Search: “research”

Unstable Rankings in Bayesian Deep Learning Evaluation

arXiv:2604.23102v1 Announce Type: new Abstract: Standard evaluations of Bayesian deep learning methods assume that metric estimates are reliable, but we show this assumption fails under data scarcity.

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Unveiling the Backdoor Mechanism Hidden Behind Catastrophic Overfitting in Fast Adversarial Training

DGX agent

arXiv:2604.24350v1 Announce Type: cross Abstract: Fast Adversarial Training (FAT) has attracted significant attention due to its efficiency in enhancing neural network robustness against adversarial a

researcharxiv-cs-ai

28 Apr 2026

Urban Flood Observations (UFO): A hand-labeled training and validation dataset of post-flood inundation

arXiv:2604.23066v1 Announce Type: new Abstract: Urban flooding affects lives and infrastructure worldwide. Mapping inundation in complex urban environments from satellite imagery remains challenging d

Using Language Models as Closed-Loop High-Level Planners for Robotics Applications: A Brief Overview and Benchmarks

arXiv:2511.07410v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) and Vision Language Models (VLMs) have become popular tools for embodied high-level planning. However, their depl

VAMP-Net: An Interpretable Multi-Path Network of Genomic Permutation-Invariant Set Attention and Quality-Aware 1D-CNN for MTB Drug Resistance

arXiv:2512.21786v2 Announce Type: replace Abstract: Genomic prediction of drug resistance in Mycobacterium tuberculosis is often hindered by complex epistatic interactions and variable sequencing qual

VDLF-Net: Variational Feature Fusion for Adaptive and Few-Shot Visual Learning

arXiv:2604.23641v1 Announce Type: new Abstract: This paper introduces VDLF-Net, which attaches a compact VAE to a multi-scale CNN backbone. Latent vectors and softmax-gate support the backbone feature

Viewport-Unaware Blind Omnidirectional Image Quality Assessment: A Unified and Generalized Approach

arXiv:2604.23953v1 Announce Type: cross Abstract: Blind omnidirectional image quality assessment (BOIQA) presents a great challenge to the visual quality assessment community, due to different storage

Visual Funnel: Resolving Contextual Blindness in Multimodal Large Language Models

arXiv:2512.10362v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) demonstrate impressive reasoning capabilities, but often fail to perceive fine-grained visual details

VitaminP: cross-modal learning enables whole-cell segmentation from routine histology

arXiv:2604.23799v1 Announce Type: new Abstract: Accurate whole-cell and nuclear segmentation is essential for precision pathology and spatial omics, yet routine hematoxylin and eosin (H&E) staining pr

VS-DDPM: Efficient Low-Cost Diffusion Model for Medical Modality Translation

arXiv:2604.22942v1 Announce Type: cross Abstract: Diffusion models produce high-quality synthetic data but suffer from slow inference. We propose 3D Variable-Step Denoising Diffusion Probabilistic Mod

Weakly Supervised Multicenter Nancy Index Scoring in Ulcerative Colitis Using Foundation Models

arXiv:2604.23706v1 Announce Type: new Abstract: Histologic assessment of ulcerative colitis (UC) activity is an important endpoint in clinical trials and routine care, but manual grading with indices

Well-Conditioned Oblivious Perturbations in Linear Space

arXiv:2604.23193v1 Announce Type: cross Abstract: Perturbing a deterministic n-dimensional matrix with small Gaussian noise is a cornerstone of smoothed analysis of algorithms [Spielman and Teng, JACM

What Drives Compositional Generalization? The Importance of Continuous Training Objectives in Visual Generative Models

arXiv:2510.03075v3 Announce Type: replace-cross Abstract: Compositional generalization, the ability to generate novel combinations of known concepts, is a key ingredient for visual generative models.

What Prompts Don't Say: Understanding and Managing Underspecification in LLM Prompts

arXiv:2505.13360v3 Announce Type: replace Abstract: Prompt underspecification is a common challenge when interacting with LLMs. In this paper, we present an in-depth analysis of this problem, showing

Applications

What Understanding Means in AI-Laden Astronomy

arXiv:2601.10038v2 Announce Type: replace-cross Abstract: Artificial intelligence is rapidly transforming astronomical research, yet the scientific community has largely treated this transformation as

applicationsarxiv-cs-ai

When Chain-of-Thought Fails, the Solution Hides in the Hidden States

arXiv:2604.23351v1 Announce Type: cross Abstract: Whether intermediate reasoning is computationally useful or merely explanatory depends on whether chain-of-thought (CoT) tokens contain task-relevant

When Context Sticks: Studying Interference in In-Context Learning

arXiv:2604.23371v1 Announce Type: new Abstract: This paper investigates context stickiness in in-context learning (ICL), a phenomenon where earlier examples in a prompt interfere with a transformer's

When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions

arXiv:2604.23528v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a promising machine learning framework for solving partial differential equations, but their training o

When to Commit? Towards Variable-Size Self-Contained Blocks for Discrete Diffusion Language Models

arXiv:2604.23994v1 Announce Type: cross Abstract: Discrete diffusion language models (dLLMs) enable parallel token updates with bidirectional attention, yet practical generation typically adopts block

Why AI Harms Can't Be Fixed One Identity at a Time: What 5300 Incident Reports Reveal About Intersectionality

arXiv:2604.24519v1 Announce Type: cross Abstract: AI risk assessment is the primary tool for identifying harms caused by AI systems. These include intersectional harms, which arise from the interactio

Why Architecture Choice Matters in Symbolic Regression

arXiv:2604.23256v1 Announce Type: cross Abstract: Symbolic regression discovers mathematical formulas from data. Some methods fix a tree of operators, assign learnable weights, and train by gradient d

XITE: Cross-lingual Interpolation for Transfer using Embeddings

arXiv:2604.23589v1 Announce Type: new Abstract: Facilitating cross-lingual transfer in multilingual language models remains a critical challenge. Towards this goal, we propose an embedding-based data

YOLOv8 to YOLO11: A Comprehensive Architecture In-depth Comparative Review

arXiv:2501.13400v3 Announce Type: replace-cross Abstract: In the field of deep learning-based computer vision, YOLO is revolutionary. With respect to deep learning models, YOLO is also the one that is

Applications

Your Reviews Replicate You: LLM-Based Agents as Customer Digital Twins for Conjoint Analysis

arXiv:2604.22756v1 Announce Type: cross Abstract: Conjoint analysis is a cornerstone of market research for estimating consumer preferences; however, traditional methods face persistent challenges reg

applicationsarxiv-cs-ai

A general optimization solver based on OP-to-MaxSAT reduction

arXiv:2604.21961v1 Announce Type: cross Abstract: Optimization problems are fundamental in diverse fields, such as engineering, economics, and scientific computing. However, current algorithms are mos

A Kinematic Analysis of Palm Degrees of Freedom for Enhancing Thumb Opposability in Robotic Hands

arXiv:2604.22283v1 Announce Type: new Abstract: This study investigates the kinematic role of palm degrees of freedom (DoF) in enhancing thumb opposability in a five-finger robotic hand. A hand model

researcharxiv-cs-ro

Adapting MLLMs for Nuanced Video Retrieval

arXiv:2512.13511v2 Announce Type: replace Abstract: Our objective is to build an embedding model that captures the nuanced relationship between a search query and candidate videos. We cover three aspe

Adaptive Head Budgeting for Efficient Multi-Head Attention

arXiv:2604.22583v1 Announce Type: new Abstract: Transformers have become the dominant architecture across a wide range of domains, largely due to the effectiveness of multi-head attention in capturing

Adversarial Co-Evolution of Malware and Detection Models: A Bilevel Optimization Perspective

arXiv:2604.22569v1 Announce Type: cross Abstract: Machine learning-based malware detectors are increasingly vulnerable to adversarial examples. Traditional defenses, such as one-shot adversarial train

Aggregate vs. Personalized Judges in Business Idea Evaluation: Evidence from Expert Disagreement

arXiv:2604.22517v1 Announce Type: new Abstract: Evaluating LLM-generated business ideas is often harder to scale than generating them. Unlike standard NLP benchmarks, business idea evaluation relies o

AI-Driven Performance-to-Design Generation and Optimization of Marine Propellers

arXiv:2604.22224v1 Announce Type: cross Abstract: AI is increasingly used to accelerate engineering design by improving decision-making and shortening iteration cycles. Application to marine propeller

All Eyes on the Workflow: Automated and Efficient Event Discovery from Video Streams

arXiv:2604.22476v1 Announce Type: new Abstract: Disciplines such as business process management and process mining aid organizations by discovering insights about processes on the basis of recorded ev

Altitude-Adaptive Vision-Only Geo-Localization for UAVs in GPS-Denied Environments

arXiv:2602.23872v2 Announce Type: replace Abstract: To address the scale mismatch caused by large altitude variations in UAV visual place recognition, we propose a monocular vision-only altitude-adapt

An End-to-End Ukrainian RAG for Local Deployment. Optimized Hybrid Search and Lightweight Generation

arXiv:2604.22095v1 Announce Type: new Abstract: This paper presents a highly efficient Retrieval-Augmented Generation (RAG) system built specifically for Ukrainian document question answering, which a

An Undecidability Proof for the Plan Existence Problem

arXiv:2604.22736v1 Announce Type: cross Abstract: The plan existence problem asks, given a goal in the form of a formula in modal logic, an initial epistemic state (a pointed Kripke model), and a set

Are Video Models Emerging as Zero-Shot Learners and Reasoners in Medical Imaging?

arXiv:2510.10254v2 Announce Type: replace Abstract: Recent advances in large generative models have shown that simple autoregressive formulations, when scaled appropriately, can exhibit strong zero-sh

Assessing the impact of dimensionality reduction on clustering performance -- a systematic study

arXiv:2604.22099v1 Announce Type: new Abstract: Dimensionality reduction is a critical preprocessing step for clustering high-dimensional data, yet comprehensive evaluation of its impact across divers

Associativity-Peakiness Metric for Contingency Tables

arXiv:2604.22655v1 Announce Type: new Abstract: For the use case of comparing the performance of clustering algorithms whose output is a contingency table, a single performance metric for contingency

BERAG: Bayesian Ensemble Retrieval-Augmented Generation for Knowledge-based Visual Question Answering

arXiv:2604.22678v1 Announce Type: new Abstract: A common approach to question answering with retrieval-augmented generation (RAG) is to concatenate documents into a single context and pass it to a lan

BLAST: Benchmarking LLMs with ASP-based Structured Testing

arXiv:2604.22306v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated remarkable performance across a broad spectrum of tasks, including natural language understanding, dial

Breaking Watermarks in the Frequency Domain: A Modulated Diffusion Attack Framework

arXiv:2604.22220v1 Announce Type: new Abstract: Digital image watermarking has advanced rapidly for copyright protection of generative AI, yet the comparatively limited progress in watermark attack te

CAGE-SGG: Counterfactual Active Graph Evidence for Open-Vocabulary Scene Graph Generation

arXiv:2604.22274v1 Announce Type: new Abstract: Open-vocabulary scene graph generation (SGG) aims to describe visual scenes with flexible and fine-grained relation phrases beyond a fixed predicate voc

Can QPP Choose the Right Query Variant? Evaluating Query Variant Selection for RAG Pipelines

arXiv:2604.22661v1 Announce Type: cross Abstract: Large Language Models (LLMs) have made query reformulation ubiquitous in modern retrieval and Retrieval-Augmented Generation (RAG) pipelines, enabling

Causal Concept Graphs in LLM Latent Space for Stepwise Reasoning

arXiv:2603.10377v2 Announce Type: replace-cross Abstract: Sparse autoencoders can localize where concepts live in language models, but not how they interact during multi-step reasoning. We propose Cau

Chain-of-Memory: Lightweight Memory Construction with Dynamic Evolution for LLM Agents

arXiv:2601.14287v2 Announce Type: replace Abstract: External memory systems are pivotal for enabling Large Language Model (LLM) agents to maintain persistent knowledge and perform long-horizon decisio

Characterizing pitch and roll torque coupling in insect-sized flapping-wing robots using a microfabricated gimbal

arXiv:2604.22121v1 Announce Type: cross Abstract: Sub-gram flapping-wing flying insect robots (FIRs) are challenging to model because of mechanical complexity in their wings, unsteady aerodynamic flow

researcharxiv-cs-ro

Closed Form Relations and Higher-Order Approximations of First and Second Derivatives of the Tangent Operator on SE(3)

arXiv:2604.22287v1 Announce Type: cross Abstract: The Lie group SE(3) of isometric orientation preserving transformation is used for modeling multibody systems, robots, and Cosserat continua. The use

researcharxiv-cs-ro

Conformalized Super Learner

arXiv:2604.22391v1 Announce Type: cross Abstract: The Super Learner (SL) is a widely used ensemble method that combines predictions from a library of learners based on their predictive performance. In