Search: “papers”

Why MLLMs Struggle to Determine Object Orientations

arXiv:2604.13321v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) struggle with tasks that require reasoning about 2D object orientation in images, as documented in prior work.

safetyarxiv-cs-cv

16 Apr 2026

ZoomSpec: A Physics-Guided Coarse-to-Fine Framework for Wideband Spectrum Sensing

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2604.13568v1 Announce Type: new Abstract: Wideband spectrum sensing for low-altitude monitoring is critical yet challenging due to heterogeneous protocols,large bandwidths, and non-stationary SN

applicationsarxiv-cs-cv

16 Apr 2026

3DRO: Lidar-level SE(3) Direct Radar Odometry Using a 2D Imaging Radar and a Gyroscope

arXiv:2604.12027v1 Announce Type: new Abstract: Recently, the robotics community has regained interest in radar-based perception and state estimation. A 2D imaging radar provides dense 360deg informat

researcharxiv-cs-ro

Local Ai

A Hybrid Architecture for Benign-Malignant Classification of Mammography ROIs

arXiv:2604.12437v1 Announce Type: new Abstract: Accurate characterization of suspicious breast lesions in mammography is important for early diagnosis and treatment planning. While Convolutional Neura

local-aiarxiv-cs-cv

A longitudinal health agent framework

arXiv:2604.12019v1 Announce Type: new Abstract: Although artificial intelligence (AI) agents are increasingly proposed to support potentially longitudinal health tasks, such as symptom management, beh

A Residual-Shell-Based Lower Bound for Ollivier-Ricci Curvature

arXiv:2604.12211v1 Announce Type: new Abstract: Ollivier-Ricci curvature (ORC), defined via the Wasserstein distance that captures rich geometric information, has received growing attention in both th

researcharxiv-cs-lg

A Theoretical Comparison of No-U-Turn Sampler Variants: Necessary and Sufficient Convergence Conditions and Mixing Time Analysis under Gaussian Targets

arXiv:2603.18640v3 Announce Type: replace-cross Abstract: The No-U-Turn Sampler (NUTS) is the computational workhorse of modern Bayesian software libraries, yet its qualitative and quantitative conver

researcharxiv-cs-lg

A Two-Stage LLM Framework for Accessible and Verified XAI Explanations

arXiv:2604.12543v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to translate the technical outputs of eXplainable Artificial Intelligence (XAI) methods into accessib

applicationsarxiv-cs-ai

A2-DIDM: Privacy-preserving Accumulator-enabled Auditing for Distributed Identity of DNN Model

arXiv:2405.04108v2 Announce Type: replace-cross Abstract: Recent booming development of Generative Artificial Intelligence (GenAI) has facilitated model commercialization to reinforce the model perfor

AdaMCoT: Rethinking Cross-Lingual Factual Reasoning through Adaptive Multilingual Chain-of-Thought

arXiv:2501.16154v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown impressive multilingual capabilities through pretraining on diverse corpora. Although these models sho

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI

arXiv:2603.18104v3 Announce Type: replace Abstract: Prevailing AI training infrastructure assumes reverse-mode automatic differentiation over IEEE-754 arithmetic. The memory overhead of training relat

Agents

Aethon: A Reference-Based Replication Primitive for Constant-Time Instantiation of Stateful AI Agents

arXiv:2604.12129v1 Announce Type: new Abstract: The transition from stateless model inference to stateful agentic execution is reshaping the systems assumptions underlying modern AI infrastructure. Wh

agentsarxiv-cs-ai

AffectAgent: Collaborative Multi-Agent Reasoning for Retrieval-Augmented Multimodal Emotion Recognition

model-releasesarxiv-cs-cv

arXiv:2604.12735v1 Announce Type: new Abstract: LLM-based multimodal emotion recognition relies on static parametric memory and often hallucinates when interpreting nuanced affective states. In this p

AISafetyBenchExplorer: A Metric-Aware Catalogue of AI Safety Benchmarks Reveals Fragmented Measurement and Weak Benchmark Governance

arXiv:2604.12875v1 Announce Type: new Abstract: The rapid expansion of large language model (LLM) safety evaluation has produced a substantial benchmark ecosystem, but not a correspondingly coherent m

An Optimal Sauer Lemma Over k-ary Alphabets

arXiv:2604.12952v1 Announce Type: new Abstract: The Sauer-Shelah-Perles Lemma is a cornerstone of combinatorics and learning theory, bounding the size of a binary hypothesis class in terms of its Vapn

researcharxiv-cs-lg

ArtifactWorld: Scaling 3D Gaussian Splatting Artifact Restoration via Video Generation Models

arXiv:2604.12251v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) delivers high-fidelity real-time rendering but suffers from geometric and photometric degradations under sparse-view constr

applicationsarxiv-cs-cv

Asymptotically Stable Gait Generation and Instantaneous Walkability Determination for Planar Almost Linear Biped with Knees

arXiv:2604.12274v1 Announce Type: new Abstract: A class of planar bipedal robots with unique mechanical properties has been proposed, where all links are balanced around the hip joint, preventing natu

researcharxiv-cs-ro

BarbieGait: An Identity-Consistent Synthetic Human Dataset with Versatile Cloth-Changing for Gait Recognition

arXiv:2604.12221v1 Announce Type: new Abstract: Gait recognition, as a reliable biometric technology, has seen rapid development in recent years while it faces significant challenges caused by diverse

applicationsarxiv-cs-cv

Beyond Weather Correlation: A Comparative Study of Static and Temporal Neural Architectures for Fine-Grained Residential Energy Consumption Forecasting in Melbourne, Australia

arXiv:2604.12304v1 Announce Type: new Abstract: Accurate short-term residential energy consumption forecasting at sub-hourly resolution is critical for smart grid management, demand response programme

applicationsarxiv-cs-lg

Local Ai

BIND-USBL: Bounding IMU Navigation Drift using USBL in Heterogeneous ASV-AUV Teams

arXiv:2604.11861v1 Announce Type: new Abstract: Accurate and continuous localization of Autonomous Underwater Vehicles (AUVs) in GPS-denied environments is a persistent challenge in marine robotics. I

local-aiarxiv-cs-ro

Black-Box Optimization From Small Offline Datasets via Meta Learning with Synthetic Tasks

arXiv:2604.12325v1 Announce Type: cross Abstract: We consider the problem of offline black-box optimization, where the goal is to discover optimal designs (e.g., molecules or materials) from past expe

BRAIN: Bias-Mitigation Continual Learning Approach to Vision-Brain Understanding

arXiv:2508.18187v2 Announce Type: replace-cross Abstract: Memory decay makes it harder for the human brain to recognize visual objects and retain details. Consequently, recorded brain signals become w

CBAM-Enhanced DenseNet121 for Multi-Class Chest X-Ray Classification with Grad-CAM Explainability

arXiv:2604.12305v1 Announce Type: cross Abstract: Pneumonia remains a leading cause of childhood mortality worldwide, with a heavy burden in low-resource settings such as Bangladesh where radiologist

researcharxiv-cs-cv

CIA: Inferring the Communication Topology from LLM-based Multi-Agent Systems

arXiv:2604.12461v1 Announce Type: new Abstract: LLM-based Multi-Agent Systems (MAS) have demonstrated remarkable capabilities in solving complex tasks. Central to MAS is the communication topology whi

Clustering-Enhanced Domain Adaptation for Cross-Domain Intrusion Detection in Industrial Control Systems

arXiv:2604.12183v1 Announce Type: cross Abstract: Industrial control systems operate in dynamic environments where traffic distributions vary across scenarios, labeled samples are limited, and unknown

CoD-Lite: Real-Time Diffusion-Based Generative Image Compression

model-releasesarxiv-cs-cv

arXiv:2604.12525v1 Announce Type: new Abstract: Recent advanced diffusion methods typically derive strong generative priors by scaling diffusion transformers. However, scaling fails to generalize when

CoLA: A Choice Leakage Attack Framework to Expose Privacy Risks in Subset Training

arXiv:2604.12342v1 Announce Type: cross Abstract: Training models on a carefully chosen portion of data rather than the full dataset is now a standard preprocess for modern ML. From vision coreset sel

researcharxiv-cs-cv

CompliBench: Benchmarking LLM Judges for Compliance Violation Detection in Dialogue Systems

model-releasesarxiv-cs-cl

arXiv:2604.12312v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed as task-oriented agents in enterprise environments, ensuring their strict adherence to complex

ContextLens: Modeling Imperfect Privacy and Safety Context for Legal Compliance

arXiv:2604.12308v1 Announce Type: new Abstract: Individuals' concerns about data privacy and AI safety are highly contextualized and extend beyond sensitive patterns. Addressing these issues requires

safetyarxiv-cs-cl

CoSyncDiT: Cognitive Synchronous Diffusion Transformer for Movie Dubbing

arXiv:2604.12292v1 Announce Type: cross Abstract: Movie dubbing aims to synthesize speech that preserves the vocal identity of a reference audio while synchronizing with the lip movements in a target

safetyarxiv-cs-cv

Deepfakes at Face Value: Image and Authority

arXiv:2604.12490v1 Announce Type: cross Abstract: Deepfakes are synthetic media that superimpose or generate someone's likeness on to pre-existing sound, images, or videos using deep learning methods.

Agents

Defining and Evaluation Method for External Human-Machine Interfaces

arXiv:2604.12293v1 Announce Type: new Abstract: As the number of fatalities involving Autonomous Vehicles increase, the need for a universal method of communicating between vehicles and other agents o

agentsarxiv-cs-ro

DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding

arXiv:2604.12812v1 Announce Type: new Abstract: Existing Multimodal Large Language Models (MLLMs) suffer from significant performance degradation on the long document understanding task as document le

Does Visual Token Pruning Improve Calibration? An Empirical Study on Confidence in MLLMs

arXiv:2604.12035v1 Announce Type: new Abstract: Visual token pruning is a widely used strategy for efficient inference in multimodal large language models (MLLMs), but existing work mainly evaluates i

researcharxiv-cs-cv

DPC-VQA: Decoupling Quality Perception and Residual Calibration for Video Quality Assessment

model-releasesarxiv-cs-cv

arXiv:2604.12813v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have shown promising performance on video quality assessment (VQA) tasks. However, adapting them to new

Dynamic Modeling and Robust Gait Optimization of a Compliant Worm Robot

arXiv:2604.12031v1 Announce Type: new Abstract: Worm-inspired robots provide an effective locomotion strategy for constrained environments by combining cyclic body deformation with alternating anchori

researcharxiv-cs-ro

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning

arXiv:2409.06679v3 Announce Type: replace Abstract: Processing long contexts is increasingly important for Large Language Models (LLMs) in tasks like multi-turn dialogues, code generation, and documen

researcharxiv-cs-cl

Efficiency of Proportional Mechanisms in Online Auto-Bidding Advertising

arXiv:2604.12799v1 Announce Type: cross Abstract: The rise of automated bidding strategies in online advertising presents new challenges in designing and analyzing efficient auction mechanisms. In thi

Efficient Adversarial Training via Criticality-Aware Fine-Tuning

arXiv:2604.12780v1 Announce Type: cross Abstract: Vision Transformer (ViT) models have achieved remarkable performance across various vision tasks, with scalability being a key advantage when applied

Efficient Semantic Image Communication for Traffic Monitoring at the Edge

arXiv:2604.12622v1 Announce Type: cross Abstract: Many visual monitoring systems operate under strict communication constraints, where transmitting full-resolution images is impractical and often unne

Empirical Evaluation of PDF Parsing and Chunking for Financial Question Answering with RAG

model-releasesarxiv-cs-cl

arXiv:2604.12047v1 Announce Type: new Abstract: PDF files are primarily intended for human reading rather than automated processing. In addition, the heterogeneous content of PDFs, such as text, table

Enhancing Clustering: An Explainable Approach via Filtered Patterns

arXiv:2604.12460v1 Announce Type: new Abstract: Machine learning has become a central research area, with increasing attention devoted to explainable clustering, also known as conceptual clustering, w

applicationsarxiv-cs-ai

Euler-inspired Decoupling Neural Operator for Efficient Pansharpening

arXiv:2604.12463v1 Announce Type: cross Abstract: Pansharpening aims to synthesize high-resolution multispectral (HR-MS) images by fusing the spatial textures of panchromatic (PAN) images with the spe

Evaluating Differential Privacy Against Membership Inference in Federated Learning: Insights from the NIST Genomics Red Team Challenge

model-releasesarxiv-cs-lg

arXiv:2604.12737v1 Announce Type: cross Abstract: While Federated Learning (FL) mitigates direct data exposure, the resulting trained models remain susceptible to membership inference attacks (MIAs).

Evaluating LLM-Generated ACSL Annotations for Formal Verification

arXiv:2602.13851v3 Announce Type: replace-cross Abstract: Formal specifications are crucial for building verifiable and dependable software systems, yet generating accurate and verifiable specificatio

Hardware

Fast AI Model Partition for Split Learning over Edge Networks

arXiv:2507.01041v4 Announce Type: replace-cross Abstract: Split learning (SL) is a distributed learning paradigm that can enable computation-intensive artificial intelligence (AI) applications by part

hardwarearxiv-cs-ai

Filtered Reasoning Score: Evaluating Reasoning Quality on a Model's Most-Confident Traces

arXiv:2604.11996v1 Announce Type: cross Abstract: Should we trust Large Language Models (LLMs) with high accuracy? LLMs achieve high accuracy on reasoning benchmarks, but correctness alone does not re

Fine-tuning Factor Augmented Neural Lasso for Heterogeneous Environments

model-releasesarxiv-cs-lg

arXiv:2604.12288v1 Announce Type: cross Abstract: Fine-tuning is a widely used strategy for adapting pre-trained models to new tasks, yet its methodology and theoretical properties in high-dimensional