Search: “evaluation”

Simple Self-Conditioning Adaptation for Masked Diffusion Models

arXiv:2604.26985v1 Announce Type: cross Abstract: Masked diffusion models (MDMs) generate discrete sequences by iterative denoising under an absorbing masking process. In standard masked diffusion, if

researcharxiv-cs-ai

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Stable Behavior, Limited Variation: Persona Validity in LLM Agents for Urban Sentiment Perception

DGX agent

arXiv:2604.28048v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as proxies for human perception in urban analysis, yet it remains unclear whether persona prompting p

safetyarxiv-cs-cl

1 May 2026

TiMem: Temporal-Hierarchical Memory Consolidation for Long-Horizon Conversational Agents

arXiv:2601.02845v2 Announce Type: replace-cross Abstract: Long-horizon conversational agents have to manage ever-growing interaction histories that quickly exceed the finite context windows of large l

researcharxiv-cs-ai

Towards Generalizable Mapping of Hedges and Linear Woody Features from Earth Observation Data: a national Product for Germany

arXiv:2604.27247v1 Announce Type: new Abstract: Hedges and other linear woody features provide valuable ecosystem services, particularly within intensively managed agricultural landscapes. They are ke

researcharxiv-cs-cv

Applications

TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning

arXiv:2604.27861v1 Announce Type: cross Abstract: Decompositional jailbreaks pose a critical threat to large language models (LLMs) by allowing adversaries to fragment a malicious objective into a seq

applicationsarxiv-cs-cl

Agents

Understanding Adversarial Transferability in Vision-Language Models for Autonomous Driving: A Cross-Architecture Analysis

arXiv:2604.27414v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used in autonomous driving because they combine visual perception with language-based reasoning, supporti

agentsarxiv-cs-cv

Unsupervised Electrofacies Classification and Porosity Characterization in the Offshore Keta Basin Using Wireline Logs

arXiv:2604.27126v1 Announce Type: new Abstract: This study presents an unsupervised machine learning workflow for electrofacies analysis in the offshore Keta Basin, Ghana, where core data are scarce.

researcharxiv-cs-ai

Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling

arXiv:2604.28185v1 Announce Type: new Abstract: Recent visual generation models have made major progress in photorealism, typography, instruction following, and interactive editing, yet they still str

Tutorials

A Data-Centric Framework for Intraoperative Fluorescence Lifetime Imaging for Glioma Surgical Guidance

arXiv:2604.26147v1 Announce Type: cross Abstract: Accurate intraoperative assessment of glioma infiltration is essential for maximizing tumor resection while preserving functional brain tissue. Fluore

tutorialsarxiv-cs-ai

A Multimodal Pre-trained Network for Integrated EEG-Video Seizure Detection

arXiv:2604.26379v1 Announce Type: new Abstract: Reliable seizure detection in mouse models is essential for preclinical epilepsy research, yet manual review of synchronized video-EEG recordings is lab

safetyarxiv-cs-cv

A Systematic Comparison of Prompting and Multi-Agent Methods for LLM-based Stance Detection

arXiv:2604.26319v1 Announce Type: new Abstract: Stance detection identifies the attitude of a text author toward a given target. Recent studies have explored various LLM-based strategies for this task

Agents

AGEL-Comp: A Neuro-Symbolic Framework for Compositional Generalization in Interactive Agents

arXiv:2604.26522v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents exhibit systemic failures in compositional generalization, limiting their robustness in interactive environments

agentsarxiv-cs-ai

Benchmarking the Safety of Large Language Models for Robotic Health Attendant Control

arXiv:2604.26577v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly considered for deployment as the control component of robotic health attendants, yet their safety in this

safetyarxiv-cs-ai

ClassEval-Pro: A Cross-Domain Benchmark for Class-Level Code Generation

arXiv:2604.26923v1 Announce Type: cross Abstract: LLMs have achieved strong results on both function-level code synthesis and repository-level code modification, yet a capability that falls between th

ClawGym: A Scalable Framework for Building Effective Claw Agents

arXiv:2604.26904v1 Announce Type: cross Abstract: Claw-style environments support multi-step workflows over local files, tools, and persistent workspace states. However, scalable development around th

CoFL: Continuous Flow Fields for Language-Conditioned Navigation

arXiv:2603.02854v2 Announce Type: replace-cross Abstract: Existing language-conditioned navigation systems typically rely on modular pipelines or trajectory generators, but the latter use each scene--

local-aiarxiv-cs-ai

Decoupled Prototype Matching with Vision Foundation Models for Few-Shot Industrial Object Detection

arXiv:2604.26404v1 Announce Type: new Abstract: Industrial object detection systems typically rely on large annotated datasets, which are expensive to collect and challenging to maintain in industrial

DenseStep2M: A Scalable, Training-Free Pipeline for Dense Instructional Video Annotation

arXiv:2604.26565v1 Announce Type: new Abstract: Long-term video understanding requires interpreting complex temporal events and reasoning over procedural activities. While instructional video corpora,

Hierarchical adaptive control for real-time dynamic inference at the edge

arXiv:2604.26470v1 Announce Type: new Abstract: Industrial systems increasingly depend on Machine Learning (ML), and operate on heterogeneous nodes that must satisfy tight latency, energy, and memory

local-aiarxiv-cs-lg

Improving Bayesian Optimization for Portfolio Management with an Adaptive Scheduling

arXiv:2504.13529v4 Announce Type: replace Abstract: Existing black-box portfolio management systems are prevalent in the financial industry due to commercial and safety constraints, though their perfo

safetyarxiv-cs-lg

Inference-Time Scaling of Verification: Self-Evolving Deep Research Agents via Test-Time Rubric-Guided Verification

arXiv:2601.15808v2 Announce Type: replace Abstract: Recent advances in Deep Research Agents (DRAs) are transforming automated knowledge discovery and problem-solving. While the majority of existing ef

safetyarxiv-cs-ai

KAYRA: A Microservice Architecture for AI-Assisted Karyotyping with Cloud and On-Premise Deployment

arXiv:2604.26869v1 Announce Type: cross Abstract: We present KAYRA, an end-to-end karyotyping system that operates inside the operational constraints of a clinical cytogenetic laboratory. KAYRA is arc

researcharxiv-cs-cv

Learning to Ask: When LLM Agents Meet Unclear Instruction

arXiv:2409.00557v4 Announce Type: replace-cross Abstract: Equipped with the capability to call functions, modern large language models (LLMs) can leverage external tools for addressing a range of task

Open Problems in Frontier AI Risk Management

arXiv:2604.25982v1 Announce Type: cross Abstract: Frontier AI both amplifies existing risks and introduces qualitatively novel challenges. Not only is there a notable lack of stable scientific consens

safetyarxiv-cs-ai

Point Cloud Registration via Probabilistic Self-Update Local Correspondence and Line Vector Sets

arXiv:2604.26318v1 Announce Type: new Abstract: Point cloud registration (PCR) is a fundamental task for integrating 3D observations in remote sensing applications. This paper proposes a fast and effe

local-aiarxiv-cs-cv

PPG-Based Affect Recognition with Long-Range Deep Models: A Measurement-Driven Comparison of CNN, Transformer, and Mamba Architectures

arXiv:2604.26078v1 Announce Type: new Abstract: Photoplethysmography (PPG) is increasingly used in wearable affective computing due to its low cost and ease of integration into consumer devices. Recen

researcharxiv-cs-lg

Random Cloud: Finding Minimal Neural Architectures Without Training

arXiv:2604.26830v1 Announce Type: cross Abstract: I propose the Random Cloud method, a training-free approach to neural architecture search that discovers minimal feedforward network topologies throug

SpecTr-GBV: Multi-Draft Block Verification Accelerating Speculative Decoding

arXiv:2604.25925v1 Announce Type: new Abstract: Autoregressive language models suffer from high inference latency due to their sequential decoding nature. Speculative decoding (SD) mitigates this by e

State Beyond Appearance: Diagnosing and Improving State Consistency in Dial-Based Measurement Reading

arXiv:2604.26614v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved impressive progress on general multimodal tasks, yet they remain brittle on dial-based measuremen

Applications

The hidden risks of temporal resampling in clinical reinforcement learning

arXiv:2602.06603v3 Announce Type: replace Abstract: Reinforcement learning (RL) is a type of artificial intelligence for making optimal choices. In healthcare, researchers generally use offline RL (OR

applicationsarxiv-cs-lg

TildeOpen LLM: Leveraging Curriculum Learning to Achieve Equitable Language Representation

arXiv:2603.08182v2 Announce Type: replace-cross Abstract: Large language models often underperform in many European languages due to the dominance of English and a few high-resource languages in train

ViCrop-Det: Spatial Attention Entropy Guided Cropping for Training-Free Small-Object Detection

arXiv:2604.26806v1 Announce Type: cross Abstract: Transformer-based architectures have established a dominant paradigm in global semantic perception; however, they remain fundamentally constrained by

local-aiarxiv-cs-ai

A paradox of AI fluency

arXiv:2604.25905v1 Announce Type: new Abstract: How much does a user's skill with AI shape what AI actually delivers for them? This question is critical for users, AI product builders, and society at

An analysis of sensor selection for fruit picking with suction-based grippers

arXiv:2604.24906v1 Announce Type: cross Abstract: Robotic fruit harvesting often fails to reliably detect whether a fruit has been successfully picked, limiting efficiency and increasing crop damage.

researcharxiv-cs-lg

Analyzing LLM Reasoning to Uncover Mental Health Stigma

arXiv:2604.25053v1 Announce Type: new Abstract: While large language models (LLMs) are increasingly being explored for mental health applications, recent studies reveal that they can exhibit stigma to

Benchmarking and Adapting On-Device LLMs for Clinical Decision Support

arXiv:2601.03266v2 Announce Type: replace Abstract: Large language models (LLMs) have rapidly advanced in clinical decision-making, yet the deployment of proprietary systems is hindered by privacy con

Benchmarking Logistic Regression, SVM, and LightGBM Against BiLSTM with Attention for Sentiment Analysis on Indonesian Product Reviews

arXiv:2604.25452v1 Announce Type: new Abstract: Sentiment analysis of product reviews on e-commerce platforms plays a critical role in automatically understanding customer satisfaction and providing a

Beyond Accuracy: Benchmarking Cross-Task Consistency in Unified Multimodal Models

arXiv:2604.25072v1 Announce Type: new Abstract: Unified Multimodal Models (uMMs) aim to support both visual understanding and visual generation within a shared representation. However, existing evalua

safetyarxiv-cs-cv

Bug-Report-Driven Fault Localization: Industrial Benchmarking and Lesson Learned at ABB Robotics

arXiv:2604.25700v1 Announce Type: cross Abstract: Software quality assurance remains a major challenge in industrial environments, where large-scale and long-lived systems inevitably accumulate defect

local-aiarxiv-cs-lg

Categorical Optimization with Bayesian Anchored Latent Trust Regions for Structural Design under High-Dimensional Uncertainty

arXiv:2604.25241v1 Announce Type: new Abstract: Categorical structural optimization under aleatoric uncertainty is challenging because each design variable must be selected from a finite catalog of ad

researcharxiv-cs-lg

DiscreteRTC: Discrete Diffusion Policies are Natural Asynchronous Executors

arXiv:2604.25050v1 Announce Type: new Abstract: Unlike chatbots, physical AI must act while the world keeps evolving. Therefore, the inter-chunk pause of synchronous executors are fatal for dynamic ta

safetyarxiv-cs-ro

DV-World: Benchmarking Data Visualization Agents in Real-World Scenarios

arXiv:2604.25914v1 Announce Type: new Abstract: Real-world data visualization (DV) requires native environmental grounding, cross-platform evolution, and proactive intent alignment. Yet, existing benc

Dynamic UGV-UAV Cooperative Path Planning in Uncertain Environments

arXiv:2604.25267v1 Announce Type: new Abstract: This paper addresses the Dynamic UGV-UAV Cooperative Path Planning (DUCPP) problem involving one unmanned ground vehicle (UGV) assisted by one or more u

researcharxiv-cs-ro

Elderly-Contextual Data Augmentation via Speech Synthesis for Elderly ASR

arXiv:2604.24770v1 Announce Type: new Abstract: Despite recent progress in automatic speech recognition (ASR), elderly ASR (EASR) remains challenging due to limited training data and the distinct acou

Enhancing Financial Report Question-Answering: A Retrieval-Augmented Generation System with Reranking Analysis

arXiv:2603.16877v2 Announce Type: replace Abstract: Financial analysts face significant challenges extracting information from lengthy 10-K reports, which often exceed 100 pages. This paper presents a

Exploring Reasoning Reward Model for Agents

arXiv:2601.22154v2 Announce Type: replace-cross Abstract: Agentic Reinforcement Learning (Agentic RL) has achieved notable success in enabling agents to perform complex reasoning and tool use. However

FCMBench-Video: Benchmarking Document Video Intelligence

arXiv:2604.25186v1 Announce Type: new Abstract: Document understanding is a critical capability in financial credit review, onboarding, and remote verification, where both decision accuracy and eviden

Generative AI Carries Non-Democratic Biases and Stereotypes: Representation of Women, Black Individuals, Age Groups, and People with Disability in AI-Generated Images across Occupations

arXiv:2409.13869v2 Announce Type: replace-cross Abstract: In this study, I investigate how generative artificial intelligence (AI) systems reproduce and reinforce societal biases, with a specific focu

safetyarxiv-cs-cl