Search: “models”

Why LLMs Fail at Causal Discovery and How Interventional Agents Escape

arXiv:2605.27567v1 Announce Type: new Abstract: Causal discovery is a cornerstone of scientific reasoning, yet whether large language models can perform it reliably remains an open question. Recent be

28 May 2026

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Adversarial Water-Filling: Theory, Algorithms and Foundation Model

DGX agent

arXiv:2605.26163v1 Announce Type: cross Abstract: Competitive resource allocation problems over frequency and space can be formulated as minimax interaction between transmit power and worst-case inter

tutorialsarxiv-cs-lg

27 May 2026

ARBITER: Reasoning Trajectory Basins and Majority Vote Failures in Test-Time Sampling

arXiv:2605.26172v1 Announce Type: new Abstract: When language models use test-time sampling, they generate multiple reasoning trajectories and select an answer by majority vote. We show that these tra

BioFact-MoE: Biologically Factorized Mixture of Experts for Vision-Language Prognostic Modeling in Hepatocellular Carcinoma

arXiv:2605.26376v1 Announce Type: cross Abstract: Hepatocellular carcinoma (HCC) is biologically heterogeneous, shaped by the interplay between hepatic functional reserve and tumor-related oncologic f

tutorialsarxiv-cs-ai

Dense2MoE: Pushing the Pareto Frontier of On-Device LLMs via Unified Pruning and Upcycling

arXiv:2605.26496v1 Announce Type: cross Abstract: The Mixture of Experts MoE architecture is highly promising for resource constrained on device deployments yet training these models from scratch incu

Generative Animations: A Multi-Model Pipeline for Prompt-Driven Motion Synthesis

arXiv:2605.27203v1 Announce Type: cross Abstract: Animation elevates digital documents into immersive experiences, yet creating custom motion paths remains cumbersome, requiring designers to manually

applicationsarxiv-cs-ai

METATR: A Multilingual, Evolving Benchmark for Automatic Text Recognition

model-releasesarxiv-cs-cv

arXiv:2605.26712v1 Announce Type: new Abstract: Benchmarks that reflect the diversity and complexity of real-world documents are essential for accurately evaluating Automatic Text Recognition (ATR) sy

Modeling Agentic Technical Debt and Stochastic Tax: A Standalone Framework for Measurement, Simulation, and Dashboarding

arXiv:2605.27320v1 Announce Type: new Abstract: Agentic AI systems combine probabilistic reasoning with delegated action through tools, context, memory, orchestration, and external workflow integratio

Personalized Generative Models for Contextual Debiasing

arXiv:2605.26353v1 Announce Type: cross Abstract: Different visual patterns appear with different frequencies in the world: e.g., beach balls appear on sand more often than they do on a road. These st

tutorialsarxiv-cs-ai

PolyFusionAgent: A Multimodal Foundation Model and Autonomous AI Assistant for Polymer Property Prediction and Inverse Design

arXiv:2605.26543v1 Announce Type: new Abstract: Polymer discovery is central to fields ranging from energy storage to biomedicine, but it is hindered by an astronomically large chemical design space a

Probabilistic Recurrent Intention Switching Model

arXiv:2605.26998v1 Announce Type: new Abstract: Inverse reinforcement learning (IRL) recovers reward functions from observed behavior, yet traditional methods assume a single stationary reward that ca

researcharxiv-cs-lg

Seeing vs. Believing: Evaluating the Language Bias of Open-Source MLLMs in Counter-Intuitive Scenes

arXiv:2601.07737v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance in mainstream visual understanding tasks, but their ability

Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolution

arXiv:2506.07813v2 Announce Type: replace-cross Abstract: Arbitrary-scale image super-resolution aims to upsample images to any desired resolution, offering greater flexibility than traditional fixed-

researcharxiv-cs-ai

SL-BiLEM: Structured Learnable Behavior-in-the-Loop Epidemic Modeling for Forecasting and Policy Evaluation

arXiv:2605.26704v1 Announce Type: cross Abstract: Epidemic forecasting faces a fundamental challenge: human behavior dynamically responds to disease spread, creating feedback loops that induce distrib

safetyarxiv-cs-ai

The Need for an External Observer Formalizing the Sufficiency Gap: A Mathematical Extension of Mixture Identifiability and Contextual Grounding in Sequence Models

arXiv:2605.26711v1 Announce Type: new Abstract: We construct a binary mixed-regime process with one deterministic textual regime and one random regime governed by an unobserved latent state. Even an i

agentsarxiv-cs-cl

Tool-Schema Compression Enables Agentic RAG Under Constrained Context Budgets

arXiv:2605.26165v1 Announce Type: cross Abstract: Agentic RAG systems that equip language models with dozens to hundreds of tool definitions face a critical resource conflict: tool schemas consume the

Transfer Learning using 66 Diseases for Disease Forecasting Applications

arXiv:2605.27269v1 Announce Type: new Abstract: Disease forecasting models typically rely on a single data stream, making models brittle when histories are short or noisy. Recent top-performing models

researcharxiv-cs-lg

UltraCUA: A Foundation Model for Computer Use Agents with Hybrid Action

arXiv:2510.17790v3 Announce Type: replace-cross Abstract: Computer-use agents face a fundamental limitation. They rely exclusively on primitive GUI actions (click, type, scroll), creating brittle exec

applicationsarxiv-cs-cl

Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems

arXiv:2605.26302v1 Announce Type: new Abstract: Long-lived AI agents are increasingly deployed as persistent operational systems, yet they are still evaluated like freshly initialized models. Day-one

Agent Manufacturing: Foundation-Model Agents as First-Class Industrial Entities

arXiv:2605.24823v1 Announce Type: new Abstract: Manufacturing has passed through four widely recognized paradigms - mechanization, electrification, programmable automation, and Smart Manufacturing - e

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control

arXiv:2510.20955v2 Announce Type: replace Abstract: Safe decision-making algorithms for control of mobile robots often require the existence of feedback to verify the safety of proposed actions. This

Automated Detection and Classification of Delusion-related Content in Naturalistic Audio Diaries Using Multi-Agent Language Models

arXiv:2605.24755v1 Announce Type: new Abstract: Speech monologues recorded in naturalistic settings provide opportunities to characterize mental illness phenomenology and detect symptom exacerbation.

Bridging On-Device and Cloud LLMs for Collaborative Reasoning: A Unified Methodology for Local Routing and Post-Training

arXiv:2509.24050v4 Announce Type: replace Abstract: Device-cloud collaboration holds promise for deploying large language models (LLMs), leveraging lightweight on-device models for efficiency while re

Dale meets Langevin: A Multiplicative Denoising Diffusion Model

arXiv:2510.02730v2 Announce Type: replace Abstract: Exponentiated gradient descent (EGD), a biologically motivated optimisation algorithm that respects Dale's law, produces log-normally distributed sy

Few-Shot Neural Differentiable Simulator: Real-to-Sim Rigid-Contact Modeling

arXiv:2603.06218v2 Announce Type: replace Abstract: Accurate physics simulation is essential for robotic learning and control, yet analytical simulators often fail to capture complex contact dynamics,

safetyarxiv-cs-ro

From Index to Equity: Pre-Training Transformers for Stock Return Prediction

arXiv:2605.23962v1 Announce Type: cross Abstract: This research aims to leverage machine learning to improve stock price prediction and support informed investment decisions related to buying, selling

Geo-Expert: Towards Expert-Level Geological Reasoning via Parameter-Efficient Fine-Tuning

arXiv:2605.24844v1 Announce Type: new Abstract: While general-purpose Large Language Models (LLMs) applied to Geology often hallucinate when reasoning about subsurface structures and deep-time evoluti

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification

arXiv:2605.24961v1 Announce Type: new Abstract: Medical time series are central to healthcare, enabling continuous monitoring and supporting timely clinical decisions. Despite recent progress, existin

applicationsarxiv-cs-lg

Parameter-Efficient VLMs for Gastrointestinal Endoscopy: Medical Image Generation and Clinical Visual Question Answering

arXiv:2605.24792v1 Announce Type: cross Abstract: The major limitations of gastrointestinal (GI) endoscopy AI systems arise from a shortage of annotated data, strict privacy policies, and significant

Phonetic Modeling of Dialectal Variation in Vietnamese Speech

arXiv:2605.24451v1 Announce Type: new Abstract: Vietnamese exhibits substantial dialectal phonetic variation across Northern, Central, and Southern regions, where identical lexical items may be realiz

researcharxiv-cs-cl

Polymorphism Is Rotation: Operational Mechanistic Interpretability from a Two-Layer Transformer to Pythia-70m

arXiv:2605.24577v1 Announce Type: cross Abstract: Independently trained transformers compute the same function in residual-stream bases that differ by a uniform random rotation on SO(d_{model}). We ca

Private Adaptive Covariance Estimation via Gaussian Graphical Models

arXiv:2605.24295v1 Announce Type: new Abstract: We propose PACE-GGM, a data-adaptive differentially private method for covariance estimation that concentrates its privacy budget on the most informativ

applicationsarxiv-cs-lg

Solving Combinatorial Counting Problems with Weighted First-Order Model Counting

arXiv:2605.24845v1 Announce Type: new Abstract: Combinatorial counting problems pervade artificial intelligence, statistics, and discrete mathematics. Whether the task is enumerating subsets, multiset

researcharxiv-cs-ai

An Open-Source Training Dataset for Foundation Models for Black-box Optimization

arXiv:2605.23417v1 Announce Type: new Abstract: Most black-box optimization methods require extensive hyperparameter tuning, often limiting their ability to generalize across different optimization do

tutorialsarxiv-cs-lg

Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models

arXiv:2605.23797v1 Announce Type: cross Abstract: Aiming at identifying unexpected inputs from unknown classes, out-of-distribution (OOD) detection has emerged as a pivotal approach to enhancing the r

safetyarxiv-cs-cv

Defining AI Fatigue in Academic Contexts: Dimensions, Indicators, and a Stage-Based Model Using Grounded Theory

arXiv:2605.23123v1 Announce Type: cross Abstract: The integration of AI tools in academic settings has introduced a distinct form of strain that existing frameworks like technostress and digital fatig

researcharxiv-cs-ai

Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models

arXiv:2605.23070v1 Announce Type: new Abstract: We propose Flow Mismatching, an unsupervised anomaly detection method that deliberately avoids reconstruction-based paradigms. Instead, we treat flow ma

researcharxiv-cs-cv

Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time Series Forecasting Based on Biological ODEs

arXiv:2502.07489v2 Announce Type: replace Abstract: State-of-the-art methods for forecasting irregularly sampled time series with missing values predominantly rely on just four datasets and a few smal

What Linear Probes Miss: Multi-View Probing for Weight-Space Learning

model-releasesarxiv-cs-cv

arXiv:2605.23410v1 Announce Type: cross Abstract: The explosive growth of open-source model repositories has created a Model Jungle, where checkpoints are frequently shared without adequate documentat

Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs

arXiv:2605.21541v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) remain vulnerable to transfer-based targeted attacks, where perturbations optimized on open-source surrogate

HealthMamba: An Uncertainty-aware Spatiotemporal Graph State Space Model for Effective and Reliable Healthcare Facility Visit Prediction

arXiv:2602.05286v3 Announce Type: replace Abstract: Healthcare facility visit prediction is essential for optimizing healthcare resource allocation and informing public health policy. Despite advanced

MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data

arXiv:2605.22775v1 Announce Type: new Abstract: Real-time cognitive load assessment from eye-tracking signals could potentially enable adaptive human-centered-AI such as safety-critical applications s

Riemannian geometry meets fMRI: the advantages of modeling correlation manifolds and eigenvector subspaces

arXiv:2605.22334v1 Announce Type: new Abstract: Correlation matrices are fundamental summaries of functional brain networks, yet standard analyses often treat entries independently, ignoring the curve

applicationsarxiv-cs-lg

AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the Wild

arXiv:2605.22715v1 Announce Type: cross Abstract: As wearable and mobile devices become increasingly embedded in daily life, they offer a practical way to continuously sense human motion in the wild.

tutorialsarxiv-cs-cl

Can We Build a Monolithic Model for Fake Image Detection? SICA: Semantic-Induced Constrained Adaptation for Unified-Yet-Discriminative Artifact Feature Space Reconstruction

arXiv:2602.06676v4 Announce Type: replace Abstract: Fake Image Detection (FID), aiming at unified detection across four image forensic subdomains, is critical in real-world forensic scenarios. Compare

applicationsarxiv-cs-cv

Check Your LLM's Secret Dictionary! Five Lines of Code Reveal What Your LLM Learned (Including What It Shouldn't Have)

model-releasesarxiv-cs-cl

arXiv:2605.22005v1 Announce Type: cross Abstract: We show that singular value decomposition of the lm_head} weight matrix of a transformer-based large language model -- requiring only five lines of Py

Does Slightly Mean Somewhat? Measuring Vague Intensity Words in LLM Numeric Actions

model-releasesarxiv-cs-cl

arXiv:2605.21827v1 Announce Type: new Abstract: Do language models preserve the ordinal meaning of intensity words when those words must produce numeric actions? I study a researcher-constructed scale

MRecover: A Conditional Generative Model for Recovering Motion-Corrupted MR images Using AI Generated Contrast

arXiv:2605.21669v1 Announce Type: new Abstract: Hippocampal subfield segmentation requires high-resolution T2w turbo spin echo (TSE) MRI, yet this sequence is susceptible to motion artifacts, leading

researcharxiv-cs-cv