Search: “models”

Analysing Lightweight Large Language Models for Biomedical Named Entity Recognition on Diverse Ouput Formats

arXiv:2604.25920v1 Announce Type: cross Abstract: Despite their strong linguistic capabilities, Large Language Models (LLMs) are computationally demanding and require substantial resources for fine-tu

applicationsarxiv-cs-ai

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AnimateAnyMesh++: A Flexible 4D Foundation Model for High-Fidelity Text-Driven Mesh Animation

DGX agent

arXiv:2604.26917v1 Announce Type: new Abstract: Recent advances in 4D content generation have attracted increasing attention, yet creating high-quality animated 3D models remains challenging due to th

researcharxiv-cs-cv

30 Apr 2026

Beyond Fixed Formulas: Data-Driven Linear Predictor for Efficient Diffusion Models

arXiv:2604.26365v1 Announce Type: new Abstract: To address the high sampling cost of Diffusion Transformers (DiTs), feature caching offers a training-free acceleration method. However, existing method

MINOS: A Multimodal Evaluation Model for Bidirectional Generation Between Image and Text

arXiv:2506.02494v2 Announce Type: replace-cross Abstract: Evaluation is important for multimodal generation tasks, while traditional multimodal evaluation metrics suffer from several limitations. With

safetyarxiv-cs-ai

MixerCA: An Efficient and Accurate Model for High-Performance Hyperspectral Image Classification

arXiv:2604.26138v1 Announce Type: new Abstract: Over the past decade, hyperspectral image (HSI) classification has drawn considerable interest due to HSIs' ability to effectively distinguish terrestri

Operating-Layer Controls for Onchain Language-Model Agents Under Real Capital

arXiv:2604.26091v1 Announce Type: new Abstract: We study reliability in autonomous language-model agents that translate user mandates into validated tool actions under real capital. The setting is DX

safetyarxiv-cs-ai

Quantifying Climate Change Impacts on Renewable Energy Generation: A Super-Resolution Recurrent Diffusion Model

arXiv:2412.11399v4 Announce Type: replace Abstract: Driven by global climate change and the ongoing energy transition, the coupling between power supply capabilities and meteorological factors has bec

Agents

RetroMotion: Retrocausal Motion Forecasting Models are Instructable

arXiv:2505.20414v2 Announce Type: replace-cross Abstract: Motion forecasts of road users (i.e., agents) vary in complexity depending on the number of agents, scene constraints, and interactions. In pa

agentsarxiv-cs-ai

Local Ai

TLPO: Token-Level Policy Optimization for Mitigating Language Confusion in Large Language Models

arXiv:2604.26553v1 Announce Type: cross Abstract: Large language models (LLMs) demonstrate strong multilingual capabilities, yet often fail to consistently generate responses in the intended language,

local-aiarxiv-cs-ai

WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation Models

arXiv:2510.14438v2 Announce Type: replace Abstract: The hallmark of Deep Research agents lies in compositional reasoning, the capacity to aggregate distributed, heterogeneous information into coherent

An Investigation of Linguistic Biases in LLM-Based Recommendations

arXiv:2604.25456v1 Announce Type: new Abstract: We investigate linguistic biases in LLM-based restaurant and product recommendations given prompts varying across Southern American English (AE), Indian

Liquid Neural Network Models for Natural Gas Spot Price Time-Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2604.24788v1 Announce Type: new Abstract: Natural gas is undoubtedly an essential component of the global energy system. Accurate short-term forecasting of natural gas price is challenging due t

Agents

MiMo-Embodied: X-Embodied Foundation Model Technical Report

arXiv:2511.16518v2 Announce Type: replace-cross Abstract: We open-source MiMo-Embodied, the first cross-embodied foundation model to successfully integrate and achieve state-of-the-art performance in

agentsarxiv-cs-cl

The Dynamics of Delusion: Modeling Bidirectional False Belief Amplification in Human-Chatbot Dialogue

arXiv:2604.25096v1 Announce Type: new Abstract: There is growing concern that AI chatbots might fuel delusional beliefs in users. Some have suggested that humans and chatbots mutually reinforce false

researcharxiv-cs-cl

The Surprising Universality of LLM Outputs: A Real-Time Verification Primitive

arXiv:2604.25634v1 Announce Type: cross Abstract: We report a striking statistical regularity in frontier LLM outputs that enables a CPU-only scoring primitive running at 2.6 microseconds per token, w

VibeToken: Scaling 1D Image Tokenizers and Autoregressive Models for Dynamic Resolution Generations

arXiv:2604.24885v1 Announce Type: new Abstract: We introduce an efficient, resolution-agnostic autoregressive (AR) image synthesis approach that generalizes to arbitrary resolutions and aspect ratios,

applicationsarxiv-cs-cv

BEAR: Towards Beam-Search-Aware Optimization for Recommendation with Large Language Models

arXiv:2601.22925v2 Announce Type: replace-cross Abstract: Recent years have seen a rapid surge in research leveraging Large Language Models (LLMs) for recommendation. These methods typically employ su

applicationsarxiv-cs-ai

Context-Integrated Adversarial Learning for Predictive Modelling of Stock Price Dynamics

arXiv:2604.22801v1 Announce Type: cross Abstract: It is a challenging task to forecast equity prices in fast moving financial markets as this becomes even more difficult when the predictive signal is

CUB: Benchmarking Context Utilisation Techniques for Language Models

arXiv:2505.16518v3 Announce Type: replace-cross Abstract: Incorporating external knowledge is crucial for knowledge-intensive tasks, such as question answering and fact checking. However, language mod

Local Ai

EXACT: an explainable anomaly-aware vision foundation model for analysis of 3D chest CT

arXiv:2604.24146v1 Announce Type: new Abstract: Chest computed tomography (CT) is central to the detection and management of thoracic disease, yet the growing scale and complexity of volumetric imagin

local-aiarxiv-cs-cv

EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain

arXiv:2406.14075v2 Announce Type: replace Abstract: It is crucial to understand a specific domain by events. Extensive event extraction research has been conducted in many domains such as news, financ

Exploiting Differential Flatness for Efficient Learning-based Model Predictive Control of Constrained Multi-Input Control Affine Systems

arXiv:2604.24706v1 Announce Type: cross Abstract: Learning-based control techniques use data from past trajectories to control systems with uncertain dynamics. However, learning-based controllers are

Extending Precipitation Nowcasting Horizons via Spectral Fusion of Radar Observations and Foundation Model Priors

arXiv:2603.21768v3 Announce Type: replace-cross Abstract: Precipitation nowcasting is critical for disaster mitigation and aviation safety. However, radar-only models frequently suffer from a lack of

safetyarxiv-cs-ai

Forecasting Commencing Enrolments Under Data Sparsity: A Zero-Shot Time Series Foundation Models Framework for Higher Education Planning

arXiv:2602.12120v3 Announce Type: replace Abstract: Effective resource allocation in higher education depends on reliable enrolment forecasts, yet institutional planners frequently face data series di

Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer

arXiv:2604.24062v1 Announce Type: new Abstract: Extracting abstract causal structures and applying them to novel situations is a hallmark of human intelligence. While Large Language Models (LLMs) and

Guiding Vector Field Generation via Score-based Diffusion Model

arXiv:2604.24487v1 Announce Type: new Abstract: Guiding Vector Fields (GVFs) are a powerful tool for robotic path following. However, classical methods assume smooth, ordered curves and fail when path

researcharxiv-cs-ro

Local Ai

h-MINT: Modeling Pocket-Ligand Binding with Hierarchical Molecular Interaction Network

arXiv:2604.23134v1 Announce Type: new Abstract: Accurate molecular representations are critical for drug discovery, and a central challenge lies in capturing the chemical environment of molecular frag

local-aiarxiv-cs-lg

HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization

arXiv:2511.08425v3 Announce Type: replace Abstract: Diffusion and flow-matching have emerged as powerful methodologies for generative modeling, with remarkable success in capturing complex data distri

Hierarchical Spatio-Channel Clustering for Efficient Model Compression in Medical Image Analysis

arXiv:2604.23375v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) have become increasingly difficult to deploy in resource-constrained environments due to their large memory and com

High-accuracy sampling for diffusion models and log-concave distributions

arXiv:2602.01338v2 Announce Type: replace Abstract: We present algorithms for diffusion model sampling which obtain elta-error in polylog(1/elta) steps, given access to widetilde O(elta)-accurate scor

Tutorials

Investigating the Representation of Backchannels and Fillers in Fine-tuned Language Models

arXiv:2509.20237v2 Announce Type: replace Abstract: Backchannels and fillers are important linguistic expressions in dialogue, but often treated as 'noise' to be bypassed in modern transformer-based l

tutorialsarxiv-cs-cl

Large Language Model based Interactive Decision-Making for Autonomous Driving

arXiv:2604.23513v1 Announce Type: new Abstract: In high-conflict mixed-traffic scenarios involving human-driven and autonomous vehicles, most existing autonomous driving systems default to overly cons

safetyarxiv-cs-ro

MirrorMark: A Distortion-Free Multi-Bit Watermark for Large Language Models

arXiv:2601.22246v2 Announce Type: replace-cross Abstract: As large language models (LLMs) become integral to applications such as question answering and content creation, reliable content attribution

Multi-scale Dynamic Wake Modeling of Floating Offshore Wind Turbines via Fourier Neural Operators and Physics-Informed Neural Networks

arXiv:2604.23937v1 Announce Type: cross Abstract: Multi-scale dynamic wake prediction is essential for the real-time control and performance optimization of floating offshore wind turbines (FOWTs). In

Planning Under Observation Mismatch for Traffic Signal Control via Adaptive Modular World Models

arXiv:2501.02548v2 Announce Type: replace-cross Abstract: Deploying learned decision-making systems often requires transferring to new sites where the sensing pipeline differs. In such cases, observat

Tutorials

Probing Visual Planning in Image Editing Models

arXiv:2604.22868v1 Announce Type: cross Abstract: Visual planning represents a crucial facet of human intelligence, especially in tasks that require complex spatial reasoning and navigation. Yet, in m

tutorialsarxiv-cs-ai

Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data

arXiv:2503.05587v3 Announce Type: replace-cross Abstract: Robustness has become a critical attribute for the deployment of RAG systems in real-world applications. Existing research focuses on robustne

applicationsarxiv-cs-ai

Quantum Kernel Advantage over Classical Collapse in Medical Foundation Model Embeddings

arXiv:2604.24597v1 Announce Type: cross Abstract: We provide evidence of quantum kernel advantage under noiseless simulation in binary insurance classification on MIMIC-CXR chest radiographs using qua

SARM: Stage-Aware Reward Modeling for Long Horizon Robot Manipulation

arXiv:2509.25358v4 Announce Type: replace Abstract: Large-scale robot learning has made progress on complex manipulation tasks, yet long horizon, contact rich problems, especially those involving defo

safetyarxiv-cs-ro

Shape: A Self-Supervised 3D Geometry Foundation Model for Industrial CAD Analysis

arXiv:2604.22826v1 Announce Type: new Abstract: Industrial CAD workflows require robust, generalizable 3D geometric representations supporting accuracy and explainability. We introduce Shape, a self-s

Strategic Bidding in 6G Spectrum Auctions with Large Language Models

arXiv:2604.24156v1 Announce Type: cross Abstract: Efficient and fair spectrum allocation is a central challenge in 6G networks, where massive connectivity and heterogeneous services continuously compe

TEMPO: Transformers for Temporal Disease Progression from Cross-Sectional Data

arXiv:2604.23368v1 Announce Type: new Abstract: Event-Based Models (EBMs) infer biomarker progression from cross-sectional data but typically only as ordinal sequences and rely on rigid model assumpti

Trajectory Planning for an Articulated Commercial Vehicle using Model Predictive Contouring Control

arXiv:2604.24064v1 Announce Type: new Abstract: This paper presents a trajectory planning method for articulated commercial vehicles, specifically tractor-semitrailers, based on Model Predictive Conto

researcharxiv-cs-ro

Tutorials

Universal approximation property of Banach space-valued random feature models including random neural networks

arXiv:2312.08410v5 Announce Type: replace Abstract: We introduce a Banach space-valued extension of random feature learning, a data-driven supervised machine learning technique for large-scale kernel

tutorialsarxiv-cs-lg

V-GRPO: Online Reinforcement Learning for Denoising Generative Models Is Easier than You Think

arXiv:2604.23380v1 Announce Type: cross Abstract: Aligning denoising generative models with human preferences or verifiable rewards remains a key challenge. While policy-gradient online reinforcement

safetyarxiv-cs-cv

xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models

arXiv:2509.13021v2 Announce Type: replace-cross Abstract: This work introduces xOffense, an AI-driven, multi-agent penetration testing framework that shifts the process from labor-intensive, expert-dr

CodeGraphVLP: Code-as-Planner Meets Semantic-Graph State for Non-Markovian Vision-Language-Action Models

arXiv:2604.22238v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models promise generalist robot manipulation, but are typically trained and deployed as short-horizon policies that assume

applicationsarxiv-cs-ro

27 Apr 2026

Equivariant Asynchronous Diffusion: An Adaptive Denoising Schedule for Accelerated Molecular Conformation Generation

arXiv:2603.10093v2 Announce Type: replace-cross Abstract: Recent 3D molecular generation methods primarily use asynchronous auto-regressive or synchronous diffusion models. While auto-regressive model