Search: “evaluation”

GAVEL: Grounded Caption Error Verification and Localization

model-releasesarxiv-cs-cl

arXiv:2606.26923v1 Announce Type: new Abstract: Vision-language models (VLMs) often produce hallucinated or inconsistent outputs, where text and images are not properly aligned. Addressing this issue

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Safety

Governing Actions, Not Agents: Institutional Attestation as a Governance Model for Autonomous AI Systems

DGX agent

arXiv:2606.26298v1 Announce Type: new Abstract: Autonomous AI agents may begin to perform consequential, irreversible actions such as clinical prescribing and production software deployment. This pape

safetyarxiv-cs-ai

26 Jun 2026

HauntAttack: When Attack Follows Reasoning as a Shadow

arXiv:2506.07031v5 Announce Type: replace-cross Abstract: Emerging Large Reasoning Models (LRMs) consistently excel in mathematical and reasoning tasks, showcasing remarkable capabilities. However, th

Helpfulness Hurts: Domain-Dependent Degradation of Mid-Trained Compassion Values Under Post-Training

arXiv:2606.26102v1 Announce Type: cross Abstract: Standard post-training pipelines apply supervised fine-tuning (SFT) and reinforcement learning (RL) to make language models helpful, but these process

HierBias: Context-Conditioned Hierarchical Media Bias Detection with Multi-Task Type Classification

arXiv:2606.26100v1 Announce Type: new Abstract: Media bias detection is a critical task for ensuring fair and balanced information dissemination, yet existing sentence-level approaches classify each s

safetyarxiv-cs-cl

hisao{}: A GPU-Native Parallel Optimizer for Multimodal Black-Box Functions via Convergence-Anticonvergence Oscillation

model-releasesarxiv-cs-lg

arXiv:2606.26164v1 Announce Type: new Abstract: Finding all modes of a multimodal black-box function is a fundamental challenge in optimization, Bayesian inference, and scientific computing. Existing

How Surprising Is Historical Italian to Language Models? Tokenization Tax, Comprehension Tax, and a Simple Mitigation

arXiv:2606.27275v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly critical to digital library workflows, yet their ability to process historical language remains poorly und

applicationsarxiv-cs-cl

I can personally attest: OpenClaude using GLM 5.2 is now performing on par with Claude Code powered by Opus 4.8.

model-releasesclem-delangue--x

I cannot verify the claims in this post as the URL format appears invalid and the specific version numbers (GLM 5.2, Claude Code/Opus 4.8) don't correspond to publicly documented model releases as of

Identifying the Unknown: Prompt-Free Open Vocabulary Anomaly Recognition for Robot-Object Interaction

arXiv:2606.26829v1 Announce Type: new Abstract: Robots operating in real-world environments must in general be able to recognize previously unseen objects. As robotic systems move toward open-world au

applicationsarxiv-cs-cv

Investigating LLM's Problem Solving Capability -- a Study on Statics Questions

arXiv:2606.26103v1 Announce Type: cross Abstract: Large Language Models (LLMs) have rapidly influenced many aspects of society, particularly education, due to their demonstrated ability to complete as

applicationsarxiv-cs-ai

Joint Reward Modeling: Internalizing Chain-of-Thought for Efficient Visual Reward Models

arXiv:2602.07533v2 Announce Type: replace Abstract: Reward models are critical for reinforcement learning from human feedback, as they determine the alignment quality and reliability of generative mod

local-aiarxiv-cs-ai

KG-TRACE: A Neuro-Symbolic Framework for Mechanistic Grounding in Antimicrobial Resistance Prediction

arXiv:2606.26179v1 Announce Type: cross Abstract: While WGS-based AMR prediction has reached high accuracy, existing models lack a mechanism to ground neural attributions in established biological pat

Agents

Lacuna: A Research Map for Machine Learning

arXiv:2606.26246v1 Announce Type: cross Abstract: Lacuna is a research map for machine learning that uses LLMs to turn papers and scholarly metadata into markdown summaries, concept elements, research

agentsarxiv-cs-ai

Language-Based Digital Twins for Elderly Cognitive Assistance

arXiv:2606.27334v1 Announce Type: new Abstract: Digital twins have emerged as a promising paradigm for personalized healthcare, enabling modeling of individual behavior and health trajectories. In cog

applicationsarxiv-cs-ai

Latent-Mark: An Audio Watermark Robust to Neural Codec Compression

arXiv:2603.05310v3 Announce Type: replace-cross Abstract: While existing audio watermarking techniques have achieved strong robustness against traditional digital signal processing (DSP) attacks, they

researcharxiv-cs-ai

LCG: Long-Context Consistent Image Generation with Sparse Relational Attention

arXiv:2606.26171v1 Announce Type: cross Abstract: Recent image generation models achieve impressive quality in single-image synthesis, but often fail to maintain consistency across sequential outputs,

Learning Adversarial Augmentation Policies for Robust Garlic Seedling Detection

arXiv:2606.26828v1 Announce Type: new Abstract: Accurate seedling detection during early growth stages is essential for timely replanting and effective crop management in precision agriculture. Howeve

local-aiarxiv-cs-cv

Learning to Select Maximum Clique Algorithms: From Traditional Machine Learning to a Dual-Channel Hybrid Neural Architecture

arXiv:2508.08005v4 Announce Type: replace-cross Abstract: The Maximum Clique Problem (MCP) is an NP-hard problem with wide-ranging applications in fields such as bioinformatics, network science, and s

Life After Benchmark Saturation: A Case Study of CORE-Bench

arXiv:2606.26158v1 Announce Type: new Abstract: When a benchmark's accuracy saturates, it is often retired and replaced with a more challenging version. We show that this approach privileges accuracy

LiMoDE: Rethinking Lifelong Robot Manipulation from a Mixture-of-Dynamic-Experts Perspective

arXiv:2606.26183v1 Announce Type: cross Abstract: Building a generalist robot that can leverage prior knowledge for continuous task adaptation remains a significant challenge. Previous works alleviate

Linguistics and Human Brain: A Perspective of Computational Neuroscience

arXiv:2602.08275v3 Announce Type: replace-cross Abstract: Elucidating the language-brain relationship requires bridging the methodological gap between the abstract theoretical frameworks of linguistic

safetyarxiv-cs-cl

LiveEdit: Towards Real-Time Diffusion-Based Streaming Video Editing

model-releasesarxiv-cs-cv

arXiv:2606.26740v1 Announce Type: new Abstract: Streaming video editing has made rapid progress, yet practical deployment is still limited by two core issues: maintaining stable backgrounds and non-ed

LLM-Based Examination of Eligibility Criteria from Securities Prospectuses at the German Central Bank

arXiv:2606.27316v1 Announce Type: new Abstract: Verifying the eligibility of securities as collateral is a key responsibility of the German Central Bank. However, manually verifying these assets again

applicationsarxiv-cs-cl

LLM-based Models for Detecting Emerging Topics in Service Feedback

arXiv:2606.26595v1 Announce Type: new Abstract: Enhancing the analysis of service feedback is essential for public sector organizations, particularly tax administrations, where trust and compliance de

LMs as Task-Specific Knowledge Bases: An Interpretability Analysis

model-releasesarxiv-cs-cl

arXiv:2606.27237v1 Announce Type: new Abstract: Language models (LMs) capture large amounts of factual knowledge applicable to a wide range of tasks, motivating the view of their parameters as a knowl

Memory Depth, Not Memory Access: Selective Parametric Consolidation for Long-Running Language Agents

arXiv:2606.26806v1 Announce Type: new Abstract: Long-running language agents need more than memory access. Retrieval systems can fetch past facts at query time, but they do not decide which experience

Mesh-RL: Coupled subgrid reinforcement learning

arXiv:2606.26333v1 Announce Type: new Abstract: Reinforcement learning in large or sparse-reward environments suffers from slow temporal-difference reward propagation, as value information spreads onl

local-aiarxiv-cs-lg

Methane-Plume Segmentation From Hyperspectral Satellite Imagery Via Multimodal Deep Learning

arXiv:2606.26416v1 Announce Type: new Abstract: Efficient detection of methane plumes is crucial for understanding and mitigating global warming, as accurately identifying and segmenting them in earth

applicationsarxiv-cs-cv

Tutorials

Modeling Local, Global, and Cross-Modal Context in Multimodal 3D MRI

arXiv:2606.26894v1 Announce Type: new Abstract: Brain MRI poses a fundamental challenge for machine learning: models must learn from high-dimensional 3D data spanning multiple co-registered modalities

tutorialsarxiv-cs-cv

MPC-Injection: Biasing Off-Policy Locomotion RL Toward Controller-Induced Behavior Basins

arXiv:2606.26392v1 Announce Type: new Abstract: Reinforcement learning (RL) for locomotion frequently converges to locally optimal but undeployable behaviors, such as vibrating limbs or scooting on th

local-aiarxiv-cs-ro

Multilingual Reasoning Cascades Need More Context

arXiv:2606.27306v1 Announce Type: new Abstract: Translation cascades for reasoning translate the query from another language to English, reason in English, and translate the answer back to the origina

researcharxiv-cs-cl

NavIsaacLab: Generating Realistic Crowd via Parallel Robot Learning for Benchmarking Human-aware Navigation

model-releasesarxiv-cs-ro

arXiv:2606.26265v1 Announce Type: new Abstract: Robot autonomous navigation that accounts for surrounding human activities is crucial for ensuring both safety and natural human-robot interaction in re

Hardware

Otter Weather: Skillful and Computationally Efficient Medium-Range Weather Forecasting

arXiv:2606.26421v1 Announce Type: new Abstract: State-of-the-art medium-range AI weather models can outperform traditional Numerical Weather Prediction (NWP) but require massive training budgets. This

hardwarearxiv-cs-lg

Parametric Generalized Adaptive Moment Features (PG-AMF) for Bearing Fault Diagnosis and Machine Health Monitoring

arXiv:2606.26317v1 Announce Type: cross Abstract: Accurate fault diagnosis of rolling element bearings in rotating machinery is considered essential for ensuring industrial safety and enabling predict

Paved with True Intents: Intent-Aware Training Improves LLM Safety Classification Across Training Regimes

arXiv:2606.27210v1 Announce Type: new Abstract: We argue that safety classifiers should model user intent as an explicit signal between the prompt and the final label. To study this, we introduce AIMS

safetyarxiv-cs-cl

Perception, Verdict, and Evolution: Hindsight-Driven Self-Refining Forensics Agent for AI-Generated Image Detection

arXiv:2606.26552v1 Announce Type: cross Abstract: The rapid advancement of generative models presents a significant challenge to existing deepfake detection methods, particularly given the widespread

PhyEditBench: A Real-World Multi-Stage Benchmark for Physics-Aware Image Editing

model-releasesarxiv-cs-cv

arXiv:2606.26551v1 Announce Type: new Abstract: While instruction-based image editing, enabled by multi-modal generative models, has advanced significantly, existing benchmarks lack a comprehensive ev

PlanRL: A Trajectory Planning Architecture for Reinforcement Learning-based Driving Experts

arXiv:2606.26858v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a prominent framework for developing driving experts in autonomous vehicles. However, most existing RL-based expe

safetyarxiv-cs-ro

Probabilistic NDVI Forecasting from Sparse Satellite Time Series and Weather Covariates

arXiv:2602.17683v3 Announce Type: replace-cross Abstract: Short-term forecasting of vegetation dynamics is a key enabler for data-driven decision support in precision agriculture. Normalized Differenc

researcharxiv-cs-cv

Prompt Injection in Automated Resume Screening with Large Language Models: Single and Multi-Injection Settings

arXiv:2606.27287v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to screen and rank job applicants, creating incentives for candidates to strategically manipulate alg

Pseudo-Text-Conditioned 3D Grounding DINO for Organ Localization in Abdominal CT

arXiv:2606.27084v1 Announce Type: new Abstract: Reliable organ localization in abdominal CT can provide spatial priors for downstream trauma analysis. We propose CT-3GDINO, a lightweight 3D detector t

local-aiarxiv-cs-cv

Qwen-Image-Agent: Bridging the Context Gap in Real-World Image Generation

model-releasesarxiv-cs-cv

arXiv:2606.26907v1 Announce Type: new Abstract: While text-to-image (T2I) models have achieved remarkable progress, they struggle with real-world requests that are often underspecified, implicit, or d

ReasonCLIP-58M: Visually Grounded Commonsense Reasoning Supervision for CLIP

arXiv:2606.26794v1 Announce Type: cross Abstract: CLIP and its variants are widely adopted visual backbones in multimodal systems, but their pretraining remains dominated by descriptive image-text ali

Reasoning Quality Emerges Early: Data Curation for Reasoning Models

arXiv:2606.26797v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) on a small, high-quality set of long reasoning traces is an effective approach for eliciting strong reasoning capabilities

researcharxiv-cs-lg

RedVox: Safety and Fairness Gaps in Speech Models Across Languages

model-releasesarxiv-cs-cl

arXiv:2606.26968v1 Announce Type: new Abstract: Speech-capable models are increasingly deployed in real-world applications across languages. Yet their safety and fairness beyond English settings and u

Reinforcement Fine-Tuning of Flow-Matching Policies for Vision-Language-Action Models

model-releasesarxiv-cs-lg

arXiv:2510.09976v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models such as OpenVLA, Octo, and pi_0 have shown strong generalization by leveraging large-scale demonstrations, yet t

Reinforcement Learning without Ground-Truth Solutions can Improve LLMs

model-releasesarxiv-cs-lg

arXiv:2606.27369v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) for training LLMs typically rely on ground-truth answers to assign rewards, limiting their applica

Rendering Novel Views of MRI Using 3D Gaussian Splatting

arXiv:2606.26236v1 Announce Type: cross Abstract: The objective of this paper is to improve radiological gradings measured on MRIs of spines, by resampling scans so that the new view planes are better

researcharxiv-cs-cv