Search: “evaluation”

arXiv:2605.24386v1 Announce Type: cross Abstract: Fermi-Dirac machines were proposed recently as an approach to solving semidefinite optimization problems on quantum computers. Here, we reinterpret th

tutorialsarxiv-cs-lg

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Fine-Tuning Over Architectural Complexity: Broad-Coverage PII Detection on PIIBench with DeBERTa

DGX agent

arXiv:2605.25816v1 Announce Type: cross Abstract: Personally identifiable information (PII) detection systems are frequently trained within narrow source or domain boundaries, limiting coverage when d

researcharxiv-cs-ai

26 May 2026

FoodMonitor: Benchmarking MLLMs for Explainable Compliance Analysis

arXiv:2605.24503v1 Announce Type: cross Abstract: As AI-powered compliance monitoring becomes increasingly important in public governance and industrial safety, the ability to provide verifiable evide

Forgotten Words: Benchmarking NeoBERT for Dementia Detection in Low-Resource Conversational Filipino and English Speech

arXiv:2605.26007v1 Announce Type: new Abstract: Dementia detection from spontaneous speech offers a scalable approach to cognitive screening, yet NLP systems remain predominantly English-centric. This

researcharxiv-cs-cl

From Automation to Collaboration: Human-in-the-Loop Methods for Safe and Trustworthy NLP

arXiv:2605.25226v1 Announce Type: new Abstract: Large language models are widely deployed in high-stakes NLP tasks, yet risks such as bias, hallucination, adversarial vulnerability and unreliable gene

safetyarxiv-cs-cl

From Model Scaling to System Scaling: Scaling the Harness in Agentic AI

arXiv:2605.26112v1 Announce Type: new Abstract: This paper studies the next major bottleneck in agentic AI as system scaling, not only model scaling: the design of auditable, persistent, modular, and

INSIGHT: INference-time Sequence Introspection for Generating Help Triggers in Vision-Language-Action Models

arXiv:2510.01389v2 Announce Type: replace-cross Abstract: Recent Vision-Language-Action (VLA) models show strong generalization capabilities, yet they lack introspective mechanisms for anticipating fa

Insuring Every Action: An Authority Frontier Framework for Runtime Actuarial Control of Autonomous AI Agents

arXiv:2605.25632v1 Announce Type: new Abstract: Autonomous AI agents increasingly issue side-effect-bearing actions: database mutations, refunds, payments, external commitments. We propose the Actuari

IsaacIPC: Coupling High-Fidelity Simulation and Realistic Rendering for Contact-Rich Robotic Systems

arXiv:2605.24339v1 Announce Type: new Abstract: We present IsaacIPC, a robotic simulation framework that couples GPU accelerated incremental potential contact (IPC) with IsaacSim/Lab. IsaacIPC maps si

safetyarxiv-cs-ro

Iterate Until Retrieved: Factual Nugget Optimization for Discoverable Continual Corrections in Agentic RAG

arXiv:2605.25641v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) systems in complex B2B (business-to-business) settings may often receive free-form response feedback. Rathe

agentsarxiv-cs-cl

LiveMCP-101: Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queries

arXiv:2508.15760v2 Announce Type: replace-cross Abstract: Tool calling has emerged as a critical capability for AI agents. In contrast to conventional tool calling frameworks that rely on static, prov

LLM-as-a-Reviewer: Benchmarking Their Ability, Divergence, and Prompt Injection Resistance as Paper Reviewers

model-releasesarxiv-cs-cl

arXiv:2605.25415v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in academic peer review, yet their reliability, alignment with human judgment, and robustness to adve

LLM-SAA: LLM-persona Generated Distributions for Decision-making

arXiv:2602.06357v2 Announce Type: replace Abstract: LLMs can generate a wealth of data, ranging from simulated personas imitating human valuations and preferences, to demand forecasts based on world k

researcharxiv-cs-lg

M^3-Verse: A 'Spot the Difference' Challenge for Large Multimodal Models

arXiv:2512.18735v2 Announce Type: replace-cross Abstract: Modern Large Multimodal Models (LMMs) have demonstrated extraordinary ability in static image and single-state spatial-temporal understanding.

Hardware

MathOptAI.jl: Embed trained machine learning predictors into JuMP models

arXiv:2507.03159v2 Announce Type: replace Abstract: We present exttt{MathOptAI.jl}, an open-source Julia library for embedding trained machine learning predictors into a JuMP model. exttt{MathOptAI.jl

hardwarearxiv-cs-lg

Metacognition Should Be the Scientific Framework for Bounded and Effective Self-Governance in Generative AI

arXiv:2605.23981v1 Announce Type: cross Abstract: Generative AI research increasingly confronts a shared problem: systems must sustain yet govern their own generative activity when uncertainty is high

safetyarxiv-cs-ai

Multi-Agent Specification-based Metamorphic Testing of FMU-Based Simulations

arXiv:2605.25101v1 Announce Type: cross Abstract: In many industrial domains, the Functional Mock-up Interface (FMI) is used to exchange simulation models as Functional Mock-up Units (FMUs) across dif

Multilingual Phonological Feature Recognition with Self-Supervised Speech Models

arXiv:2605.25596v1 Announce Type: new Abstract: Phonological features provide a language-general and linguistically grounded representation of speech. We present PhonoQ-2.0, a multilingual frame-level

researcharxiv-cs-cl

Nano World Models: A Minimalist Implementation of Future Video Prediction

arXiv:2605.23993v1 Announce Type: cross Abstract: World models have become a central paradigm for learning predictive simulators that support generation, planning, and decision-making. Yet, despite ra

PACT: Proactive Asking for Continual Task Assistance in Human-Robot Collaboration

arXiv:2605.24350v1 Announce Type: new Abstract: Robotic assistants in long-term human-robot collaboration need to assist users under partial observations while leveraging cross-day interaction history

researcharxiv-cs-ro

Partner-Aware Hierarchical Skill Discovery for Robust Human-AI Collaboration

arXiv:2605.24352v1 Announce Type: new Abstract: Multi-agent collaboration, especially in human-AI teaming, requires agents that can adapt to novel partners with diverse and dynamic behaviors. Conventi

PCGRLLM: Large Language Model-Driven Reward Design for Procedural Content Generation Reinforcement Learning

arXiv:2502.10906v2 Announce Type: replace Abstract: Reward design plays a pivotal role in the training of game AIs, requiring substantial domain-specific knowledge and human effort. In recent years, s

Performance Comparison of Classical and Neural Sampling Algorithms for Robotic Navigation

arXiv:2605.25010v1 Announce Type: cross Abstract: Integrating artificial intelligence (AI) into sampling-based motion planning provides new possibilities for improving autonomous navigation efficiency

PerSoMed: A Large-Scale Balanced Dataset for Persian Social Media Text Classification

arXiv:2602.19333v2 Announce Type: replace Abstract: This research introduces the first large-scale, well-balanced Persian social media text classification dataset, specifically designed to address the

researcharxiv-cs-cl

Persuasion Should be Double-Blind: A Multi-Domain Dialogue Dataset With Faithfulness Based on Causal Theory of Mind

arXiv:2502.21297v2 Announce Type: replace Abstract: Persuasive dialogue is central to human communication, yet existing datasets often rely on a single language model generating both roles, producing

agentsarxiv-cs-cl

Pixelwise Uncertainty Quantification of Accelerated MRI Reconstruction

arXiv:2601.13236v2 Announce Type: replace-cross Abstract: Parallel imaging techniques reduce magnetic resonance imaging (MRI) scan time but image quality degrades as the acceleration factor increases.

Applications

QUIVER: A Formal Framework for Quantifying Perturbation Propagation and Bifurcation in Compound AI Systems

arXiv:2605.23956v1 Announce Type: new Abstract: Compound AI systems that chain multiple LLM calls into directed computation graphs are now the dominant architecture for production AI. Although these a

applicationsarxiv-cs-ai

Reading, Not Thinking: Understanding and Bridging the Modality Gap When Text Becomes Pixels in Multimodal LLMs

arXiv:2603.09095v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) can process text presented as images, yet they often perform worse than when the same content is provided a

safetyarxiv-cs-cl

Red-Teaming Claude Opus and ChatGPT-based Security Advisors for Trusted Execution Environments

arXiv:2602.19450v2 Announce Type: replace-cross Abstract: Trusted Execution Environments (TEEs) (e.g., Intel SGX and ArmTrustZone) aim to protect sensitive computation from a compromised operating sys

Reinforcement Learning for Laser Additive Manufacturing Scan-Order Optimisation: A Bilevel Proxy--FEA Diagnostic Framework for Reward and World-Model Diagnosis

model-releasesarxiv-cs-lg

arXiv:2605.25063v1 Announce Type: new Abstract: Reinforcement learning offers a promising approach for scan-order optimisation in laser additive manufacturing, where sequential scan decisions critical

Rethinking Weak Supervision in Anomaly Detection: A Comprehensive Benchmark

arXiv:2605.26068v1 Announce Type: cross Abstract: Weakly supervised anomaly detection (WSAD) has developed in three primary directions: incomplete, inexact, and inaccurate supervision. However, these

Hardware

SA-Kura: An Energy-Efficient Systolic Array Accelerator for Locally-Coupled Kuramoto Drift in Diffusion Sampling

arXiv:2605.24016v1 Announce Type: cross Abstract: Diffusion inference remains costly for edge deployment, yet existing accelerators focus almost exclusively on score networks because standard drift is

hardwarearxiv-cs-ai

SemanticZip: A Pilot Framework for Lossy Text Compression with LLMs as Semantic Decompressors

arXiv:2605.24541v1 Announce Type: cross Abstract: Text compression for large language model (LLM) systems is usually framed as token deletion, retrieval, summarization, or exact reconstruction. We stu

SODE: Analyzing Social Dynamics in LLM Agents

arXiv:2605.23949v1 Announce Type: cross Abstract: As Large Language Models (LLMs) evolve into interactive agents, understanding their behavioral alignment within human social dynamics becomes essentia

SpecAlign: A Semantic Alignment Framework for SystemVerilog Assertion Generation

arXiv:2605.25181v1 Announce Type: new Abstract: Existing Large Language Model (LLM) approaches to SystemVerilog Assertion (SVA) generation primarily focus on syntactic validity and formal verification

safetyarxiv-cs-ai

Specification-Based Code-Text-Code Reengineering for LLM-Mediated Software Evolution

arXiv:2605.25232v1 Announce Type: cross Abstract: Direct Code2Code transformation remains challenging to control because it can preserve surface-level syntax while introducing semantic drift, hidden b

Strat-Reasoner: Reinforcing Strategic Reasoning of LLMs in Multi-Agent Games

arXiv:2605.04906v2 Announce Type: replace Abstract: While Large Language Models (LLMs) excel in certain reasoning tasks, they struggle in multi-agent games where the final outcome depends on the joint

safetyarxiv-cs-ai

STREAM: A Data-Centric Framework for Mining High-Value Task-Oriented Dialogues from Streaming Media

arXiv:2605.25162v1 Announce Type: cross Abstract: Large language models for vertical domains are bottlenecked by the scarcity of complex, domain-specific task-oriented dialogues. Existing data acquisi

Applications

StrTransformer: Source-Wise Structured Transformers for Unsupervised Blind Source Recovery

arXiv:2605.25648v1 Announce Type: cross Abstract: This paper proposes StrTransformer, a source-wise structured Transformer framework for blind source recovery and branch-wise latent modeling. Instead

applicationsarxiv-cs-lg

Test-Time Deep Thinking to Explore Implicit Rules

arXiv:2605.24828v1 Announce Type: new Abstract: With the continuous advancement of Large Language Models (LLMs), intelligent agents are becoming increasingly vital. However, these agents often fail in

TIAR: Trajectory-Informed Advantage Reweighting for LLM Abstention Learning

arXiv:2605.25850v1 Announce Type: cross Abstract: This paper investigates large language model (LLM) abstention learning, specifically using ternary reward, which incentivize truthfulness in large lan

TimeSpot: Benchmarking Geo-Temporal Understanding in Vision-Language Models in Real-World Settings

model-releasesarxiv-cs-cl

arXiv:2603.06687v2 Announce Type: replace-cross Abstract: Geo-temporal understanding, the ability to infer location, time, and contextual properties from visual input alone, underpins applications suc

Towards Large Model Feature Coding

model-releasesarxiv-cs-lg

arXiv:2605.24025v1 Announce Type: cross Abstract: Large models have delivered remarkable performance across a wide range of perception and generation tasks, yet practical deployment is increasingly co

Uncertainty Decomposition via Cyclical SG-MCMC and Soft-label Learning for Subjective NLP

arXiv:2605.24773v1 Announce Type: new Abstract: Annotator disagreement in emotion classification reflects ambiguity intrinsic to emotion concepts and is essential for predictor-quality assessment in s

Local Ai

Unlocking Apple's Private Cloud Compute: An Analysis of Privacy-Preserving Artificial Intelligence

arXiv:2605.24239v1 Announce Type: cross Abstract: Many existing Artificial Intelligence (AI) solutions on mobile devices rely on an extensive collection of sensitive data, raising privacy concerns and

local-aiarxiv-cs-ai

When Can We Trust Early Warnings? Leakage-Excluded Early Outcome Prediction from LMS Interaction Logs

arXiv:2605.25794v1 Announce Type: new Abstract: Early-warning models built from Learning Management System (LMS) logs aim to predict end-of-course outcomes early enough to enable timely learner suppor

Who judges the judges? Governance from metrics: a runtime framework for continuous LLM compliance monitoring

arXiv:2605.24737v1 Announce Type: cross Abstract: Current approaches to AI compliance treat conformity as a binary, audit-time verdict rather than a continuous, measurable property of production syste

WLNO: Wavelet-Laplace Neural Operator for Solving Partial Differential Equations

model-releasesarxiv-cs-lg

arXiv:2605.24658v1 Announce Type: new Abstract: This work introduces the Wavelet-Laplace Neural Operator (WLNO), a novel neural operator that fuses Haar wavelet multi-scale spatial decomposition with