Search: “models”

Fake-HR1: Rethinking Reasoning of Vision Language Model for Synthetic Image Detection

arXiv:2602.10042v3 Announce Type: replace-cross Abstract: Recent studies have demonstrated that incorporating Chain-of-Thought (CoT) reasoning into the detection process can enhance a model's ability

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Generating Multiple-Choice Knowledge Questions with Interpretable Difficulty Estimation using Knowledge Graphs and Large Language Models

DGX agent

arXiv:2604.10748v1 Announce Type: cross Abstract: Generating multiple-choice questions (MCQs) with difficulty estimation remains challenging in automated MCQ-generation systems used in adaptive, AI-as

applicationsarxiv-cs-ai

14 Apr 2026

HFI: A unified framework for training-free detection and implicit watermarking of latent diffusion model generated images

arXiv:2412.20704v2 Announce Type: replace Abstract: Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-genera

researcharxiv-cs-cv

HOG-Layout: Hierarchical 3D Scene Generation, Optimization and Editing via Vision-Language Models

arXiv:2604.10772v1 Announce Type: new Abstract: 3D layout generation and editing play a crucial role in Embodied AI and immersive VR interaction. However, manual creation requires tedious labor, while

researcharxiv-cs-cv

Human Centered Non Intrusive Driver State Modeling Using Personalized Physiological Signals in Real World Automated Driving

arXiv:2604.11549v1 Announce Type: cross Abstract: In vehicles with partial or conditional driving automation (SAE Levels 2-3), the driver remains responsible for supervising the system and responding

agentsarxiv-cs-lg

Human-like Working Memory Interference in Large Language Models

arXiv:2604.09670v1 Announce Type: cross Abstract: Intelligent systems must maintain and manipulate task-relevant information online to adapt to dynamic environments and changing goals. This capacity,

Improving Pediatric Emergency Department Triage with Modality Dropout in Late Fusion Multimodal EHR Models

arXiv:2604.09905v1 Announce Type: new Abstract: Emergency department triage relies heavily on both quantitative vital signs and qualitative clinical notes, yet multimodal machine learning models predi

researcharxiv-cs-lg

Knowledge Integration in Differentiable Models: A Comparative Study of Data-Driven, Soft-Constrained, and Hard-Constrained Paradigms for Identification and Control of the Single Machine Infinite Bus System

model-releasesarxiv-cs-lg

arXiv:2602.09667v2 Announce Type: replace Abstract: Integrating domain knowledge into neural networks is a central challenge in scientific machine learning. Three paradigms have emerged -- data-driven

Large Language Models Can Help Mitigate Barren Plateaus in Quantum Neural Networks

arXiv:2502.13166v3 Announce Type: replace-cross Abstract: In the era of noisy intermediate-scale quantum (NISQ) computing, Quantum Neural Networks (QNNs) have emerged as a promising approach for vario

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

arXiv:2604.11513v1 Announce Type: cross Abstract: We review recent advances in machine-learning (ML) force-field methods for large-scale Landau-Lifshitz-Gilbert (LLG) simulations of metallic spin syst

local-aiarxiv-cs-lg

MedVeriSeg: Teaching MLLM-Based Medical Segmentation Models to Verify Query Validity Without Extra Training

model-releasesarxiv-cs-cv

arXiv:2604.10242v1 Announce Type: new Abstract: Despite recent advances in MLLM-based medical image segmentation, existing LISA-like methods cannot reliably reject false queries and often produce hall

Merging Triggers, Breaking Backdoors: Defensive Poisoning for Instruction-Tuned Language Models

arXiv:2601.04448v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have greatly advanced Natural Language Processing (NLP), particularly through instruction tuning, which enables b

NeuroFlow: Toward Unified Visual Encoding and Decoding from Neural Activity

arXiv:2604.09817v1 Announce Type: new Abstract: Visual encoding and decoding models act as gateways to understanding the neural mechanisms underlying human visual perception. Typically, visual encodin

researcharxiv-cs-lg

Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights

arXiv:2504.06307v2 Announce Type: replace-cross Abstract: The rapid adoption of large language models (LLMs) has led to significant energy consumption and carbon emissions, posing a critical challenge

local-aiarxiv-cs-ai

Applications

PnP-CM: Consistency Models as Plug-and-Play Priors for Inverse Problems

arXiv:2509.22736v2 Announce Type: replace-cross Abstract: Diffusion models have found extensive use in solving inverse problems, by sampling from an approximate posterior distribution of data given th

applicationsarxiv-cs-ai

Quantum-Gated Task-interaction Knowledge Distillation for Pre-trained Model-based Class-Incremental Learning

arXiv:2604.11112v1 Announce Type: cross Abstract: Class-incremental learning (CIL) aims to continuously accumulate knowledge from a stream of tasks and construct a unified classifier over all seen cla

tutorialsarxiv-cs-cv

Ro-SLM: Onboard Small Language Models for Robot Task Planning and Operation Code Generation

arXiv:2604.10929v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) provide robots with contextual reasoning abilities to comprehend human instructions. Yet, current LLM-en

tutorialsarxiv-cs-ro

Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling

arXiv:2512.12675v2 Announce Type: replace-cross Abstract: Subject-driven image generation has advanced from single- to multi-subject composition, while neglecting distinction, the ability to distingui

STU-PID: Steering Token Usage via PID Controller for Efficient Large Language Model Reasoning

arXiv:2506.18831v2 Announce Type: replace Abstract: Large Language Models employing extended chain-of-thought (CoT) reasoning often suffer from the overthinking phenomenon, generating excessive and re

TempusBench: An Evaluation Framework for Time-Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2604.11529v1 Announce Type: new Abstract: Foundation models have transformed natural language processing and computer vision, and a rapidly growing literature on time-series foundation models (T

Transformers Learn Latent Mixture Models In-Context via Mirror Descent

arXiv:2604.10848v1 Announce Type: new Abstract: Sequence modelling requires determining which past tokens are causally relevant from the context and their importance: a process inherent to the attenti

tutorialsarxiv-cs-lg

Valence-Arousal Subspace in LLMs: Circular Emotion Geometry and Multi-Behavioral Control

arXiv:2604.03147v2 Announce Type: replace-cross Abstract: We present a method to identify a valence-arousal (VA) subspace within large language model representations. From 211k emotion-labeled texts,

Applications

What Do Vision-Language Models Encode for Personalized Image Aesthetics Assessment?

arXiv:2604.11374v1 Announce Type: cross Abstract: Personalized image aesthetics assessment (PIAA) is an important research problem with practical real-world applications. While methods based on vision

applicationsarxiv-cs-cl

A Mathematical Framework for Temporal Modeling and Counterfactual Policy Simulation of Student Dropout

arXiv:2604.08874v1 Announce Type: cross Abstract: This study proposes a temporal modeling framework with a counterfactual policy-simulation layer for student dropout in higher education, using LMS eng

AMO-ENE: Attention-based Multi-Omics Fusion Model for Outcome Prediction in Extra Nodal Extension and HPV-associated Oropharyngeal Cancer

arXiv:2604.09280v1 Announce Type: cross Abstract: Extranodal extension (ENE) is an emerging prognostic factor in human papillomavirus (HPV)-associated oropharyngeal cancer (OPC), although it is curren

researcharxiv-cs-cv

An Adaptive Model Selection Framework for Demand Forecasting under Horizon-Induced Degradation to Support Business Strategy and Operations

arXiv:2602.13939v3 Announce Type: replace-cross Abstract: Business environments characterized by intermittent demand, high variability, and multi-step planning horizons require forecasting policies th

Bayesian Social Deduction with Graph-Informed Language Models

arXiv:2506.17788v2 Announce Type: replace Abstract: Social reasoning - inferring unobservable beliefs and intentions from partial observations of other agents - remains a challenging task for large la

agentsarxiv-cs-ai

Demystifying Mergeability: Interpretable Properties to Predict Model Merging Success

arXiv:2601.22285v4 Announce Type: replace Abstract: Model merging combines knowledge from separately fine-tuned models, yet success factors remain poorly understood. While recent work treats mergeabil

safetyarxiv-cs-lg

Applications

Graph Defense Diffusion Model

arXiv:2501.11568v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) are highly vulnerable to adversarial attacks, which can greatly degrade their performance. Existing graph purification

applicationsarxiv-cs-lg

Listener-Rewarded Thinking in VLMs for Image Preferences

arXiv:2506.22832v3 Announce Type: replace-cross Abstract: Training robust and generalizable reward models for human visual preferences is essential for aligning text-to-image and text-to-video generat

LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving

arXiv:2604.08719v1 Announce Type: cross Abstract: Recent years have seen remarkable progress in autonomous driving, yet generalization to long-tail and open-world scenarios remains a major bottleneck

M-IDoL: Information Decomposition for Modality-Specific and Diverse Representation Learning in Medical Foundation Model

arXiv:2604.08936v1 Announce Type: new Abstract: Medical foundation models (MFMs) aim to learn universal representations from multimodal medical images that can generalize effectively to diverse downst

tutorialsarxiv-cs-cv

Model Space Reasoning as Search in Feedback Space for Planning Domain Generation

arXiv:2604.08712v1 Announce Type: new Abstract: The generation of planning domains from natural language descriptions remains an open problem even with the advent of large language models and reasonin

agentsarxiv-cs-ai

On the Limits of Layer Pruning for Generative Reasoning in Large Language Models

arXiv:2602.01997v2 Announce Type: replace-cross Abstract: Recent work has shown that layer pruning can effectively compress large language models (LLMs) while retaining strong performance on classific

Online3R: Online Learning for Consistent Sequential Reconstruction Based on Geometry Foundation Model

arXiv:2604.09480v1 Announce Type: new Abstract: We present Online3R, a new sequential reconstruction framework that is capable of adapting to new scenes through online learning, effectively resolving

local-aiarxiv-cs-cv

PaceLLM: Brain-Inspired Large Language Models for Long-Context Understanding

arXiv:2506.17310v3 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) demonstrate strong performance across domains, their long-context capabilities are limited by transient neu

Re-Mask and Redirect: Exploiting Denoising Irreversibility in Diffusion Language Models

arXiv:2604.08557v1 Announce Type: cross Abstract: Diffusion-based language models (dLLMs) generate text by iteratively denoising masked token sequences. We show that their safety alignment rests on a

Reasoning Models Will Sometimes Lie About Their Reasoning

arXiv:2601.07663v3 Announce Type: replace Abstract: Hint-based faithfulness evaluations have established that Large Reasoning Models (LRMs) may not say what they think: they do not always volunteer in

WAND: Windowed Attention and Knowledge Distillation for Efficient Autoregressive Text-to-Speech Models

arXiv:2604.08558v1 Announce Type: cross Abstract: Recent decoder-only autoregressive text-to-speech (AR-TTS) models produce high-fidelity speech, but their memory and compute costs scale quadratically

A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection

arXiv:2604.08381v1 Announce Type: new Abstract: Sarcasm is a rhetorical device that expresses criticism or emphasizes characteristics of certain individuals or situations through exaggeration, irony,

ClawLess: A Security Model of AI Agents

arXiv:2604.06284v1 Announce Type: cross Abstract: Autonomous AI agents powered by Large Language Models can reason, plan, and execute complex tasks, but their ability to autonomously retrieve informat

agentsarxiv-cs-ai

Daily and Weekly Periodicity in Large Language Model Performance and Its Implications for Research

arXiv:2602.15889v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used in research as both tools and objects of study. Much of this work assumes that LLM performa

Diffusion Language Models Know the Answer Before Decoding

arXiv:2508.19982v5 Announce Type: replace Abstract: Diffusion language models (DLMs) have recently emerged as an alternative to autoregressive approaches, offering parallel sequence generation and fle

Digital Skin, Digital Bias: Uncovering Tone-Based Biases in LLMs and Emoji Embeddings

arXiv:2604.06863v1 Announce Type: cross Abstract: Skin-toned emojis are crucial for fostering personal identity and social inclusion in online communication. As AI models, particularly Large Language

Geometric Properties of the Voronoi Tessellation in Latent Semantic Manifolds of Large Language Models

arXiv:2604.06767v1 Announce Type: new Abstract: Language models operate on discrete tokens but compute in continuous vector spaces, inducing a Voronoi tessellation over the representation manifold. We

safetyarxiv-cs-lg

Hallucination Detection and Evaluation of Large Language Model

arXiv:2512.22416v2 Announce Type: replace Abstract: Hallucinations in Large Language Models (LLMs) pose a significant challenge, generating misleading or unverifiable content that undermines trust and

local-aiarxiv-cs-cl

Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM

arXiv:2604.08425v1 Announce Type: cross Abstract: When humans label subjective content, they disagree, and that disagreement is not noise. It reflects genuine differences in perspective shaped by anno

safetyarxiv-cs-cl

Linear Representations of Hierarchical Concepts in Language Models

arXiv:2604.07886v1 Announce Type: new Abstract: We investigate how and to what extent hierarchical relations (e.g., Japan subset Eastern Asia subset Asia) are encoded in the internal representat

tutorialsarxiv-cs-cl