Search: “evaluation”

Mesh Based Simulations with Spatial and Temporal awareness

arXiv:2605.01542v1 Announce Type: new Abstract: Machine Learning surrogates for Computational Fluid Dynamics (CFD), particularly Graph Neural Networks (GNNs) and Transformers, have become a new import

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Metric Unreliability in Multimodal Machine Unlearning: A Systematic Analysis and Principled Unified Score

DGX agent

arXiv:2605.02206v1 Announce Type: new Abstract: Machine unlearning in Vision-Language Models (VLMs) is required for compliance with the General Data Protection Regulation (GDPR), yet current evaluatio

model-releasesarxiv-cs-cv

5 May 2026

Minimal, Local, Causal Explanations for Jailbreak Success in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2605.00123v1 Announce Type: new Abstract: Safety trained large language models (LLMs) can often be induced to answer harmful requests through jailbreak prompts. Because we lack a robust understa

Mitigating Multimodal LLMs Hallucinations via Relevance Propagation at Inference Time

arXiv:2605.01766v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have revolutionized the landscape of AI, demonstrating impressive capabilities in tackling complex vision and

Model Merging: Foundations and Algorithms

arXiv:2605.01580v1 Announce Type: new Abstract: Modern deep learning usually treats models as separate artifacts: trained independently, specialized for particular purposes, and replaced when improved

Model Organisms Are Leaky: Perplexity Differencing Often Reveals Finetuning Objectives

arXiv:2605.00994v1 Announce Type: new Abstract: Finetuning can significantly modify the behavior of large language models, including introducing harmful or unsafe behaviors. To study these risks, rese

researcharxiv-cs-cl

Molecular Representations for Large Language Models

arXiv:2605.01822v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly being used to support scientific discovery. In chemistry, tasks such as reaction prediction and structure

MooD: An Efficient VA-Driven Affective Image Editing Framework via Fine-Grained Semantic Control

arXiv:2605.02521v1 Announce Type: new Abstract: Affective image editing (AIE) aims to edit visual content to evoke target emotions. However, existing methods often overlook inference efficiency and pr

MorphIt: Flexible Spherical Approximation of Robot Morphology for Representation-driven Adaptation

model-releasesarxiv-cs-ro

arXiv:2507.14061v2 Announce Type: replace Abstract: What if a robot could rethink its own morphological representation to better meet the demands of diverse tasks? Most robotic systems today treat the

MOSAIC: Multi-agent Orchestration for Task-Intelligent Scientific Coding

arXiv:2510.08804v3 Announce Type: replace Abstract: We present MOSAIC, a multi-agent Large Language Model (LLM) framework for solving challenging scientific coding tasks. Unlike general-purpose coding

MPCS: Neuroplastic Continual Learning via Multi-Component Plasticity and Topology-Aware EWC

arXiv:2605.02509v1 Announce Type: new Abstract: Continual learning systems face a fundamental tension between plasticity -- acquiring new knowledge -- and stability -- retaining prior knowledge. We in

MSMixer: Learned Multi-Scale Temporal Mixing with Complementary Linear Shortcut for Long-Term Time Series Forecasting

arXiv:2605.02689v1 Announce Type: new Abstract: Long-term time series forecasting requires models that simultaneously capture rapid oscillations, medium-range periodicities, and slowly evolving macro-

Multi-Dataset Cross-Domain Knowledge Distillation for Unified Medical Image Segmentation, Classification, and Detection

arXiv:2605.01563v1 Announce Type: new Abstract: We propose a unified cross-domain transfer learning framework that leverages knowledge from multiple heterogeneous medical imaging datasets to improve p

Multi-Perspective Transformers in ARC-AGI-2 Challenge

arXiv:2605.01154v1 Announce Type: new Abstract: ARC-AGI-2 is a benchmark of human-intuitive visual puzzles that measures a machine's ability to generalize from limited examples, interpret symbolic mea

Multi-Rater Calibrated Segmentation Models

arXiv:2605.02437v1 Announce Type: new Abstract: Objective: Accurate probability estimates are essential for the safe deployment of medical image segmentation models in clinical decision-making. Howeve

MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction

arXiv:2602.03668v2 Announce Type: replace-cross Abstract: Latent actions learned from diverse human videos serve as pseudo-labels for vision-language-action (VLA) pretraining, but provide effective su

Agents

Neural Backward Reach-Avoid Tubes with MPC Supervision for High-Dimensional Systems: An Application to Safe Spacecraft Docking

arXiv:2605.02021v1 Announce Type: new Abstract: Autonomous spacecraft docking requires control policies that simultaneously ensure collision avoidance and target reachability under coupled, high-dimen

agentsarxiv-cs-ro

Noise Steering for Controlled Text Generation: Improving Diversity and Reading-Level Fidelity in Arabic Educational Story Generation

arXiv:2604.03380v2 Announce Type: replace Abstract: Generating diverse, pedagogically valid stories for Arabic early-grade reading assessments requires balancing tight constraints on vocabulary, readi

researcharxiv-cs-cl

NTIRE 2026 Challenge on Efficient Low Light Image Enhancement: Methods and Results

arXiv:2605.02212v1 Announce Type: new Abstract: This paper presents a comprehensive review of the NITRE 2026 Efficient Low Light Image Enhancement (E-LLIE) Challenge, highlighting the proposed solutio

Object-Level Explanations for Image Geolocation Models: a GeoGuessr use-case

arXiv:2605.00912v1 Announce Type: new Abstract: When humans play geolocation games such as GeoGuessr, they rely on concrete visual cues, such as road markings, vegetation, or architectural details, to

OceanPile: A Large-Scale Multimodal Ocean Corpus for Foundation Models

arXiv:2605.00877v1 Announce Type: cross Abstract: The vast and underexplored ocean plays a critical role in regulating global climate and supporting marine biodiversity, yet artificial intelligence ha

Omni-Fake: Benchmarking Unified Multimodal Social Media Deepfake Detection

arXiv:2605.01638v1 Announce Type: new Abstract: Multimodal deepfakes are proliferating on social media and threaten authenticity, information integrity, and digital forensics. Existing benchmarks are

OmniTrack++: Omnidirectional Multi-Object Tracking by Learning Large-FoV Trajectory Feedback

arXiv:2511.00510v2 Announce Type: replace Abstract: To address panoramic distortion, large search space, and identity ambiguity under a 360{eg} FoV, OmniTrack++ adopts a feedback-driven framework that

Safety

Online Safety Filter for Deformable Object Manipulation with Horizon Agnostic Neural Operators

arXiv:2605.01069v1 Announce Type: new Abstract: Safety critical control of robotic manipulation tasks involving deformable media such as fluids, cloth, and soft objects remains challenging because exi

safetyarxiv-cs-ro

Local Ai

Open-access model for detecting openly dumped dispersed municipal solid waste from crowdsourced UAV imagery in Sub-Saharan Africa

arXiv:2605.02316v1 Announce Type: new Abstract: Managing municipal solid waste in rapidly urbanizing Sub-Saharan Africa remains challenging due to dispersed informal dumping and limited high-resolutio

local-aiarxiv-cs-cv

OpenAI claims ChatGPT’s new default model hallucinates way less

model-releasesthe-verge-ai

OpenAI's newest default model for ChatGPT might not make stuff up as much. Hallucinations have been an ongoing problem for AI models, but OpenAI says its new GPT-5.5 Instant model has 'significant imp

OpenAI GPT-5 System Card

arXiv:2601.03267v2 Announce Type: replace Abstract: This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers

Agents

Optimized and kinematically feasible multi-agent motion planning

arXiv:2605.01996v1 Announce Type: new Abstract: Multi-agent motion planning (MAMP) is an important problem for autonomous systems with multiple agents. In this work we propose a two-step method for fi

agentsarxiv-cs-ro

Orchestrating Spatial Semantics via a Zone-Graph Paradigm for Intricate Indoor Scene Generation

model-releasesarxiv-cs-ro

arXiv:2605.02537v1 Announce Type: new Abstract: Autonomous 3D indoor scene synthesis breaks down in non-convex rooms with tightly coupled spatial constraints. Data-driven generators lack topological p

P3-LLM: An Integrated NPU-PIM Accelerator for Edge LLM Inference Using Hybrid Numerical Formats

arXiv:2511.06838v4 Announce Type: replace-cross Abstract: The substantial memory bandwidth and computational demands of large language models (LLMs) present critical challenges for efficient inference

Page image classification for content-specific data processing

arXiv:2507.21114v3 Announce Type: replace-cross Abstract: Digitization projects in humanities often generate vast quantities of page images from historical documents, presenting significant challenges

Pair2Score: Pairwise-to-Absolute Transfer for LLM-Based Essay Scoring

arXiv:2605.02069v1 Announce Type: new Abstract: Many scoring applications require absolute predictions, while pairwise comparisons can provide a simpler learning objective. We present Pair2Score, a tw

Applications

PanDORA: Casual HDR Radiance Acquisition of Indoor Scenes for Image-based Lighting

arXiv:2407.06150v3 Announce Type: replace Abstract: Most novel view synthesis methods -- including Neural Radiance Fields (NeRF) -- struggle to capture the high dynamic range (HDR) radiance required f

applicationsarxiv-cs-cv

Safety

Patient-Specific Optimization for Mandibular Reconstruction Planning with Enhanced Bone Union

arXiv:2605.01084v1 Announce Type: new Abstract: Mandibular reconstruction with vascularized bone grafts is complicated by donor-host nonunion, and current virtual surgical planning produces a geometri

safetyarxiv-cs-cv

Applications

Pedagogical Promise and Peril of AI: A Text Mining Analysis of ChatGPT Research Discussions in Programming Education

arXiv:2605.00361v1 Announce Type: cross Abstract: GenAI systems such as ChatGPT are increasingly discussed in programming education, but the ways in which the research literature conceptualizes and fr

applicationsarxiv-cs-ai

Perturbation Dose Responses in Recursive LLM Loops: Raw Switching, Stochastic Floors, and Persistent Escape under Append, Replace, and Dialog Updates

arXiv:2605.02236v1 Announce Type: cross Abstract: Recursive language-model loops often settle into recognizable attractor-like patterns. The practical question is how much injected text is needed to m

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models

arXiv:2605.01185v1 Announce Type: new Abstract: Accelerated magnetic resonance imaging (MRI) enabled by the training of deep learning (DL)-based image recon. models requires large and diverse raw k-sp

Physics-Informed Neural Learning for State Reconstruction and Parameter Identification in Coupled Greenhouse Climate Dynamics

arXiv:2605.02524v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have recently emerged as a promising framework for integrating data-driven learning with physical knowledge. In

Tutorials

PiCSRL: Physics-Informed Contextual Spectral Reinforcement Learning

arXiv:2603.26816v2 Announce Type: replace Abstract: High-dimensional low-sample-size (HDLSS) datasets constrain reliable environmental model development, where labeled data remain sparse. Reinforcemen

tutorialsarxiv-cs-lg

Pretraining on Sleep Data Improves non-Sleep Biosignal Tasks

arXiv:2605.02500v1 Announce Type: new Abstract: Sleep foundation models have recently demonstrated strong performance on in-domain polysomnography tasks, including sleep staging, apnea detection, and

Progress Ratio Embeddings: An Impatience Signal for Robust Length Control in Neural Text Generation

arXiv:2512.06938v2 Announce Type: replace Abstract: Modern neural language models achieve high accuracy in text generation, yet precise control over generation length remains underdeveloped. In this p

researcharxiv-cs-cl

Projection-Free Transformers via Gaussian Kernel Attention

arXiv:2605.02144v1 Announce Type: new Abstract: Self-attention in Transformers is typically implemented as softmax(QK^op/sqrt{d})V, where Q=XW_Q, K=XW_K, and V=XW_V are learned linear projections of t

RADMI: Latent Information Aggregation as a Proxy for Model Uncertainty

arXiv:2605.01502v1 Announce Type: new Abstract: Epistemic uncertainty estimation is essential for identifying regions where deep learning system outputs may be unreliable. However, existing approaches

Random-Effects Algorithm for Random Objects in Metric Spaces

arXiv:2605.02693v1 Announce Type: cross Abstract: Across many scientific disciplines, multiple observations are collected from the same experimental units, and in modern datasets these observations of

Safety

RECAP: Transparent Inference-Time Emotion Alignment for Medical Dialogue Systems

arXiv:2509.10746v3 Announce Type: replace Abstract: Large language models in healthcare often produce emotionally flat or opaque responses, failing to provide the transparent reasoning required for cl

safetyarxiv-cs-cl

Recurrent Deep Reinforcement Learning for Chemotherapy Control under Partial Observability

arXiv:2605.02552v1 Announce Type: new Abstract: Chemotherapy dose optimization can be formulated as a dynamic treatment regime, requiring sequential decisions under uncertainty that must balance tumor

Reference-Sampled Boltzmann Projection for KL-Regularized RLVR: Target-Matched Weighted SFT, Finite One-Shot Gaps, and Policy Mirror Descent

arXiv:2605.02469v1 Announce Type: new Abstract: Online reinforcement learning with verifiable rewards (RLVR) turns checkable outcomes into a scalable training signal, but it keeps rollout generation,

RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs

arXiv:2605.01913v1 Announce Type: cross Abstract: Fine-tuning safety-aligned language models for downstream tasks often leads to substantial degradation of refusal behavior, making models vulnerable t