Search: “models”

LongFlow: Efficient KV Cache Compression for Reasoning Models

arXiv:2603.11504v2 Announce Type: replace-cross Abstract: Recent reasoning models such as OpenAI-o1 and DeepSeek-R1 have shown strong performance on complex tasks including mathematical reasoning and

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Predicting one-year clinical instability and mortality in heart failure patients using sequence modeling

DGX agent

arXiv:2511.16839v3 Announce Type: replace-cross Abstract: Heart failure (HF) discharge planning depends on identifying patients at risk of deterioration or death, yet accurate prediction from routinel

model-releasesarxiv-cs-ai

28 Apr 2026

Predicting Wind Loads on Container Ships in Harbor Environments through Multi-Fidelity Modeling

model-releasesarxiv-cs-lg

arXiv:2604.22882v1 Announce Type: new Abstract: Modern container ships face higher wind loads due to increased windage areas, making accurate predictions of wind loads essential for mooring design. Ex

RegMean++: Enhancing Effectiveness and Generalization of Regression Mean for Model Merging

arXiv:2508.03121v3 Announce Type: replace Abstract: Regression Mean (RegMean), an approach that formulates model merging as a linear regression problem, aims to find the optimal weights for each linea

researcharxiv-cs-lg

SketchVLM: Vision language models can annotate images to explain thoughts and guide users

arXiv:2604.22875v1 Announce Type: cross Abstract: When answering questions about images, humans naturally point, label, and draw to explain their reasoning. In contrast, modern vision-language models

Structural Pruning of Large Vision Language Models: A Comprehensive Study on Pruning Dynamics, Recovery, and Data Efficiency

arXiv:2604.24380v1 Announce Type: new Abstract: While Large Vision Language Models (LVLMs) demonstrate impressive capabilities, their substantial computational and memory requirements pose deployment

The Kerimov-Alekberli Model: An Information-Geometric Framework for Real-Time System Stability

arXiv:2604.24083v1 Announce Type: new Abstract: This study introduces the Kerimov-Alekberli model, a novel information-geometric framework that redefines AI safety by formally linking non-equilibrium

What Drives Compositional Generalization? The Importance of Continuous Training Objectives in Visual Generative Models

arXiv:2510.03075v3 Announce Type: replace-cross Abstract: Compositional generalization, the ability to generate novel combinations of known concepts, is a key ingredient for visual generative models.

researcharxiv-cs-ai

Z^2-Sampling: Zero-Cost Zigzag Trajectories for Semantic Alignment in Diffusion Models

arXiv:2604.23536v1 Announce Type: new Abstract: Diffusion models have achieved unprecedented success in text-aligned generation, largely driven by Classifier-Free Guidance (CFG). However, standard CFG

safetyarxiv-cs-cv

Deep Learning for Model Calibration in Simulation of Itaconic Acid Production

model-releasesarxiv-cs-lg

arXiv:2604.22496v1 Announce Type: new Abstract: In this study, deep learning is used to estimate kinetic parameters for modeling itaconic acid production based on real batch experiments conducted at d

dWorldEval: Scalable Robotic Policy Evaluation via Discrete Diffusion World Model

arXiv:2604.22152v1 Announce Type: new Abstract: Evaluating robotics policies across thousands of environments and thousands of tasks is infeasible with existing approaches. This motivates the need for

safetyarxiv-cs-ro

Applications

FeatEHR-LLM: Leveraging Large Language Models for Feature Engineering in Electronic Health Records

arXiv:2604.22534v1 Announce Type: cross Abstract: Feature engineering for Electronic Health Records (EHR) is complicated by irregular observation intervals, variable measurement frequencies, and struc

applicationsarxiv-cs-ai

Model Predictive Control of Hybrid Dynamical Systems

arXiv:2604.21989v1 Announce Type: cross Abstract: The problem of controlling hybrid dynamical systems using model predictive control (MPC) is formulated and sufficient conditions for asymptotic stabil

researcharxiv-cs-ai

V-MAGE: A Game Evaluation Framework for Assessing Vision-Centric Capabilities in Multimodal Large Language Models

arXiv:2504.06148v3 Announce Type: replace Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in visual-text processing. However, existi

researcharxiv-cs-cv

AFRILANGTUTOR: Advancing Language Tutoring and Culture Education in Low-Resource Languages with Large Language Models

arXiv:2604.20996v1 Announce Type: new Abstract: How can language learning systems be developed for languages that lack sufficient training resources? This challenge is increasingly faced by developers

BackPlay: Head-Only Look-Back Self-Correction for Diffusion Language Models

arXiv:2601.06428v3 Announce Type: replace Abstract: Diffusion Language Models (DLMs) decode multiple tokens in parallel, but aggressive multi-token decoding amplifies cross-token dependency errors and

researcharxiv-cs-lg

DepthMaster: Taming Diffusion Models for Monocular Depth Estimation

arXiv:2501.02576v2 Announce Type: replace Abstract: Monocular depth estimation within the diffusion-denoising paradigm demonstrates impressive generalization ability but suffers from low inference spe

safetyarxiv-cs-cv

Fine-Grained Perspectives: Modeling Explanations with Annotator-Specific Rationales

arXiv:2604.21667v1 Announce Type: cross Abstract: Beyond exploring disaggregated labels for modeling perspectives, annotator rationales provide fine-grained signals of individual perspectives. In this

Generalization Properties of Score-matching Diffusion Models for Intrinsically Low-dimensional Data

arXiv:2603.03700v2 Announce Type: replace-cross Abstract: Despite the remarkable empirical success of score-based diffusion models, their statistical guarantees remain underdeveloped. Existing analyse

researcharxiv-cs-ai

Quotient-Space Diffusion Models

arXiv:2604.21809v1 Announce Type: cross Abstract: Diffusion-based generative models have reformed generative AI, and have enabled new capabilities in the science domain, for example, generating 3D str

SQLyzr: A Comprehensive Benchmark and Evaluation Platform for Text-to-SQL

arXiv:2604.21214v1 Announce Type: cross Abstract: Text-to-SQL models have significantly improved with the adoption of Large Language Models (LLMs), leading to their increasing use in real-world applic

Structured Visual Narratives Undermine Safety Alignment in Multimodal Large Language Models

arXiv:2603.21697v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) extend text-only LLMs with visual reasoning, but also introduce new safety failure modes under visual

Unlocking Multi-Spectral Data for Multi-Modal Models with Guided Inputs and Chain-of-Thought Reasoning

model-releasesarxiv-cs-cv

arXiv:2604.21032v1 Announce Type: new Abstract: Multi-spectral imagery is a valuable input signal for Remote Sensing applications, such as land-use and land-cover classification and environmental moni

Environmental Understanding Vision-Language Model for Embodied Agent

arXiv:2604.19839v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown strong perception and reasoning abilities for instruction-following embodied agents. However, despite these a

Fairness Testing of Large Language Models in Role-Playing

arXiv:2411.00585v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A cr

Generative Flow Networks for Model Adaptation in Digital Twins of Natural Systems

arXiv:2604.20707v1 Announce Type: new Abstract: Digital twins of natural systems must remain aligned with physical systems that evolve over time, are only partially observed, and are typically modeled

safetyarxiv-cs-lg

HumorRank: A Tournament-Based Leaderboard for Evaluating Humor Generation in Large Language Models

arXiv:2604.19786v1 Announce Type: new Abstract: Evaluating humor in large language models (LLMs) is an open challenge because existing approaches yield isolated, incomparable metrics rather than unifi

researcharxiv-cs-cl

Intersectional Fairness in Large Language Models

arXiv:2604.20677v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in socially sensitive settings, raising concerns about fairness and biases, particularly across i

Tutorials

Language Models Learn Universal Representations of Numbers and Here's Why You Should Care

arXiv:2510.26285v2 Announce Type: replace-cross Abstract: Prior work has shown that large language models (LLMs) often converge to accurate input embedding for numbers, based on sinusoidal representat

tutorialsarxiv-cs-ai

On the Quantization Robustness of Diffusion Language Models in Coding Benchmarks

arXiv:2604.20079v1 Announce Type: cross Abstract: Auto-regressive Large Language Models (LLMs) achieve strong performance on coding tasks, but incur high memory and inference costs. Diffusion-based la

researcharxiv-cs-cl

Online Survival Analysis: A Bandit Approach under Cox PH Model

arXiv:2604.20296v1 Announce Type: cross Abstract: Survival analysis is a widely used statistical framework for modeling time-to-event data under censoring. Classical methods, such as the Cox proportio

researcharxiv-cs-lg

Retrofitting Small Multilingual Models for Retrieval: Matching 7B Performance with 300M Parameters

arXiv:2510.14274v2 Announce Type: replace Abstract: Training effective multilingual embedding models presents unique challenges due to the diversity of languages and task objectives. Although small mu

researcharxiv-cs-cl

SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Models

arXiv:2509.15174v3 Announce Type: replace-cross Abstract: WARNING: This paper contains examples of offensive materials. To address the proliferation of toxic content on social media, we introduce SMAR

Agents

X-Cache: Cross-Chunk Block Caching for Few-Step Autoregressive World Models Inference

arXiv:2604.20289v1 Announce Type: new Abstract: Real-time world simulation is becoming a key infrastructure for scalable evaluation and online reinforcement learning of autonomous driving systems. Rec

agentsarxiv-cs-cv

Applications

Conditional Diffusion Modeling with Attention for Probabilistic Battery Capacity Prediction under Real-World Condition

arXiv:2510.17414v2 Announce Type: replace Abstract: Accurate prediction of lithium-ion battery capacity and its associated uncertainty is essential for reliable battery management but remains challeng

applicationsarxiv-cs-lg

Do Emotions Influence Moral Judgment in Large Language Models?

arXiv:2604.19125v1 Announce Type: new Abstract: Large language models have been extensively studied for emotion recognition and moral reasoning as distinct capabilities, yet the extent to which emotio

safetyarxiv-cs-cl

Ground-Level Near Real-Time Modeling for PM2.5 Pollution Prediction

arXiv:2604.18973v1 Announce Type: cross Abstract: Air pollution is a worldwide public health threat that can cause or exacerbate many illnesses, including respiratory disease, cardiovascular disease,

safetyarxiv-cs-lg

Local Ai

How Out-of-Equilibrium Phase Transitions can Seed Pattern Formation in Trained Diffusion Models

arXiv:2603.20092v3 Announce Type: replace Abstract: Diffusion models generate structure by progressively transforming noise into data, yet the mechanisms underlying this transition remain poorly under

local-aiarxiv-cs-lg

Lingua-SafetyBench: A Benchmark for Safety Evaluation of Multilingual Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2601.22737v2 Announce Type: replace Abstract: The robust safety of Vision-Language Large Models (VLLMs) against joint multilingual and multimodal threats remains severely underexplored. Current

Machine individuality: Separating genuine idiosyncrasy from response bias in large language models

arXiv:2604.16755v2 Announce Type: replace Abstract: As large language models (LLMs) are increasingly integrated into daily life, in roles ranging from high-stakes decision support to companionship, un

On the Generalizability of Foundation Models for Crop Type Mapping

arXiv:2409.09451v5 Announce Type: replace Abstract: Foundation models pre-trained using self-supervised learning have shown powerful transfer learning capabilities on various downstream tasks, includi

safetyarxiv-cs-cv

One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models

arXiv:2604.18839v1 Announce Type: cross Abstract: Looped transformers scale computational depth without increasing parameter count by repeatedly applying a shared transformer block and can be used for

Applications

PREF-XAI: Preference-Based Personalized Rule Explanations of Black-Box Machine Learning Models

arXiv:2604.19684v1 Announce Type: new Abstract: Explainable artificial intelligence (XAI) has predominantly focused on generating model-centric explanations that approximate the behavior of black-box

applicationsarxiv-cs-lg

RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation

arXiv:2604.19092v1 Announce Type: cross Abstract: Recent advances in large-scale video world models have enabled increasingly realistic future prediction, raising the prospect of leveraging imagined v

SafetyALFRED: Evaluating Safety-Conscious Planning of Multimodal Large Language Models

arXiv:2604.19638v1 Announce Type: new Abstract: Multimodal Large Language Models are increasingly adopted as autonomous agents in interactive environments, yet their ability to proactively address saf

Local Ai

Self-Improving Tabular Language Models via Iterative Group Alignment

arXiv:2604.18966v1 Announce Type: cross Abstract: While language models have been adapted for tabular data generation, two fundamental limitations remain: (1) static fine-tuning produces models that c

local-aiarxiv-cs-ai

TROJail: Trajectory-Level Optimization for Multi-Turn Large Language Model Jailbreaks with Process Rewards

arXiv:2512.07761v3 Announce Type: replace Abstract: Large language models have seen widespread adoption, yet they remain vulnerable to multi-turn jailbreak attacks, threatening their safe deployment.

A Benchmark Study of Segmentation Models and Adaptation Strategies for Landslide Detection from Satellite Imagery