Search: “evaluation”

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer

arXiv:2606.05626v1 Announce Type: new Abstract: Machine-generated text (MGT) attribution aims to identify the specific generator responsible for a given text, thereby providing fine-grained evidence f

5 Jun 2026

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World-Language-Action Model for Unified World Modeling, Language Reasoning, and Action Synthesis

DGX agent

arXiv:2606.05979v1 Announce Type: new Abstract: We propose world-language-action (WLA) models as a new class of embodied foundation models. WLA takes textual instructions, images, and robot states as

hardwarearxiv-cs-ro

5 Jun 2026

Would you still call this Dax? Novel Visual References in VLMs and Humans

arXiv:2606.05409v1 Announce Type: cross Abstract: Vision-language models (VLMs), like human learners, are frequently exposed to new visual concepts, but how they map novel visual references to languag

5 Jun 2026

A Normative Intermediate Representation for ASP-Based Compliance Reasoning

arXiv:2606.04619v1 Announce Type: new Abstract: We propose MONIR, a Modalized-Output Normative Intermediate Representation for ASP-based compliance reasoning. Its core fragment has a staged operationa

A Pathology Foundation Model for Gastric Cancer with Real-World Validation

arXiv:2606.04792v1 Announce Type: new Abstract: Gastric cancer remains a major cause of cancer mortality, yet its histological and molecular heterogeneity complicates diagnosis and risk stratification

safetyarxiv-cs-cv

Achieving Rotation-Invariant Convolution via Non-Learnable Orientation Alignment Operators

arXiv:2404.11309v2 Announce Type: replace Abstract: Achieving rotational invariance in deep neural networks without data augmentation is a research hotspot. Intrinsic invariance enables features to ca

safetyarxiv-cs-cv

Adaptive Minds: Empowering Agents with LoRA-as-Tools

arXiv:2510.15416v2 Announce Type: replace Abstract: We investigate a framework in which LoRA adapters are treated as callable tools that a base language model can dynamically select and invoke. We hyp

Local Ai

Adaptive Patching Is Harder Than It Looks For Time-Series Forecasting

arXiv:2606.04074v1 Announce Type: cross Abstract: Adaptive patching is a recent and compelling proposal for time-series Transformers: allocate finer patches where the sequence looks locally informativ

local-aiarxiv-cs-ai

Agent Planning Benchmark: A Diagnostic Framework for Planning Capabilities in LLM Agents

arXiv:2606.04874v1 Announce Type: new Abstract: Planning is central to LLM agents: before acting, an agent must decompose goals, select tools, reason over constraints, and decide when a task is infeas

AICompanionBench: Benchmarking LLMs-as-Judges for AI Companion Safety

arXiv:2606.04867v1 Announce Type: new Abstract: As AI companion platforms such as Replika and Character.AI rapidly grow, concerns about unsafe human-AI interactions have intensified. This study introd

Aligning Deep Implicit Preferences by Learning to Reason Defensively

arXiv:2510.11194v3 Announce Type: replace Abstract: Personalized alignment is crucial for enabling Large Language Models (LLMs) to engage effectively in user-centric interactions. However, current met

Archi: Agentic Operations at the CMS Experiment

arXiv:2606.04755v1 Announce Type: cross Abstract: We present Archi, an open-source, end-to-end framework for scientific collaborations that combines the systematic ingestion and organization of hetero

Audio Interaction Model

arXiv:2606.05121v1 Announce Type: cross Abstract: Audio is an inherently interactive modality, yet today's Large Audio Language Models (LALMs) are offline, and streaming audio models each handle only

Automated Lexical Coverage for Language Learning: From General to Specialized Word Lists

arXiv:2512.15552v2 Announce Type: replace Abstract: A General Service List (GSL) is a commonly used resource for language learners to identify important English words. Traditional GSL creation is reso

Automatic Generation of Titles for Research Papers Using Language Models

arXiv:2606.05085v1 Announce Type: cross Abstract: The title of a research paper conveys its primary idea and, occasionally, its conclusions in a clear and concise manner. Choosing an appropriate title

Benchmarking Living-Screen-Native GUI Agents on Short-Video Platforms

arXiv:2606.04701v1 Announce Type: cross Abstract: GUI agents today assume a static screen, where the world is frozen between two actions. However, real interfaces such as short-video applications viol

Beyond Objective Equivalence: Constraint Injection for LLM-Based Optimization Modeling on Vehicle Routing Problems

arXiv:2606.04816v1 Announce Type: new Abstract: Large language models (LLMs) increasingly translate natural-language optimization problems into executable solver code. Yet for constraint-dense operati

Beyond Symmetric Alignment: Spectral Diagnostics of Modality Imbalance in Vision-Language Models in the Medical Domain

arXiv:2606.04613v1 Announce Type: new Abstract: Vision-Language Models (VLMs) struggle when applied to medical image-text data, yet the tools available to diagnose this failure remain limited. Existin

safetyarxiv-cs-cv

Bilevel Autoresearch: Meta-Autoresearching Itself

arXiv:2603.23420v2 Announce Type: replace Abstract: If autoresearch is itself a form of research, then autoresearch can be applied to research itself. We present Bilevel Autoresearch, a bilevel framew

Boosting Self-Consistency with Ranking

arXiv:2606.05054v1 Announce Type: new Abstract: Self-consistency improves large language models by sampling multiple reasoning paths and selecting the most frequent answer, but majority voting often f

Bypassing Prompt Guards in Production with Controlled-Release Prompting

model-releasesarxiv-cs-lg

arXiv:2510.01529v3 Announce Type: replace Abstract: Ball et al. recently established that prompt filtering for AI alignment faces a fundamental barrier: under standard cryptographic assumptions, no fi

Caliper: Probing Lexical Anchors versus Causal Structure in LLMs

arXiv:2606.04915v1 Announce Type: new Abstract: Large language models reach 50 to 70% accuracy on causal reasoning benchmarks such as CLadder, but it is unclear whether this reflects structural reason

Cascading Hallucination in Agentic RAG: The CHARM Framework for Detection and Mitigation

arXiv:2606.04435v1 Announce Type: new Abstract: Multi-step agentic retrieval-augmented generation (RAG) pipelines have demonstrated significant capability for complex reasoning tasks, yet remain vulne

CleanCodec: Efficient and Robust Speech Tokenization via Perceptually Guided Encoding

arXiv:2606.04418v1 Announce Type: cross Abstract: Neural audio codecs are a key component of speech processing pipelines, compressing audio into discrete tokens for downstream modeling. However, exist

Applications

ClustRecNet: A Novel End-to-End Deep Learning Framework for Clustering Algorithm Recommendation

arXiv:2509.25289v4 Announce Type: replace-cross Abstract: Identifying an effective clustering algorithm for a given dataset remains a fundamental unsupervised learning issue. We introduce ClustRecNet,

applicationsarxiv-cs-ai

Local Ai

Coarse-to-fine Hierarchical Architecture with Sequential Mamba for Brain Reconstruction

arXiv:2606.04772v1 Announce Type: cross Abstract: Understanding the relationship between deep visual representations and the human visual system is a fundamental challenge in computational neuroscienc

local-aiarxiv-cs-ai

ContactExplorer: Contact Coverage-Guided Exploration for General-Purpose Dexterous Manipulation

arXiv:2603.10971v2 Announce Type: replace-cross Abstract: Reinforcement learning has achieved remarkable success in domains such as Atari games, navigation, and locomotion, where exploration can often

Controllable Dynamic 3D Shape Generation via 3D Trajectories and Text

arXiv:2606.05162v1 Announce Type: new Abstract: We introduce T2Mo, a feed-forward framework for controllable dynamic 3D shape generation conditioned on 3D trajectories and text. Due to the inherent am

researcharxiv-cs-cv

CoPark: Learning Reactive Parking via Self-Play

model-releasesarxiv-cs-ro

arXiv:2606.04149v1 Announce Type: new Abstract: Learning a single policy that reaches a goal with high geometric precision while interacting safely with nearby agents poses conflicting objectives. Pre

Counterfactual Explanations for Deep Two-Sample Testing

arXiv:2606.04009v1 Announce Type: cross Abstract: Two-sample testing is a fundamental tool for detecting distributional differences across scientific domains, but classical tests (including kernel-bas

Culturally Grounded Personas in Large Language Models: Characterization and Alignment with Socio-Psychological Value Frameworks

arXiv:2601.22396v2 Announce Type: replace-cross Abstract: Despite the growing utility of Large Language Models (LLMs) for simulating human behavior, the extent to which these synthetic personas accura

safetyarxiv-cs-ai

Curvature-aware dynamic precision approach for physics-informed neural networks

arXiv:2606.04736v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) have become a promising framework for simulating partial differential equations (PDEs) by embedding physical

DAR: Deontic Reasoning with Agentic Harnesses

arXiv:2606.05009v1 Announce Type: cross Abstract: Deontic reasoning is the task of answering questions by applying explicit rules and policies to case-specific facts, for example computing tax liabili

Data Attribution in Large Language Models via Bidirectional Gradient Optimization

arXiv:2606.04928v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed across diverse applications, raising critical questions for governance, accountability, and dat

Data Efficient Complex Feature Fusion Network For Hyperspectral Image Classification

arXiv:2606.04710v1 Announce Type: new Abstract: This work presents a data-efficient variant of the Attention-Based Dual-Branch Complex Feature Fusion Network (CFFN) for hyperspectral image classificat

researcharxiv-cs-cv

Derivative Informed Learning of Exchange-Correlation Functionals

arXiv:2606.04279v1 Announce Type: new Abstract: Machine-learned (ML) exchange-correlation (XC) functionals aim to replace human-designed density functional approximations by learning directly from ref

researcharxiv-cs-lg

Discourse-Role Labels as Presentation-Time Variables for Context Use in Language Models

arXiv:2606.04109v1 Announce Type: new Abstract: Context-augmented language model systems often wrap supplied content with labels such as Reference:, Evidence:, Instruction:, Note:, or Example:, but th

Dive into the Scene: Breaking the Perceptual Bottleneck in Vision-Language Decision Making via Focus Plan Generation

arXiv:2606.04046v1 Announce Type: cross Abstract: In embodied vision-language decision making tasks such as robotic manipulation and navigation, Vision-Language and Vision-Language-Action Models (VLMs

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats

arXiv:2606.04115v1 Announce Type: cross Abstract: Quantizing large language models (LLMs) to low-precision floating-point representations is central to efficient deployment, yet applying a single bit-

Do Transformers Need Three Projections? Systematic Study of QKV Variants

arXiv:2606.04032v1 Announce Type: cross Abstract: Transformers have become the standard solution for various AI tasks, with the query, key, and value (QKV) attention formulation playing a central role

Dynamic Multi-Pair Trading Strategy in Cryptocurrency Markets with Deep Reinforcement Learning

arXiv:2606.04574v1 Announce Type: new Abstract: This study aims to determine whether the application of Deep Reinforcement Learning (DRL) as a specialized execution overlay can enhance pair trading in

safetyarxiv-cs-lg

Applications

Early Detection of Alzheimer's Disease Using Explainable Machine Learning on Clinical Biomarkers: A Multi-Class Classification Study Using the Alzheimer's Disease Neuroimaging Initiative (ADNI) Dataset

arXiv:2606.03995v1 Announce Type: cross Abstract: Background: Alzheimer's disease (AD) affects over 55 million people worldwide. Accurate, interpretable detection of normal cognition (NC), mild cognit

applicationsarxiv-cs-ai

Efficient Brood Cell Detection in Layer Trap Nests for Bees and Wasps: Balancing Labeling Effort and Species Coverage

arXiv:2603.16652v2 Announce Type: replace Abstract: Monitoring cavity-nesting wild bees and wasps is vital for biodiversity research and conservation. Layer trap nests (LTNs) are emerging as a valuabl

researcharxiv-cs-cv

Local Ai

Enhancing MedSAM with a Lightweight Box Predictor for Medical Image Segmentation

arXiv:2606.04705v1 Announce Type: cross Abstract: Semantic segmentation in medical imaging is a critical yet challenging task due to data scarcity and high variability across modalities. While foundat

local-aiarxiv-cs-ai

Enhancing the MADDPG Algorithm for Multi-Agent Learning via Action Inference and Importance Sampling

arXiv:2606.05021v1 Announce Type: new Abstract: We investigate multi-agent deep reinforcement learning and propose two enhancements to the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algor

safetyarxiv-cs-lg

Entity Binding Failures in Speech LLM Reasoning: Diagnosis and Chain-of-Thought Intervention

arXiv:2606.04474v1 Announce Type: new Abstract: Speech Large Language Models (SLLMs) underperform their text counterparts on complex reasoning. We reveal that this modality gap is not a uniform cognit

Episodic Memory Temporal Consistency for Cooperative Multi-Agent Reinforcement Learning

arXiv:2606.04492v1 Announce Type: new Abstract: Cooperative Multi-Agent Reinforcement Learning (MARL) frequently suffers from severe reward sparsity and exploration bottlenecks. While episodic memory

agentsarxiv-cs-lg

EvalStop: Using World Feedback to Detect and Correct Reward Overoptimization in Multi-Tenant RLHF Platforms

arXiv:2606.04145v1 Announce Type: cross Abstract: Cloud LLM fine-tuning platforms increasingly serve RLHF workloads, where a learned reward model is optimized as a proxy for human quality. As Gao et a