent ecosystems increasingly rely on installable skills to extend functionality, and some skills bundle learned model artifacts as part of their exec

Fully Autonomous Z-Score-Based TinyML Anomaly Detection on Resource-Constrained MCUs Using Power Side-Channel Data

arXiv:2604.08581v1 Announce Type: new Abstract: This paper presents a fully autonomous Tiny Machine Learning (TinyML) Z-Score-based anomaly detection system deployed on a low-power microcontroller for

local-aiarxiv-cs-lg

LuMon: A Comprehensive Benchmark and Development Suite with Novel Datasets for Lunar Monocular Depth Estimation

arXiv:2604.09352v1 Announce Type: new Abstract: Monocular Depth Estimation (MDE) is crucial for autonomous lunar rover navigation using electro-optical cameras. However, deploying terrestrial MDE netw

Many Ways to Be Fake: Benchmarking Fake News Detection Under Strategy-Driven AI Generation

arXiv:2604.09514v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled the large-scale generation of highly fluent and deceptive news-like content. While prior wo

MedConceal: A Benchmark for Clinical Hidden-Concern Reasoning Under Partial Observability

arXiv:2604.08788v1 Announce Type: new Abstract: Patient-clinician communication is an asymmetric-information problem: patients often do not disclose fears, misconceptions, or practical barriers unless

Medical Reasoning with Large Language Models: A Survey and MR-Bench

arXiv:2604.08559v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved strong performance on medical exam-style tasks, motivating growing interest in their deployment in real-wor

Mitigating Extrinsic Gender Bias for Bangla Classification Tasks

arXiv:2411.10636v2 Announce Type: replace-cross Abstract: In this study, we investigate extrinsic gender bias in Bangla pretrained language models, a largely underexplored area in low-resource languag

Neurons Speak in Ranges: Breaking Free from Discrete Neuronal Attribution

arXiv:2502.06809v3 Announce Type: replace-cross Abstract: Pervasive polysemanticity in large language models (LLMs) undermines discrete neuron-concept attribution, posing a significant challenge for m

local-aiarxiv-cs-ai

Noise-Aware In-Context Learning for Hallucination Mitigation in ALLMs

arXiv:2604.09021v1 Announce Type: cross Abstract: Auditory large language models (ALLMs) have demonstrated strong general capabilities in audio understanding and reasoning tasks. However, their reliab

NyayaMind- A Framework for Transparent Legal Reasoning and Judgment Prediction in the Indian Legal System

arXiv:2604.09069v1 Announce Type: cross Abstract: Court Judgment Prediction and Explanation (CJPE) aims to predict a judicial decision and provide a legally grounded explanation for a given case based

Process Reward Agents for Steering Knowledge-Intensive Reasoning

arXiv:2604.09482v1 Announce Type: new Abstract: Reasoning in knowledge-intensive domains remains challenging as intermediate steps are often not locally verifiable: unlike math or code, evaluating ste

local-aiarxiv-cs-ai