Search: “evaluation”

Direction-Flipped Influence Audits Reveal Hidden Structure in Moral Choices of LLMs

arXiv:2602.22831v2 Announce Type: replace-cross Abstract: Moral benchmarks for LLMs typically score models on context-free prompts, implicitly treating the measured choice rate as stable. We test this

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Agents

Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain Points

DGX agent

arXiv:2412.11194v2 Announce Type: replace-cross Abstract: Security vulnerabilities in software can have severe consequences; however, manual vulnerability detection is costly and does not scale, espec

agentsarxiv-cs-ai

11 May 2026

Discovering Multiagent Learning Algorithms with Large Language Models

arXiv:2602.16928v3 Announce Type: replace-cross Abstract: Much of the advancement in Multi-Agent Reinforcement Learning (MARL) for imperfect-information games has historically depended on the manual,

Distributional Process Reward Models: Calibrated Prediction of Future Rewards via Conditional Optimal Transport

arXiv:2605.06785v1 Announce Type: cross Abstract: Inference-time scaling methods rely on Process Reward Models (PRMs), which are often poorly calibrated and overestimate success probabilities. We prop

Divide and Conquer: Object Co-occurrence Helps Mitigate Simplicity Bias in OOD Detection

arXiv:2605.07821v1 Announce Type: cross Abstract: Out-of-distribution (OOD) detection is crucial for ensuring the reliability of deep learning models. Existing methods mostly focus on regular entangle

Drawing Lines in Psychological Space: What K-means Clustering Reveals in Simulated and Real Psychometric Data

arXiv:2605.06989v1 Announce Type: cross Abstract: K-means clustering is widely used in psychological and psychometric research to identify profiles, subgroups, and potential typologies, yet its classi

Local Ai

DualResolution Residual Architecture with Artifact Suppression for Melanocytic Lesion Segmentation

arXiv:2508.06816v3 Announce Type: replace Abstract: Lesion segmentation, in contrast to natural scene segmentation, requires handling subtle variations in texture and color, frequent imaging artifacts

local-aiarxiv-cs-cv

DVD: Discrete Voxel Diffusion for 3D Generation and Editing

arXiv:2605.07971v1 Announce Type: new Abstract: We introduce Discrete Voxel Diffusion (DVD), a discrete diffusion framework to generate, assess, and edit sparse voxels for SLat (Structured LATent) bas

Dynamic Properties and Motion Reproducibility of a Compact Pneumatically Actuated Humanoid Upper Body for Data-Driven Control

arXiv:2603.14787v2 Announce Type: replace Abstract: Pneumatically-actuated anthropomorphic robots with high degrees of freedom (DOF) offer significant potential for physical human-robot interaction. H

researcharxiv-cs-ro

Econometric vs. Causal Structure-Learning for Time-Series Policy Decisions: Evidence from the UK COVID-19 Policies

arXiv:2603.00041v2 Announce Type: replace-cross Abstract: Causal machine learning (ML) recovers graphical structures that inform us about potential cause-and-effect relationships. Most progress has fo

Edge Detection for Organ Boundaries via Top Down Refinement and SubPixel Upsampling

arXiv:2508.06805v2 Announce Type: replace Abstract: Accurate localization of organ boundaries is critical in medical imaging for segmentation, registration, surgical planning, and radiotherapy. While

Local Ai

Emergent Manifold Separability during Reasoning in Large Language Models

arXiv:2602.20338v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting significantly improves reasoning in Large Language Models, yet the temporal dynamics of the underlying representati

local-aiarxiv-cs-lg

Emergent Symbolic Structure in Health Foundation Models: Extraction, Alignment, and Cross-Modal Transfer

arXiv:2605.07407v1 Announce Type: new Abstract: Health foundation models (FMs) learn useful representations from wearable sensors, but interpreting what they encode and transferring that knowledge acr

safetyarxiv-cs-lg

Enhancing Eye Movement Biometrics for User Authentication via Continuous Gaze Offset Score Fusion

arXiv:2605.06810v1 Announce Type: cross Abstract: Eye movement biometrics (EMB) use subject-specific gaze dynamics for user authentication and identification. Recent deep learning-based EMB systems ac

Enhancing Federated Quadruplet Learning: Stochastic Client Selection and Embedding Stability Analysis

arXiv:2605.07888v1 Announce Type: cross Abstract: Federated Learning (FL) enables decentralised model training across distributed clients without requiring data centralisation. However, the generalisa

Excluding the Target Domain Improves Extrapolation: Deconfounded Hierarchical Physics Constraints

arXiv:2605.07485v1 Announce Type: cross Abstract: Extrapolation to out-of-distribution conditions is a fundamental challenge for physics-constrained deep generative models. Existing methods apply phys

Experience Sharing in Mutual Reinforcement Learning for Heterogeneous Language Models

arXiv:2605.07244v1 Announce Type: cross Abstract: We introduce Mutual Reinforcement Learning, a framework for concurrent RL post-training in which heterogeneous LLM policies exchange typed experience

Exploring the non-convexity in machine learning using quantum-inspired optimization

arXiv:2605.07947v1 Announce Type: cross Abstract: The escalating complexity of modern machine learning necessitates solving challenging non-convex optimization problems, particularly in high-dimension

EyeCue: Driver Cognitive Distraction Detection via Gaze-Empowered Egocentric Video Understanding

arXiv:2605.07859v1 Announce Type: new Abstract: Driver cognitive distraction is a major cause of road collisions and remains difficult to detect. Unlike manual or visual distraction, cognitive distrac

Faster Verified Explanations for Neural Networks

arXiv:2512.00164v2 Announce Type: replace Abstract: Verified explanations are a principled way to explain the decisions taken by neural networks, which are otherwise black-box in nature. However, thes

researcharxiv-cs-lg

FastOmniTMAE: Parallel Clause Learning for Scalable and Hardware-Efficient Tsetlin Embeddings

model-releasesarxiv-cs-lg

arXiv:2605.06982v1 Announce Type: new Abstract: Embedding models in natural language processing (NLP) increasingly rely on deep architectures such as BERT, while simpler models such as Word2Vec provid

Flexible Entropy Control in RLVR with a Gradient-Preserving Perspective

arXiv:2602.09782v2 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a critical method for enhancing the reasoning capabilities of Large Langu

Frequency-Aware Model Parameter Explorer: A new attribution method for improving explainability

arXiv:2510.03245v2 Announce Type: replace-cross Abstract: State-of-the-art attribution methods rely on adversarial sample generation that applies an all-pass filter across the frequency spectrum, disc

From Clouds to Hallucinations: Atmospheric Retrieval Hijacking in Remote Sensing Vision-Language RAG

arXiv:2605.07273v1 Announce Type: cross Abstract: Multimodal RAG systems increasingly rely on vision-language retrievers to ground visual queries in external textual evidence. Existing adversarial stu

From Specification to Deployment: Empirical Evidence from a W3C VC + DID Trust Infrastructure for Autonomous Agents

arXiv:2605.06738v1 Announce Type: cross Abstract: Autonomous AI agents now transact at production scale -- 69,000 bots executing 165 million transactions across 50 million USDC in cumulative volume on

Applications

From Surface Learning to Deep Understanding: A Grounded AI Tutoring System for Moodle

arXiv:2605.06963v1 Announce Type: cross Abstract: This demo paper describes the development of the AI Teaching & Learning Assistant, a modular Moodle plugin that leverages Retrieval-Augmented Generati

applicationsarxiv-cs-ai

From Synthetic to Real: Toward Identity-Consistent Makeup Transfer with Synthetic and Real Data

model-releasesarxiv-cs-cv

arXiv:2605.07861v1 Announce Type: new Abstract: Makeup transfer aims to apply the makeup style of a reference portrait to a source portrait while preserving identity and background. Early methods form

Hardware

Frozen Backpropagation: Relaxing Weight Symmetry in Deep Spiking Neural Networks

arXiv:2505.13741v2 Announce Type: replace Abstract: Direct training of Spiking Neural Networks (SNNs) on neuromorphic hardware can greatly reduce energy costs compared to GPU-based training. However,

hardwarearxiv-cs-cv

Local Ai

Future Validity is the Missing Statistic: From Impossibility to Phi-Estimation for Grammar-Faithful Speculative Decoding

arXiv:2605.07698v1 Announce Type: new Abstract: Grammar-constrained generation is often combined with local vocabulary masking and speculative decoding, but the resulting sampling law is not the gramm

local-aiarxiv-cs-lg

Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learning

arXiv:2605.06734v1 Announce Type: cross Abstract: Fast Weight Programmers (FWPs) encode temporal dependencies through dynamically updated parameters rather than recurrent hidden states. Quantum FWPs (

Agents

GEM: Generating LiDAR World Model via Deformable Mamba

arXiv:2605.07326v1 Announce Type: new Abstract: World models, which simulate environmental dynamics and generate sensor observations, are gaining increasing attention in autonomous driving. However, p

agentsarxiv-cs-cv

Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions

arXiv:2512.20974v3 Announce Type: replace-cross Abstract: Bayesian Reinforcement Learning (BRL), a subclass of Meta-Reinforcement Learning (Meta-RL), provides a principled framework for generalisation

GPO-V: Jailbreak Diffusion Vision Language Model by Global Probability Optimization

arXiv:2605.07399v1 Announce Type: new Abstract: Diffusion Vision-Language Models (dVLMs), built upon the non-causal foundations of Diffusion Large Language Models (dLLMs), have demonstrated remarkable

safetyarxiv-cs-cv

GRASP -- Graph-Based Anomaly Detection Through Self-Supervised Classification

arXiv:2605.07812v1 Announce Type: cross Abstract: Advanced persistent threat (APT) attacks remain difficult to detect due to their stealth, adaptability, and use of legitimate system components. Prove

researcharxiv-cs-lg

GRaSp: Automatic Example Optimization for In-Context Learning in Low-Data Tasks

arXiv:2605.07454v1 Announce Type: new Abstract: In-context learning enables large language models to adapt to new tasks, but their performance is highly sensitive to the selected examples. Finding eff

researcharxiv-cs-cl

GustPilot: A Hierarchical DRL-INDI Framework for Wind-Resilient Quadrotor Navigation

arXiv:2603.19966v2 Announce Type: replace Abstract: Wind disturbances remain a key barrier to reliable autonomous navigation for lightweight quadrotors, where the rapidly varying airflow can destabili

safetyarxiv-cs-ro

Hierarchical Dual-Subspace Decoupling for Continual Learning in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2605.07512v1 Announce Type: new Abstract: Class-incremental learning aims to continuously acquire new knowledge while preserving previously learned information, thereby mitigating catastrophic f

Hierarchical Task Network Planning with LLM-Generated Heuristics

arXiv:2605.07707v1 Announce Type: new Abstract: HTN planning is a variation of classical planning where, instead of searching for a linear sequence of actions, an algorithm decomposes higher-level tas

How Big Should a Wireless Foundation Model Be?

model-releasesarxiv-cs-lg

arXiv:2605.07266v1 Announce Type: cross Abstract: Wireless foundation models are rapidly emerging as a key enabler of AI-native communication systems, yet a fundamental question remains unanswered: ho

How Far Is Document Parsing from Solved? PureDocBench: A Source-TraceableBenchmark across Clean, Degraded, and Real-World Settings

model-releasesarxiv-cs-cv

arXiv:2605.07492v1 Announce Type: new Abstract: The past year has seen over 20 open-source document parsing models, yet thefield still benchmarks almost exclusively on OmniDocBench, a 1,355-pagemanual

How Well Do LLMs Perform on the Simplest Long-Chain Reasoning Tasks: An Empirical Study on the Equivalence Class Problem

arXiv:2605.06882v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved great improvements in recent years. Nevertheless, it still remains unclear how good LLMs are for reasoning ta

Tutorials

Human-like fleeting memory improves language learning but impairs reading time prediction in transformer language models

arXiv:2508.05803v2 Announce Type: replace Abstract: Human memory is fleeting. As words are processed, the exact wordforms that make up incoming sentences are rapidly lost. Cognitive scientists have lo

tutorialsarxiv-cs-cl

Tutorials

HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs

arXiv:2506.12362v3 Announce Type: replace-cross Abstract: Inductive link prediction with knowledge hypergraphs is the task of predicting missing hyperedges involving completely novel entities (i.e., n

tutorialsarxiv-cs-ai

Inference Time Causal Probing in LLMs

arXiv:2605.07631v1 Announce Type: new Abstract: Causal probing methods aim to test and control how internal representations influence the behavior of generative models. In causal probing, an intervent

InfoGeo: Information-Theoretic Object-Centric Learning for Cross-View Generalizable UAV Geo-Localization

arXiv:2605.07099v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL) is fundamental for precise localization and navigation in GPS-denied environments, aiming to match ground or UAV imag

safetyarxiv-cs-cv

Applications

Intelligent Truck Matching in Full Truckload Shipments using Ping2Hex approach

arXiv:2605.07733v1 Announce Type: cross Abstract: Accurate truck-to-shipment matching using GPS data is foundational for full truckload supply chain visibility, enabling real-time tracking and accurat

applicationsarxiv-cs-ai

InterCoG: Towards Spatially Precise Image Editing with Interleaved Chain-of-Grounding Reasoning

arXiv:2603.01586v3 Announce Type: replace Abstract: Emerging unified editing models have demonstrated strong capabilities in general object editing tasks. However, it remains a significant challenge t

safetyarxiv-cs-cv

Is Chain-of-Thought Really Not Explainability? Chain-of-Thought Can Be Faithful without Hint Verbalization

arXiv:2512.23032v2 Announce Type: replace-cross Abstract: Recent work, using the Biasing Features metric, labels a CoT as unfaithful if it omits a prompt-injected hint that affected the prediction. We