Search: “models”

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

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DepthMaster: Taming Diffusion Models for Monocular Depth Estimation

DGX agent

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

24 Apr 2026

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

safetyarxiv-cs-ai

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

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

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

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

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

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

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

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

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

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

safetyarxiv-cs-ai

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

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

arXiv:2604.16663v1 Announce Type: new Abstract: Landslide detection from high resolution satellite imagery is a critical task for disaster response and risk assessment, yet the relative effectiveness

Agents

A Rapid Deployment Pipeline for Autonomous Humanoid Grasping Based on Foundation Models

arXiv:2604.17258v1 Announce Type: new Abstract: Deploying a humanoid robot to manipulate a new object has traditionally required one to two days of effort: data collection, manual annotation, 3D model

agentsarxiv-cs-ro

Aligning Language Models for Lyric-to-Melody Generation with Rule-Based Musical Constraints

arXiv:2604.18489v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise in lyric-to-melody generation, but models trained with Supervised Fine-Tuning (SFT) often produce musically

safetyarxiv-cs-cl

Applications of deep generative models to DNA reaction kinetics and to cryogenic electron microscopy

arXiv:2604.16851v1 Announce Type: cross Abstract: This dissertation explores how deep generative models can advance the analysis of challenging biological problems by integrating domain knowledge with

Audio-DeepThinker: Progressive Reasoning-Aware Reinforcement Learning for High-Quality Chain-of-Thought Emergence in Audio Language Models

arXiv:2604.18187v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have made significant progress in audio understanding, yet they primarily operate as perception-and-answer systems

safetyarxiv-cs-cl

Beyond the Failures: Rethinking Foundation Models in Pathology

arXiv:2510.23807v5 Announce Type: replace-cross Abstract: Despite their successes in vision and language, foundation models have stumbled in pathology, revealing low accuracy, instability, and heavy c

CaTS-Bench: Can Language Models Describe Time Series?

arXiv:2509.20823v5 Announce Type: replace-cross Abstract: Time series captioning, the task of describing time series in natural language, requires numeric and temporal reasoning, trend interpretation,

DifFoundMAD: Foundation Models meet Differential Morphing Attack Detection

arXiv:2604.17961v1 Announce Type: new Abstract: In this work, we introduce DifFoundMAD, a parameter-efficient D-MAD framework that exploits the generalisation capabilities of vision foundation models

Does AI See like Art Historians? Interpreting How Vision Language Models Recognize Artistic Style

arXiv:2603.11024v2 Announce Type: replace Abstract: VLMs have become increasingly proficient at a range of computer vision tasks, such as visual question answering and object detection. This includes

Efficient Task Adaptation in Large Language Models via Selective Parameter Optimization

arXiv:2604.17051v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated excellent performance in general language understanding, generation and other tasks. However, when fine-t

Embedding Arithmetic: A Lightweight, Tuning-Free Framework for Post-hoc Bias Mitigation in Text-to-Image Models

arXiv:2604.18167v1 Announce Type: new Abstract: Modern text-to-image (T2I) models amplify harmful societal biases, challenging their ethical deployment. We introduce an inference-time method that reli

Enhancing Trust in Large Language Models via Uncertainty-Calibrated Fine-Tuning

arXiv:2412.02904v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized the field of natural language processing with their impressive reasoning and question-answering cap

Geometry-Guided 3D Visual Token Pruning for Video-Language Models

arXiv:2604.18260v1 Announce Type: new Abstract: Multimodal large language models have demonstrated remarkable capabilities in 2D vision, motivating their extension to 3D scene understanding. Recent st

Applications

How Training Data Shapes the Use of Parametric and In-Context Knowledge in Language Models

arXiv:2510.02370v3 Announce Type: replace Abstract: Large language models leverage both parametric knowledge acquired during pretraining and in-context knowledge provided at inference time. Crucially,

applicationsarxiv-cs-cl

Agents

Human Cognition in Machines: A Unified Perspective of World Models

arXiv:2604.16592v1 Announce Type: cross Abstract: This comprehensive report distinguishes prior works by the cognitive functions they innovate. Many works claim an almost 'human-like' cognitive capabi

agentsarxiv-cs-cv

ICAT: Incident-Case-Grounded Adaptive Testing for Physical-Risk Prediction in Embodied World Models

arXiv:2604.16405v1 Announce Type: cross Abstract: Video-generative world models are increasingly used as neural simulators for embodied planning and policy learning, yet their ability to predict physi

Infrastructure-Centric World Models: Bridging Temporal Depth and Spatial Breadth for Roadside Perception

arXiv:2604.17651v1 Announce Type: new Abstract: World models, generative AI systems that simulate how environments evolve, are transforming autonomous driving, yet all existing approaches adopt an ego

safetyarxiv-cs-cv

Lizard: An Efficient Linearization Framework for Large Language Models

arXiv:2507.09025v4 Announce Type: replace Abstract: We propose Lizard, a linearization framework that transforms pretrained Transformer-based Large Language Models (LLMs) into subquadratic architectur

Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization

arXiv:2401.15604v4 Announce Type: replace Abstract: Diffusion models have become a leading paradigm in generative AI, with score estimation via denoising score matching as a central component. While r

researcharxiv-cs-lg

Ouroboros: Single-step Diffusion Models for Cycle-consistent Forward and Inverse Rendering

arXiv:2508.14461v3 Announce Type: replace Abstract: While multi-step diffusion models have advanced both forward and inverse rendering, existing approaches often treat these problems independently, le

Please refuse to answer me! Mitigating Over-Refusal in Large Language Models via Adaptive Contrastive Decoding

arXiv:2604.17132v1 Announce Type: new Abstract: Safety-aligned large language models (LLMs) often generate refusal responses to harmless queries due to the over-refusal problem. However, existing meth

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning

arXiv:2502.02871v2 Announce Type: replace Abstract: Scientific reasoning, the process through which humans apply logic, evidence, and critical thinking to explore and interpret scientific phenomena, i

Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards

arXiv:2604.17957v1 Announce Type: new Abstract: Process Reward Models (PRMs) have emerged as a powerful tool for providing step-level feedback when evaluating the reasoning of Large Language Models (L

RemoteShield: Enable Robust Multimodal Large Language Models for Earth Observation

arXiv:2604.17243v1 Announce Type: new Abstract: A robust Multimodal Large Language Model (MLLM) for Earth Observation should maintain consistent interpretation and reasoning under realistic input vari

safetyarxiv-cs-cv