Search: “models”

Towards Universal Gene Regulatory Network Inference: Unlocking Generalizable Regulatory Knowledge in Single-cell Foundation Models

arXiv:2605.08128v1 Announce Type: cross Abstract: Gene Regulatory Network (GRN) inference is essential for understanding complex cellular mechanisms, rendered tractable through single-cell transcripto

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Model Releases

Transfer Learning of Multiobjective Indirect Low-Thrust Trajectories Using Diffusion Models and Markov Chain Monte Carlo

DGX agent

arXiv:2605.09125v1 Announce Type: cross Abstract: Preliminary low-thrust spacecraft mission design is a global search problem characterized by a complex solution landscape, multiple objectives, and nu

model-releasesarxiv-cs-lg

12 May 2026

VFM-SDM: A vision foundation model-based framework for training-free, marker-free, and calibration-free structural displacement measurement

arXiv:2605.09677v1 Announce Type: new Abstract: Reliable displacement measurement is fundamental for structural health monitoring and digital engineering workflows, as it provides direct structural re

VISOR: A Vision-Language Model-based Test Oracle for Testing Robot

model-releasesarxiv-cs-ro

arXiv:2605.10408v1 Announce Type: cross Abstract: Testing robots requires assessing whether they perform their intended tasks correctly, dependably, and with high quality, a challenge known as the tes

You Have Been LaTeXpOsEd: A Systematic Analysis of Information Leakage in Preprint Archives Using Large Language Models

arXiv:2510.03761v2 Announce Type: replace-cross Abstract: The widespread use of preprint repositories such as arXiv has accelerated the communication of scientific results but also introduced overlook

A Causal Diffusion Model for Video Reconstruction from Ultra-Low-Bitrate Representations

arXiv:2602.13837v2 Announce Type: replace Abstract: We study video reconstruction from ultra-low-bitrate representations, where the primary challenge shifts from encoding to decoding. In this regime,

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks

arXiv:2603.22586v2 Announce Type: replace Abstract: In-context learning (ICL) enables task adaptation at inference time by conditioning on demonstrations rather than updating model parameters. Althoug

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models

arXiv:2605.06829v1 Announce Type: cross Abstract: We survey continuous-time generative modeling methods based on transporting a simple reference distribution to a data distribution via stochastic or d

researcharxiv-cs-cv

Benchmarking EngGPT2-16B-A3B against Comparable Italian and International Open-source LLMs

arXiv:2605.07731v1 Announce Type: cross Abstract: This report benchmarks the performance of ENGINEERING Ingegneria Informatica S.p.A.'s EngGPT2MoE-16B-A3B LLM, a 16B parameter Mixture of Experts (MoE)

DiffRetriever: Parallel Representative Tokens for Retrieval with Diffusion Language Models

arXiv:2605.07210v1 Announce Type: cross Abstract: PromptReps showed that an autoregressive language model can be used directly as a retriever by prompting it to generate dense and sparse representatio

researcharxiv-cs-cl

Local Ai

Distributional simplicity bias and effective convexity in Energy Based Models

arXiv:2605.07844v1 Announce Type: new Abstract: Energy-based learning is a powerful framework for generative modelling, but its training is inherently non-convex, leading potentially to sensitivity to

local-aiarxiv-cs-lg

Local Ai

Emergent Manifold Separability during Reasoning in Large Language Models

arXiv:2602.20338v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting significantly improves reasoning in Large Language Models, yet the temporal dynamics of the underlying representati

local-aiarxiv-cs-lg

Agents

GEM: Generating LiDAR World Model via Deformable Mamba

arXiv:2605.07326v1 Announce Type: new Abstract: World models, which simulate environmental dynamics and generate sensor observations, are gaining increasing attention in autonomous driving. However, p

agentsarxiv-cs-cv

Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions

arXiv:2512.20974v3 Announce Type: replace-cross Abstract: Bayesian Reinforcement Learning (BRL), a subclass of Meta-Reinforcement Learning (Meta-RL), provides a principled framework for generalisation

Tutorials

Human-like fleeting memory improves language learning but impairs reading time prediction in transformer language models

arXiv:2508.05803v2 Announce Type: replace Abstract: Human memory is fleeting. As words are processed, the exact wordforms that make up incoming sentences are rapidly lost. Cognitive scientists have lo

tutorialsarxiv-cs-cl

Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models

arXiv:2605.07514v1 Announce Type: cross Abstract: World Action Models (WAMs) enable decision-making through imagined rollouts by predicting future observations and actions. However, the reliability of

safetyarxiv-cs-cv

LithoBench: Benchmarking Large Multimodal Models for Remote-Sensing Lithology Interpretation

arXiv:2605.07640v1 Announce Type: cross Abstract: Remote sensing lithology interpretation is fundamental to geological surveys, mineral exploration, and regional geological mapping. Unlike general lan

Miner:Mining Intrinsic Mastery for Data-Efficient RL in Large Reasoning Models

arXiv:2601.04731v2 Announce Type: replace Abstract: Current critic-free RL methods for large reasoning models suffer from severe inefficiency when training on positive homogeneous prompts (where all r

Pan-FM: A Pan-Organ Foundation Model with Saliency-Guided Masking for Missing Robustness

arXiv:2605.07055v1 Announce Type: cross Abstract: Foundation models (FMs) have shown great promise in medical imaging, but most FMs are trained on unimodal data within isolated domains, such as brain

PSK@EEUCA 2026: Fine-Tuning Large Language Models with Synthetic Data Augmentation for Multi-Class Toxicity Detection in Gaming Chat

arXiv:2605.07201v1 Announce Type: cross Abstract: This paper describes our system for the EEUCA 2026 Shared Task on Understanding Toxic Behavior in Gaming Communities. The task involves classifying Wo

Hardware

Render, Don't Decode: Weight-Space World Models with Latent Structural Disentanglement

arXiv:2605.06298v2 Announce Type: replace-cross Abstract: Training world models on vast quantities of unlabelled videos is a critical step toward fully autonomous intelligence. However, the prevailing

hardwarearxiv-cs-ai

Applications

Script Sensitivity: Benchmarking Language Models on Unicode, Romanized and Mixed-Script Sinhala

arXiv:2601.14958v3 Announce Type: replace-cross Abstract: The performance of Language Models (LMs) on low-resource, morphologically rich languages like Sinhala remains largely unexplored, particularly

applicationsarxiv-cs-ai

Hardware

Sparser, Faster, Lighter Transformer Language Models

arXiv:2603.23198v2 Announce Type: replace-cross Abstract: Scaling autoregressive large language models (LLMs) has driven unprecedented progress but comes with vast computational costs. In this work, w

hardwarearxiv-cs-cl

VDEGaussian: Video Diffusion Enhanced 4D Gaussian Splatting for Dynamic Urban Scenes Modeling

arXiv:2508.02129v2 Announce Type: replace Abstract: Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gauss

safetyarxiv-cs-cv

Hardware

Versatile yet Efficient Network Traffic Analysis: Offloading Network Foundation Model to SmartNIC

arXiv:2508.02001v2 Announce Type: replace-cross Abstract: Pervasive encryption makes large-scale labeling infeasible for traffic analysis, while security operations demand edge analysis to avert servi

hardwarearxiv-cs-lg

A Biased Nonnegative Block Term Tensor Decomposition Model for Dynamic QoS Prediction

model-releasesarxiv-cs-lg

arXiv:2605.04813v1 Announce Type: new Abstract: With the rapid development of cloud computing and Web services, Quality of Service (QoS) has become a key criterion for service selection and recommenda

A geometric relation of the error introduced by sampling a language model's output distribution to its internal state

arXiv:2605.04899v1 Announce Type: new Abstract: GPT-style language models are sensitive to single-token changes at generation points where the predicted probability distribution is spread across multi

A Regulatory Governance Framework for AI-Driven Financial Fraud Detection in U.S. Banking: Integrating OCC, SR 11-7, CFPB, and FinCEN Compliance Requirements for Model Development, Validation, and Monitoring Lifecycles

model-releasesarxiv-cs-lg

arXiv:2605.04076v1 Announce Type: new Abstract: U.S. financial institutions deploying AI-based fraud detection face a fragmented compliance landscape spanning four regulatory frameworks -- OCC Bulleti

A Universal Large Language Model -- Drone Command and Control Interface

model-releasesarxiv-cs-ro

arXiv:2601.15486v2 Announce Type: replace Abstract: The use of artificial intelligence (AI) for drone control can have a transformative impact on drone capabilities, especially when real world informa

Actionable Real-Time Modeling of Surgical Team Dynamics via Time-Expanded Interaction Graphs

arXiv:2605.04169v1 Announce Type: cross Abstract: Surgical team performance arises from complex interactions between technical execution and non-technical skills, including communication and coordinat

ArtiFixer: Enhancing and Extending 3D Reconstruction with Auto-Regressive Diffusion Models

arXiv:2603.00492v2 Announce Type: replace Abstract: Per-scene optimization methods such as 3D Gaussian Splatting provide state-of-the-art novel view synthesis quality but extrapolate poorly to under-o

researcharxiv-cs-cv

Counter-Dyna: Data-Efficient RL-Based HVAC Control using Counterfactual Building Models

arXiv:2605.04555v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) offers a promising approach for data-efficient energy management in buildings, combining the strengths of pred

DART: A Vision-Language Foundation Model for Comprehensive Rope Condition Monitoring

arXiv:2605.04943v1 Announce Type: new Abstract: The condition monitoring (CM) of synthetic fibre ropes (SFRs) used in offshore, maritime, and industrial settings demands more than a classifier: inspec

Detecting Hallucinations in Large Language Models via Internal Attention Divergence Signals

arXiv:2605.05025v1 Announce Type: new Abstract: We propose a lightweight and single-pass uncertainty quantification method for detecting hallucinations in Large Language Models. The method uses attent

researcharxiv-cs-cl

Dream-MPC: Gradient-Based Model Predictive Control with Latent Imagination

arXiv:2605.04568v1 Announce Type: new Abstract: State-of-the-art model-based Reinforcement Learning (RL) approaches either use gradient-free, population-based methods for planning, learned policy netw

From Pixels to Tokens: A Systematic Study of Latent Action Supervision for Vision-Language-Action Models

arXiv:2605.04678v1 Announce Type: cross Abstract: Latent actions serve as an intermediate representation that enables consistent modeling of vision-language-action (VLA) models across heterogeneous da

researcharxiv-cs-cv

Implicit Representations of Grammaticality in Language Models

arXiv:2605.05197v1 Announce Type: new Abstract: Grammaticality and likelihood are distinct notions in human language. Pretrained language models (LMs), which are probabilistic models of language fitte

researcharxiv-cs-cl

Investigating Trustworthiness of Nonparametric Deep Survival Models for Alzheimer's Disease Progression Analysis

arXiv:2605.04063v1 Announce Type: new Abstract: Alzheimer's Dementia (AD) is a progressive neurodegenerative disease marked by irreversible decline, making reliable modeling of its progression essenti

Applications

Perturbation is All You Need for Extrapolating Language Models

arXiv:2605.04344v1 Announce Type: cross Abstract: We introduce a simple yet powerful framework for training large language models. In contrast to the standard autoregressive next-token prediction base

applicationsarxiv-cs-lg

Positional Encoding in Transformer-Based Time Series Models: A Survey

arXiv:2502.12370v3 Announce Type: replace Abstract: Recent advancements in transformer-based models have greatly improved time series analysis, providing robust solutions for tasks such as forecasting

Agents

ProgramBench: Can Language Models Rebuild Programs From Scratch?

arXiv:2605.03546v1 Announce Type: cross Abstract: Turning ideas into full software projects from scratch has become a popular use case for language models. Agents are being deployed to seed, maintain,

agentsarxiv-cs-ai

Applications

Proximal Projection for Doubly Sparse Regularized Models

arXiv:2605.05093v1 Announce Type: cross Abstract: Regularization is often used in high-dimensional regression settings to generate a sparse model, which can save tremendous computing resources and ide

applicationsarxiv-cs-lg

Towards General Preference Alignment: Diffusion Models at Nash Equilibrium

arXiv:2605.04494v1 Announce Type: cross Abstract: Reinforcement learning from human feedback (RLHF) has been popular for aligning text-to-image (T2I) diffusion models with human preferences. As a main

safetyarxiv-cs-cv

UAV as Urban Construction Change Monitor: A New Benchmark and Change Captioning Model

arXiv:2605.04409v1 Announce Type: new Abstract: Remote Sensing Image Change Captioning (RSICC) aims to generate spatially grounded natural language descriptions of scene evolution from bi-temporal ima

Visual Disentangled Diffusion Autoencoders: Scalable Counterfactual Generation for Foundation Models

arXiv:2601.21851v2 Announce Type: replace Abstract: Foundation models, despite their robust zero-shot capabilities, remain vulnerable to spurious correlations and 'Clever Hans' strategies. Existing mi

Adaptive 3D-RoPE: Physics-Aligned Rotary Positional Encoding for Wireless Foundation Models

arXiv:2605.00968v1 Announce Type: cross Abstract: Positional encoding plays a pivotal role in determin?ing the extrapolation and generalization performance of wireless foundation models for channel st

6 May 2026

Aligning Inductive Bias for Data-Efficient Generalization in State Space Models

arXiv:2509.20789v4 Announce Type: replace Abstract: The remarkable success of modern AI has been closely tied to scaling laws, yet the finite supply of high-quality data makes data efficiency--learnin

6 May 2026

An End-to-End Framework for Building Large Language Models for Software Operations

arXiv:2605.02906v1 Announce Type: new Abstract: In the field of software operations, Large Language Models (LLMs) have attracted increasing attention. However, existing research has not yet achieved e