Search: “research”

Inference Headroom Ratio: A Diagnostic and Control Framework for Inference Stability Under Constraint

arXiv:2604.19760v1 Announce Type: new Abstract: We present a simulation-based evaluation of the Inference Headroom Ratio (IHR), a dimensionless diagnostic quantity for characterizing inference stabili

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Information Aggregation with AI Agents

DGX agent

arXiv:2604.20050v1 Announce Type: cross Abstract: Can Large Language Models (AI agents) aggregate dispersed private information through trading and reason about the knowledge of others by observing pr

researcharxiv-cs-ai

23 Apr 2026

Integrated AI Nodule Detection and Diagnosis for Lung Cancer Screening Beyond Size and Growth-Based Standards Compared with Radiologists and Leading Models

arXiv:2512.00281v2 Announce Type: replace Abstract: Early detection of malignant lung nodules remains limited by reliance on size- and growth-based screening criteria, which can delay diagnosis. We pr

Investigation of cardinality classification for bacterial colony counting using explainable artificial intelligence

arXiv:2604.20026v1 Announce Type: new Abstract: Automatic bacterial colony counting is a highly sought-after technology in modern biological laboratories because it eliminates manual counting effort.

Is Four Enough? Automated Reasoning Approaches and Dual Bounds for Condorcet Dimensions of Elections

arXiv:2604.19851v1 Announce Type: cross Abstract: In an election where n voters rank m candidates, a Condorcet winning set is a committee of k candidates such that for any outside candidate, a majorit

Issues with Value-Based Multi-objective Reinforcement Learning: Value Function Interference and Overestimation Sensitivity

arXiv:2402.06266v2 Announce Type: replace Abstract: Multi-objective reinforcement learning (MORL) algorithms extend conventional reinforcement learning (RL) to the more general case of problems with m

ItemRAG: Item-Based Retrieval-Augmented Generation for LLM-Based Recommendation

arXiv:2511.15141v2 Announce Type: replace-cross Abstract: Recently, large language models (LLMs) have been widely used as recommender systems, owing to their reasoning capability and effectiveness in

KD-Judge: A Knowledge-Driven Automated Judge Framework for Functional Fitness Movements on Edge Devices

arXiv:2604.19834v1 Announce Type: new Abstract: Functional fitness movements are widely used in training, competition, and health-oriented exercise programs, yet consistently enforcing repetition (rep

Kinematic Optimization of Phalanx Length Ratios in Robotic Hands Using Potential Dexterity

arXiv:2604.20686v1 Announce Type: new Abstract: In the design stage of robotic hands, it is not straightforward to quantitatively evaluate the effect of phalanx length ratios on dexterity without defi

researcharxiv-cs-ro

LEXIS: LatEnt ProXimal Interaction Signatures for 3D HOI from an Image

arXiv:2604.20800v1 Announce Type: new Abstract: Reconstructing 3D Human-Object Interaction from an RGB image is essential for perceptive systems. Yet, this remains challenging as it requires capturing

LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model

arXiv:2604.20796v1 Announce Type: new Abstract: We present LLaDA2.0-Uni, a unified discrete diffusion large language model (dLLM) that supports multimodal understanding and generation within a nativel

LLM StructCore: Schema-Guided Reasoning Condensation and Deterministic Compilation

arXiv:2604.20560v1 Announce Type: new Abstract: Automatically filling Case Report Forms (CRFs) from clinical notes is challenging due to noisy language, strict output contracts, and the high cost of f

Location-Aware Pretraining for Medical Difference Visual Question Answering

arXiv:2603.04950v2 Announce Type: replace-cross Abstract: Differential medical VQA models compare multiple images to identify clinically meaningful changes and rely on vision encoders to capture fine-

Machine learning moment closure models for the radiative transfer equation IV: enforcing symmetrizable hyperbolicity in two dimensions

arXiv:2604.20143v1 Announce Type: cross Abstract: This is our fourth work in the series on machine learning (ML) moment closure models for the radiative transfer equation (RTE). In the first three pap

Markov reads Pushkin, again: A statistical journey into the poetic world of Evgenij Onegin

arXiv:2604.20221v1 Announce Type: new Abstract: This study applies symbolic time series analysis and Markov modeling to explore the phonological structure of Evgenij Onegin-as captured through a graph

MasconCube: Fast and Accurate Gravity Modeling with an Explicit Representation

arXiv:2509.08607v3 Announce Type: replace-cross Abstract: The geodesy of irregularly shaped small bodies presents fundamental challenges for gravitational field modeling, particularly as deep space ex

Maximum Entropy Semi-Supervised Inverse Reinforcement Learning

arXiv:2604.20074v1 Announce Type: new Abstract: A popular approach to apprenticeship learning (AL) is to formulate it as an inverse reinforcement learning (IRL) problem. The MaxEnt-IRL algorithm succe

Maximum Likelihood Reconstruction for Multi-Look Digital Holography with Markov-Modeled Speckle Correlation

arXiv:2604.20154v1 Announce Type: cross Abstract: Multi-look acquisition is a widely used strategy for reducing speckle noise in coherent imaging systems such as digital holography. By acquiring multi

Measuring Creativity in the Age of Generative AI: Distinguishing Human and AI-Generated Creative Performance in Hiring and Talent Systems

arXiv:2604.19799v1 Announce Type: cross Abstract: Generative AI is rapidly transforming how organizations create value and evaluate talent. While large language models enhance baseline output quality,

Mechanistic Interpretability of Large-Scale Counting in LLMs through a System-2 Strategy

arXiv:2601.02989v2 Announce Type: replace Abstract: Large language models (LLMs), despite strong performance on complex mathematical problems, exhibit systematic limitations in counting tasks. This is

Mechanistic Interpretability Tool for AI Weather Models

arXiv:2604.20467v1 Announce Type: cross Abstract: Artificial Intelligence (AI) weather models are improving rapidly, and their forecasts are already competitive with long-established traditional Numer

MMCORE: MultiModal COnnection with Representation Aligned Latent Embeddings

arXiv:2604.19902v1 Announce Type: cross Abstract: We present MMCORE, a unified framework designed for multimodal image generation and editing. MMCORE leverages a pre-trained Vision-Language Model (VLM

Model Internal Sleuthing: Finding Lexical Identity and Inflectional Features in Modern Language Models

arXiv:2506.02132v5 Announce Type: replace Abstract: Large transformer-based language models dominate modern NLP, yet our understanding of how they encode linguistic information relies primarily on stu

MOMO: A framework for seamless physical, verbal, and graphical robot skill learning and adaptation

arXiv:2604.20468v1 Announce Type: cross Abstract: Industrial robot applications require increasingly flexible systems that non-expert users can easily adapt for varying tasks and environments. However

Multi-Perspective Evidence Synthesis and Reasoning for Unsupervised Multimodal Entity Linking

arXiv:2604.20283v1 Announce Type: new Abstract: Multimodal Entity Linking (MEL) is a fundamental task in data management that maps ambiguous mentions with diverse modalities to the multimodal entities

Multi-Timescale Model Predictive Control for Slow-Fast Systems

arXiv:2511.14311v2 Announce Type: replace-cross Abstract: Model Predictive Control (MPC) has established itself as the primary methodology for constrained control, enabling autonomy across diverse app

researcharxiv-cs-ro

Neural posterior estimation of the neutrino direction in IceCube using transformer-encoded normalizing flows on the sphere

arXiv:2604.19846v1 Announce Type: cross Abstract: IceCube is a cubic-kilometer-scale neutrino detector located at the geographic South Pole. A precise directional reconstruction of IceCube neutrinos i

Normalizing Flows with Iterative Denoising

arXiv:2604.20041v1 Announce Type: cross Abstract: Normalizing Flows (NFs) are a classical family of likelihood-based methods that have received revived attention. Recent efforts such as TARFlow have s

Not all ANIMALs are equal: metaphorical framing through source domains and semantic frames

arXiv:2604.20454v1 Announce Type: new Abstract: Metaphors are powerful framing devices, yet their source domains alone do not fully explain the specific associations they evoke. We argue that the inte

Object Referring-Guided Scanpath Prediction with Perception-Enhanced Vision-Language Models

arXiv:2604.20361v1 Announce Type: new Abstract: Object Referring-guided Scanpath Prediction (ORSP) aims to predict the human attention scanpath when they search for a specific target object in a visua

OISMA: On-the-fly In-memory Stochastic Multiplication Architecture for Matrix-Multiplication Workloads

arXiv:2508.08822v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) models are currently driven by a significant upscaling of their complexity, with massive matrix-multiplication wo

On the Existence of Universal Simulators of Attention

arXiv:2506.18739v2 Announce Type: replace-cross Abstract: Previous work on the learnability of transformers extemdash focused primarily on examining their ability to approximate specific algorithmic p

On the Impact of Face Segmentation-Based Background Removal on Recognition and Morphing Attack Detection

arXiv:2604.20585v1 Announce Type: new Abstract: This study investigates the impact of face image background correction through segmentation on face recognition and morphing attack detection performanc

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

On the Stability and Generalization of First-order Bilevel Minimax Optimization

arXiv:2604.20115v1 Announce Type: cross Abstract: Bilevel optimization and bilevel minimax optimization have recently emerged as unifying frameworks for a range of machine-learning tasks, including hy

Online CS-based SAR Edge-Mapping

arXiv:2604.19989v1 Announce Type: new Abstract: With modern defense applications increasingly relying on inexpensive, small Unmanned Aerial Vehicles (UAVs), a major challenge lies in designing intelli

Online Survival Analysis: A Bandit Approach under Cox PH Model

arXiv:2604.20296v1 Announce Type: cross Abstract: Survival analysis is a widely used statistical framework for modeling time-to-event data under censoring. Classical methods, such as the Cox proportio

Onyx: Cost-Efficient Disk-Oblivious ANN Search

arXiv:2604.20401v1 Announce Type: cross Abstract: Approximate nearest neighbor (ANN) search in AI systems increasingly handles sensitive data on third-party infrastructure. Trusted execution environme

Opportunistic Bone-Loss Screening from Routine Knee Radiographs Using a Multi-Task Deep Learning Framework with Sensitivity-Constrained Threshold Optimization

arXiv:2604.20268v1 Announce Type: new Abstract: Background: Osteoporosis and osteopenia are often undiagnosed until fragility fractures occur. Dual-energy X-ray absorptiometry (DXA) is the reference s

Optimizing User Profiles via Contextual Bandits for Retrieval-Augmented LLM Personalization

arXiv:2601.12078v2 Announce Type: replace Abstract: Large language models (LLMs) excel at general-purpose tasks, yet adapting their responses to individual users remains challenging. Retrieval augment

OThink-SRR1: Search, Refine and Reasoning with Reinforced Learning for Large Language Models

arXiv:2604.19766v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) expands the knowledge of Large Language Models (LLMs), yet current static retrieval methods struggle with complex

Over-Refusal and Representation Subspaces: A Mechanistic Analysis of Task-Conditioned Refusal in Aligned LLMs

arXiv:2603.27518v2 Announce Type: replace Abstract: Aligned language models that are trained to refuse harmful requests also exhibit over-refusal: they decline safe instructions that seemingly resembl

Pairing Regularization for Mitigating Many-to-One Collapse in GANs

arXiv:2604.20130v1 Announce Type: cross Abstract: Mode collapse remains a fundamental challenge in training generative adversarial networks (GANs). While existing works have primarily focused on inter

ParetoSlider: Diffusion Models Post-Training for Continuous Reward Control

arXiv:2604.20816v1 Announce Type: cross Abstract: Reinforcement Learning (RL) post-training has become the standard for aligning generative models with human preferences, yet most methods rely on a si

Passive Variable Impedance For Shared Control

arXiv:2604.20557v1 Announce Type: new Abstract: Shared Control methods often use impedance control to track target poses in a robotic manipulator. The guidance behavior of such controllers is shaped b

researcharxiv-cs-ro

PASTA: A Patch-Agnostic Twofold-Stealthy Backdoor Attack on Vision Transformers

arXiv:2604.20047v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved remarkable success across vision tasks, yet recent studies show they remain vulnerable to backdoor attacks. Exi

Personalized electric vehicle energy consumption estimation framework that integrates driver behavior with map data

arXiv:2604.20764v1 Announce Type: cross Abstract: This paper presents a personalized Battery Electric Vehicle (BEV) energy consumption estimation framework that integrates map-based contextual feature

PFGNet: A Fully Convolutional Frequency-Guided Peripheral Gating Network for Efficient Spatiotemporal Predictive Learning

arXiv:2602.20537v3 Announce Type: replace Abstract: Spatiotemporal predictive learning (STPL) aims to forecast future frames from past observations and is essential across a wide range of applications