Search: “evaluation”

Low-Rank Adapters Initialization via Gradient Surgery for Continual Learning

model-releasesarxiv-cs-lg

arXiv:2605.12752v1 Announce Type: new Abstract: LoRA is widely adopted for continual fine-tuning of Large Language Models due to its parameter efficiency, modularity across tasks, and compatibility wi

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M2Retinexformer: Multi-Modal Retinexformer for Low-Light Image Enhancement

DGX agent

arXiv:2605.12556v1 Announce Type: new Abstract: Low-light image enhancement is challenging due to complex degradations, including amplified noise, artifacts, and color distortion. While Retinex-based

researcharxiv-cs-cv

14 May 2026

Machine Learning-Driven Multimodal Spectroscopic Liquid Biopsy for Early Multicancer Detection

arXiv:2605.13218v1 Announce Type: new Abstract: Cancer is one of the leading causes of death worldwide, making the development of rapid, minimally invasive, label-free and scalable diagnostic strategi

Manipulation Planning for Construction Activities with Repetitive Tasks

arXiv:2605.13754v1 Announce Type: new Abstract: In this paper, we study the problem of manipulation skill acquisition for performing construction activities consisting of repetitive tasks (e.g., build

researcharxiv-cs-ro

Mechanism Plausibility in Generative Agent-Based Modeling

arXiv:2605.12824v1 Announce Type: cross Abstract: Large language models (LLMs) can generate high-level diverse phenomena without explicitly programmed rules. This capability has led to their adoption

agentsarxiv-cs-ai

Tutorials

Min Generalized Sliced Gromov Wasserstein: A Scalable Path to Gromov Wasserstein

arXiv:2605.13753v1 Announce Type: cross Abstract: We propose min Generalized Sliced Gromov--Wasserstein (min-GSGW), a sliced formulation for the Gromov--Wasserstein (GW) problem using expressive gener

tutorialsarxiv-cs-cv

Mind the Gap: How Elicitation Protocols Shape the Stated-Revealed Preference Gap in Language Models

arXiv:2601.21975v2 Announce Type: replace Abstract: Recent work identifies a stated-revealed (SvR) preference gap in language models (LMs): a mismatch between the values models endorse and the choices

MinT: Managed Infrastructure for Training and Serving Millions of LLMs

arXiv:2605.13779v1 Announce Type: cross Abstract: We present MindLab Toolkit (MinT), a managed infrastructure system for Low-Rank Adaptation (LoRA) post-training and online serving. MinT targets a set

MMSkills: Towards Multimodal Skills for General Visual Agents

arXiv:2605.13527v1 Announce Type: new Abstract: Reusable skills have become a core substrate for improving agent capabilities, yet most existing skill packages encode reusable behavior primarily as te

agentsarxiv-cs-ai

Moltbook Moderation: Uncovering Hidden Intent Through Multi-Turn Dialogue

arXiv:2605.12856v1 Announce Type: new Abstract: The emergence of multi-agent systems introduces novel moderation challenges that extend beyond content filtering. Agents with {em malicious intent} may

agentsarxiv-cs-ai

MPINeuralODE: Multiple-Initial-Condition Physics-Informed Neural ODEs for Globally Consistent Dynamical System Learning

arXiv:2605.13305v1 Announce Type: new Abstract: Neural ordinary differential equations (Neural ODEs) often fit training trajectories while generalizing poorly to unseen initial conditions and long hor

Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization

arXiv:2605.13641v1 Announce Type: new Abstract: Complex reinforcement learning environments frequently employ multi-task and mixed-reward formulations. In these settings, heterogeneous reward distribu

Tutorials

Multimodal Graph-based Classification of Esophageal Motility Disorders

arXiv:2605.13623v1 Announce Type: new Abstract: Diagnosing esophageal motility disorders pose significant challenges due to the complexity of high-resolution impedance manometry (HRIM) data and variab

tutorialsarxiv-cs-lg

Multimodal Hidden Markov Models for Persistent Emotional State Tracking

arXiv:2605.12838v1 Announce Type: new Abstract: Tracking an interpretable emotional arc of a conversation via the sentiment of individual utterances processed as a whole is central to both understandi

NeuroRisk: Physics-Informed Neural Optimization for Risk-Aware Traffic Engineering

arXiv:2605.12862v1 Announce Type: cross Abstract: In production Wide-Area Networks (WANs), correlated failures dominate availability losses, forcing operators to reserve large safety margins that leav

Neurosymbolic Auditing of Natural-Language Software Requirements

arXiv:2605.13817v1 Announce Type: cross Abstract: Natural-language software requirements are often ambiguous, inconsistent, and underspecified; in safety-critical domains, these defects propagate into

Object Manipulation of the Variable Topology Truss system

arXiv:2605.13086v1 Announce Type: new Abstract: This paper presents an object manipulation strategy for the Variable Topology Truss (VTT) system, a truss robot that comprises actuated truss members co

researcharxiv-cs-ro

okay okay, hillclimbing agent in the background. love it. great job @hwchase17 @Vtrivedy10 and team.

okay okay, hillclimbing agent in the background. love it. great job @hwchase17 @Vtrivedy10 and team. 🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs i

agentsharrison-chase--x

OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation

model-releasesarxiv-cs-cv

arXiv:2605.13815v1 Announce Type: new Abstract: LiDAR scene generation is increasingly important for scalable simulation and synthetic data creation, especially under diverse sensing conditions that a

On Hallucinations in Inverse Problems: Fundamental Limits and Provable Assessment Methods

arXiv:2605.13146v1 Announce Type: cross Abstract: Artificial intelligence (AI) has transformed imaging inverse problems, from medical diagnostics to Earth observation. Yet deep neural networks can pro

researcharxiv-cs-cv

Optimization in Sparse 2D to Dense 3D Weakly Supervised Learning: Application to Multi-Label Segmentation of Large ex vivo MRI Data

arXiv:2605.12753v1 Announce Type: cross Abstract: INTRODUCTION | Fully supervised 3D segmentation of high-resolution ex vivo MRI is limited by the prohibitive cost of volumetric annotation, forcing re

researcharxiv-cs-cv

PanoWorld: Towards Spatial Supersensing in 360^irc Panorama World

arXiv:2605.13169v1 Announce Type: cross Abstract: Multimodal large laboratory models (MLLMs) still struggle with spatial understanding under the dominant perspective-image paradigm, which inherits the

Pareto-Guided Optimal Transport for Multi-Reward Alignment

arXiv:2605.13155v1 Announce Type: new Abstract: Text-to-image generation models have achieved remarkable progress in preference optimization, yet achieving robust alignment across diverse reward model

safetyarxiv-cs-cv

PERCEIVE: A Benchmark for Personalized Emotion and Communication Behavior Understanding on Social Media

arXiv:2605.12525v1 Announce Type: cross Abstract: Current emotion analysis in social media is predominantly author-centric, failing to capture the subjective nature of emotional responses across diver

Persona-Model Collapse in Emergent Misalignment

arXiv:2605.12850v1 Announce Type: cross Abstract: Fine-tuning large language models on narrow data with harmful content produces broadly misaligned behavior on unrelated prompts, a phenomenon known as

Physics Guided Generative Optimization for Trotter Suzuki Decomposition

arXiv:2605.13268v1 Announce Type: cross Abstract: Product formulas for Trotter Suzuki simulation remain a practical route to Hamiltonian evolution on noisy intermediate scale quantum (NISQ) hardware,

Pitfalls of Unlabeled Disagreement-Based Drift Detection in Streaming Tree Ensembles

model-releasesarxiv-cs-lg

arXiv:2605.12803v1 Announce Type: new Abstract: Detecting concept drift in high-speed data streams remains challenging, particularly when models must operate on unlabeled data and avoid false alarms c

Plan Before You Trade: Inference-Time Optimization for RL Trading Agents

arXiv:2605.12653v1 Announce Type: cross Abstract: Reinforcement learning agents for portfolio management are typically trained and deployed as static policies, with no mechanism for using price foreca

Position: Assistive Agents Need Accessibility Alignment

arXiv:2605.13579v1 Announce Type: new Abstract: Assistive agents for Blind and Visually Impaired (BVI) users require accessibility alignment as a first-class design objective. Despite rapid progress i

Potential and challenges of generative adversarial networks for super-resolution in 4D Flow MRI

arXiv:2508.14950v2 Announce Type: replace-cross Abstract: 4D Flow Magnetic Resonance Imaging (4D Flow MRI) enables non-invasive quantification of blood flow and hemodynamic parameters. However, its cl

PRA-PoE: Robust Alzheimer's Diagnosis with Arbitrary Missing Modalities

arXiv:2605.13081v1 Announce Type: new Abstract: Missing modalities are prevalent in real-world Alzheimer's disease (AD) assessment and pose a significant challenge to multimodal learning, particularly

safetyarxiv-cs-cv

Pretraining Language Models with Subword Regularization: An Empirical Study of BPE Dropout in Low-Resource NLP

arXiv:2605.13436v1 Announce Type: cross Abstract: Subword regularization methods such as BPE dropout are typically applied only during fine-tuning, while pretraining is usually done with deterministic

Local Ai

PROMETHEUS: Automating Deep Causal Research Integrating Text, Data and Models

arXiv:2605.12835v1 Announce Type: new Abstract: Large language models can extract local causal claims from text, but those claims become more useful when organized as persistent, navigable world model

local-aiarxiv-cs-ai

Proximal-Based Generative Modeling for Bayesian Inverse Problems

arXiv:2605.13278v1 Announce Type: cross Abstract: Score-based diffusion models demonstrate superior performance in generative tasks but encounter fundamental bottlenecks in inverse problems due to the

Q-Flow: Stable and Expressive Reinforcement Learning with Flow-Based Policy

arXiv:2605.13435v1 Announce Type: cross Abstract: There is growing interest in utilizing flow-based models as decision-making policies in reinforcement learning due to their high expressive capacity.

QLAM: A Quantum Long-Attention Memory Approach to Long-Sequence Token Modeling

arXiv:2605.13833v1 Announce Type: cross Abstract: Modeling long-range dependencies in sequential data remains a central challenge in machine learning. Transformers address this challenge through atten

researcharxiv-cs-cv

QSMOTE-PGM/kPGM: QSMOTE Based PGM and kPGM for Imbalanced Dataset Classification

arXiv:2512.16960v2 Announce Type: replace Abstract: Quantum-inspired machine learning (QiML) employs mathematical principles from quantum theory, such as Hilbert-space representations and quantum stat

Quantifying Sensitivity for Tree Ensembles: A symbolic and compositional approach

arXiv:2605.13830v1 Announce Type: new Abstract: Decision tree ensembles (DTE) are a popular model for a wide range of AI classification tasks, used in multiple safety critical domains, and hence verif

RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation

arXiv:2605.13542v1 Announce Type: new Abstract: Intensive care units (ICU) generate long, dense and evolving streams of clinical information, where physicians must repeatedly reassess patient states u

Reframing preprocessing selection as model-internal calibration in near-infrared spectroscopy: A large-scale benchmark of operator-adaptive PLS and Ridge models

model-releasesarxiv-cs-lg

arXiv:2605.13587v1 Announce Type: cross Abstract: Near-infrared spectroscopy (NIRS) is rapid and non-destructive, but reliable calibration still depends heavily on spectral preprocessing. In routine p

Repurposing Image Diffusion Models for Training-Free Music Style Transfer on Mel-spectrograms

arXiv:2411.15913v4 Announce Type: replace-cross Abstract: Music style transfer blends source structure with reference style to enable personalized music creation. However, existing zero-shot methods o

Local Ai

Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle

arXiv:2605.13021v1 Announce Type: cross Abstract: Graph coarsening is a graph dimensionality reduction technique that aims to construct a smaller and more tractable graph while preserving the essentia

local-aiarxiv-cs-ai

Revisiting Reinforcement Learning with Verifiable Rewards from a Contrastive Perspective

arXiv:2605.12969v1 Announce Type: cross Abstract: RLVR has become a widely adopted paradigm for improving LLMs' reasoning capabilities, and GRPO is one of its most representative algorithms. In this p

Applications

Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations

arXiv:2507.00990v3 Announce Type: replace-cross Abstract: This work introduces Robots Imitating Generated Videos (RIGVid), a system that enables robots to perform complex manipulation tasks--such as p

applicationsarxiv-cs-ai

Robust and Explainable Bicuspid Aortic Valve Diagnosis Using Stacked Ensembles on Echocardiography

arXiv:2605.13730v1 Announce Type: cross Abstract: Transthoracic echocardiography (TTE) is the first-line imaging modality for diagnosing bicuspid aortic valve (BAV), yet diagnostic performance varies

RS-Claw: Progressive Active Tool Exploration via Hierarchical Skill Trees for Remote Sensing Agents

arXiv:2605.13391v1 Announce Type: new Abstract: The rise of multi-modal large language models (MLLMs) is shifting remote sensing (RS) intelligence from 'see' to 'action', as OpenClaw-style frameworks

Sampling from Flow Language Models via Marginal-Conditioned Bridges

arXiv:2605.13681v1 Announce Type: new Abstract: Flow Language Models (FLMs) are a recently introduced class of language models which adapt continuous flow matching for one-hot encoded token sequences.

Local Ai

Scale-Gest: Scalable Model-Space Synthesis and Runtime Selection for On-Device Gesture Detection

arXiv:2605.12506v1 Announce Type: cross Abstract: Realizing on-device ML-based gesture detection under tight real-time performance, energy and memory constraints is challenging, especially when consid

local-aiarxiv-cs-ai