Search: “models”

Evidence-Based Intelligent Diagnostic and Therapeutic Visualization System with Large Language Models: Multi-Turn Interaction and Multimodal Treatment Plan Generation

arXiv:2606.06869v1 Announce Type: new Abstract: Aim: Existing AI-assisted traditional Chinese medicine diagnostic tools suffer from opaque reasoning processes, passive interaction, and limited treatme

applicationsarxiv-cs-ai

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Interpreting Learning Under Competing Models: Joint and Stepwise Approaches for Dynamic Cognitive Diagnosis

DGX agent

arXiv:2606.06804v1 Announce Type: new Abstract: Digital learning environments record learners' responses to individual items, making it possible to study the development of specific skills rather than

safetyarxiv-cs-lg

8 Jun 2026

STRIPS-WM: Learning Grounded Propositional STRIPS-style World Models from Images

arXiv:2606.06832v1 Announce Type: new Abstract: Robots performing long-horizon visual manipulation observe high-dimensional images, but successful plans depend on action-relevant facts: what can be do

researcharxiv-cs-ro

Time series Foundation Models based on Physics-Informed Synthetic Histories for Cold-Start Photovoltaic Forecasting

arXiv:2606.07457v1 Announce Type: new Abstract: At commissioning time, Photovoltaic (PV) operators must forecast production before target-site observations are available, limiting the direct use of st

Zero-Shot Polygon Matching with Pre-trained Models for Pose Estimation and Polygon Cloud from Challenging Stereo

arXiv:2511.05949v2 Announce Type: replace Abstract: While stereo matching has achieved maturity for 0D point and 1D line primitives, establishing correspondences for 2D polygons remains largely unexpl

Analysis of the Neglect-Zero Effect in Large Language Models

arXiv:2606.05864v1 Announce Type: new Abstract: We investigate the extent to which the language processing of LLMs resembles human cognitive processes, focusing on a human cognitive bias called the ex

safetyarxiv-cs-cl

5 Jun 2026

IDEAL: Leveraging Infinite and Dynamic Characterizations of Large Language Models for Query-focused Summarization

arXiv:2407.10486v3 Announce Type: replace-cross Abstract: Query-focused summarization (QFS) aims to produce summaries that answer particular questions of interest, enabling greater user control and pe

safetyarxiv-cs-cl

5 Jun 2026

Multimodal Sexism Identification and Characterization using Large Language Models and Gradient Boosting

arXiv:2606.05997v1 Announce Type: new Abstract: We present the AILS-NTUA submission to the EXIST 2026 Lab at CLEF, addressing multimodal sexism identification and characterization in memes (Task 2) an

5 Jun 2026

Flatness and Generalization: Learning Multi-Index Models with Homogeneous Neural Networks

arXiv:2606.04429v1 Announce Type: cross Abstract: A common heuristic used to explain the generalization of first-order gradient methods on non-convex neural networks is that 'flat interpolators genera

researcharxiv-cs-lg

GlossAssist -- A Tool to Simplify Corpus Creation and Study the Effect of NLP Models in Low-Resource Documentation Settings

arXiv:2606.04367v1 Announce Type: new Abstract: Interlinear glossed text (IGT) is the standard format for linguistic annotation in language documentation. Producing it manually, however, is often slow

researcharxiv-cs-cl

Light or Full Verb? A Minimal-Pair Dataset for Probing Phraseological Competence in Language Models

arXiv:2606.05087v1 Announce Type: new Abstract: Frequent English verbs such as 'have' and 'make' can function either as collocates in light-verb constructions or as full lexical predicates, as in 'mak

researcharxiv-cs-cl

MAOAM: Unified Object and Material Selection with Vision-Language Models

arXiv:2606.04880v1 Announce Type: new Abstract: Selection is a core operation in interactive image editing. To be practical, a user should be able to specify and disambiguate the desired selection reg

MIRAGE: Mobile Agents with Implicit Reasoning and Generative World Models

arXiv:2606.04627v1 Announce Type: new Abstract: Mobile agents are increasingly expected to operate everyday applications from screenshots and language goals, where reliable control requires reasoning

Neetyabhas: A Framework for Uncertainty-Aware Public Policy Optimization in Rational Agent-Based Models

arXiv:2606.04562v1 Announce Type: new Abstract: Purpose The WHO's COVID-19 non-pharmaceutical interventions (e.g., lockdowns, vaccinations) effectively curb transmission but impose heavy economic stra

safetyarxiv-cs-ai

Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models

arXiv:2606.04123v1 Announce Type: cross Abstract: Trajectory optimization is a critical component for enabling safe and reliable autonomous operations in space exploration. As space missions increase

When Both Layers Learn: Training Dynamics of Representing Linear Models via ReLU Networks

arXiv:2606.04476v1 Announce Type: new Abstract: In this paper, we study the gradient descent dynamics for jointly training both layers of a one-hidden-layer ReLU network to fit a linear target functio

safetyarxiv-cs-lg

Tutorials

Introduction to optimization methods for training SciML models

arXiv:2601.10222v2 Announce Type: replace-cross Abstract: Optimization is central to both modern machine learning (ML) and scientific machine learning (SciML), yet the structure of the underlying opti

tutorialsarxiv-cs-ai

3 Jun 2026

Addressing Longstanding Challenges in Cognitive Science with Language Models

arXiv:2511.00206v3 Announce Type: replace Abstract: Cognitive science faces ongoing challenges in research integration, formalization, conceptual clarity, and other areas, in part due to its multiface

safetyarxiv-cs-ai

CANARY: Zero-Label Detection of Fine-Tuning Contamination in Language Models

arXiv:2606.01695v1 Announce Type: new Abstract: Adversaries can implant latent harmful behavior by poisoning as few as 1% of fine-tuning examples. The contamination is invisible to every output-level

researcharxiv-cs-lg

EvoBrain: Continual Learning of EEG Foundation Models Across Heterogeneous BCI Tasks

arXiv:2606.01767v1 Announce Type: new Abstract: Electroencephalography (EEG) is the cornerstone of non-invasive brain-computer interfaces (BCIs), yet conventional decoding relies on fragmented, task-s

Planktonzilla: Multimodal dataset and models for understanding plankton ecosystems

arXiv:2606.00080v1 Announce Type: cross Abstract: Marine plankton underpin aquatic food webs and play a key role in global CO2 sequestration, making reliable species identification critical for unders

PolarMem: A Training-Free Polarized Latent Graph Memory for Verifiable Vision-Language Models

arXiv:2602.00415v2 Announce Type: replace Abstract: Memory is not merely a storage mechanism for intelligent systems, but a structure for organizing evidence and constraining belief. This is especiall

Quantum Tunneling-Aware Machine Learning: Physics-Derived Noise Models for Robust Deployment

arXiv:2606.00741v1 Announce Type: cross Abstract: Transistor scaling is approaching a quantum-mechanical limit, as thin gate oxides induce electron leakage through quantum tunneling. Unlike convention

Thinking in Blender: Staged Executable Inverse Graphics with Vision-Language Models

arXiv:2606.02580v1 Announce Type: new Abstract: Inverse graphics is a longstanding and highly underconstrained problem that seeks to reconstruct images as editable 3D scenes which can be rendered, rel

agentsarxiv-cs-cv

When Meaning Travels: A Granular Lens on Hybrid-MoE's Role in Idiomatic Understanding for Language Models

arXiv:2606.01671v1 Announce Type: new Abstract: In the contemporary epoch of multilingual education, learning idioms provides a fascinating gateway towards creativity, cultural values, historical cont

safetyarxiv-cs-cl

NumLeak: Public Numeric Benchmarks as Latent Labels in Foundation Models

arXiv:2605.30393v1 Announce Type: cross Abstract: Public numeric benchmarks appear in pretraining, so an evaluation that conditions on a date may be measuring memorized recall rather than out-of-sampl

applicationsarxiv-cs-ai

1 Jun 2026

Hardware

SubsurfaceGen: Procedural Generation of Field-Scale Earth Models and Seismic Data

arXiv:2605.30541v1 Announce Type: new Abstract: Full waveform inversion (FWI) is the gold standard for subsurface imaging, with applications from carbon sequestration to energy and mineral exploration

hardwarearxiv-cs-lg

1 Jun 2026

Comparing Post-Hoc Explainable AI Methods for Interpreting Black-Box EEG Models in Depression Detection

arXiv:2605.28977v1 Announce Type: cross Abstract: Recent advances in deep learning have enabled increasingly accurate electroencephalography (EEG)-based classification of Major Depressive Disorder (MD

Conf-Gen: Conformal Uncertainty Quantification for Generative Models

arXiv:2605.28920v1 Announce Type: cross Abstract: Conformal prediction (CP) and its extension, conformal risk control (CRC), are established frameworks for quantifying uncertainty in supervised machin

RewardFlow: Topology-Aware Reward Propagation on State Graphs for Agentic RL with Large Language Models

arXiv:2603.18859v2 Announce Type: replace Abstract: Reinforcement learning (RL) shows promise for enhancing LLM agentic reasoning, yet sparse terminal rewards hinder fine-grained optimization. Process

Local Ai

Towards Localized and Disentangled Knowledge Editing for Multimodal Large Language Models

arXiv:2605.29826v1 Announce Type: cross Abstract: Existing methods in Multimodal Knowledge Editing (MKE) have advanced the ability to correct outdated or inaccurate knowledge in Multimodal Large Langu

local-aiarxiv-cs-ai

A Multiscale Kinetic Framework for Image Segmentation: From Particle Systems to Continuum Models

arXiv:2605.28619v1 Announce Type: new Abstract: In this work, we present a multiscale kinetic framework for consensus-based image segmentation. By interpreting an image as a system of interacting part

A Systematic Evaluation of Retrieval-Augmented Generation and Language Models for Space Operations

arXiv:2605.27444v1 Announce Type: cross Abstract: The rapid expansion of space activities has led to an unprecedented accumulation of technical documentation, operational guidelines, and scientific li

Diffusion Large Language Models for Visual Speech Recognition

arXiv:2605.28456v1 Announce Type: new Abstract: Existing Visual Speech Recognition (VSR) systems commonly rely on left-to-right autoregressive decoding, which can force premature decisions on visually

safetyarxiv-cs-ai

Fine-Tuning Vision-Language Models for Understanding Current Damage and Scoring Priority with Quality Guard Agent

arXiv:2605.27452v1 Announce Type: new Abstract: Bridge inspection in Japan requires mandatory visual assessments every five years, yet qualitative damage ratings (levels a-e) assigned by different eng

agentsarxiv-cs-cv

Large Language Models as Automatic Annotators and Annotation Adjudicators for Fine-Grained Opinion Analysis

arXiv:2601.16800v3 Announce Type: replace Abstract: Fine-grained opinion analysis of text provides a detailed understanding of expressed sentiments, including the addressed entity. Although this level

agentsarxiv-cs-cl

Skillful high-resolution weather forecasting independent of physical models

arXiv:2605.28153v1 Announce Type: cross Abstract: Accurate and timely weather forecasts are critical for high-impact decisions in modern society. Machine-learning-based weather prediction is emerging

researcharxiv-cs-lg

Stage-wise Distortion-Perception Traversal in Zero-shot Inverse Problems with Diffusion Models

arXiv:2605.28711v1 Announce Type: new Abstract: The distortion-perception (D-P) tradeoff is a fundamental phenomenon of Bayesian inverse problems, which characterizes the inherent tension between dist

Tutorials

Personalized Generative Models for Contextual Debiasing

arXiv:2605.26353v1 Announce Type: cross Abstract: Different visual patterns appear with different frequencies in the world: e.g., beach balls appear on sand more often than they do on a road. These st

tutorialsarxiv-cs-ai

27 May 2026

Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolution

arXiv:2506.07813v2 Announce Type: replace-cross Abstract: Arbitrary-scale image super-resolution aims to upsample images to any desired resolution, offering greater flexibility than traditional fixed-

27 May 2026

The Need for an External Observer Formalizing the Sufficiency Gap: A Mathematical Extension of Mixture Identifiability and Contextual Grounding in Sequence Models

arXiv:2605.26711v1 Announce Type: new Abstract: We construct a binary mixed-regime process with one deterministic textual regime and one random regime governed by an unobserved latent state. Even an i

agentsarxiv-cs-cl

27 May 2026

Automated Detection and Classification of Delusion-related Content in Naturalistic Audio Diaries Using Multi-Agent Language Models

arXiv:2605.24755v1 Announce Type: new Abstract: Speech monologues recorded in naturalistic settings provide opportunities to characterize mental illness phenomenology and detect symptom exacerbation.

26 May 2026

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification

arXiv:2605.24961v1 Announce Type: new Abstract: Medical time series are central to healthcare, enabling continuous monitoring and supporting timely clinical decisions. Despite recent progress, existin

26 May 2026

Private Adaptive Covariance Estimation via Gaussian Graphical Models

arXiv:2605.24295v1 Announce Type: new Abstract: We propose PACE-GGM, a data-adaptive differentially private method for covariance estimation that concentrates its privacy budget on the most informativ

26 May 2026

Tutorials

An Open-Source Training Dataset for Foundation Models for Black-box Optimization

arXiv:2605.23417v1 Announce Type: new Abstract: Most black-box optimization methods require extensive hyperparameter tuning, often limiting their ability to generalize across different optimization do

tutorialsarxiv-cs-lg

25 May 2026

Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models

arXiv:2605.23797v1 Announce Type: cross Abstract: Aiming at identifying unexpected inputs from unknown classes, out-of-distribution (OOD) detection has emerged as a pivotal approach to enhancing the r

safetyarxiv-cs-cv

25 May 2026

Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models

arXiv:2605.23070v1 Announce Type: new Abstract: We propose Flow Mismatching, an unsupervised anomaly detection method that deliberately avoids reconstruction-based paradigms. Instead, we treat flow ma

25 May 2026

A Human-in-the-Loop Framework for Efficient Prompt Selection in Microscopy Vision-Language Models

arXiv:2605.20495v1 Announce Type: new Abstract: Deep-learning pipelines for microscopy image classification often require expensive, labor- and time-intensive expert annotation to produce high-quality