💻 Category

cs

7235 papers

POIROT: Investigating Direct Tangible vs. Digitally Mediated Interaction and Attitude Moderation in Multi-party Murder Mystery Games

This study challenges the assumption that physical robot interaction universally enhances user experience by demonstrating that while tangible delivery does not inherently improve engagement, it significantly reduces narrative immersion for individuals with high negative attitudes toward robots, who instead benefit from digitally mediated interfaces as a social buffer.

Wen Chen, Rongxi Chen, Shankai Chen, Huiyang Gong, Minghui Guo, Yingri Xu, Xintong Wu, Xinyi Fu2026-03-10💻 cs

Multifingered force-aware control for humanoid robots

This paper presents a model-based control framework for humanoid robots that utilizes trained tactile force estimators to dynamically redistribute forces across the torso, arm, wrist, and fingers, thereby maintaining stable contact with objects of varying mass or unstable configurations by minimizing the distance between the Center of Pressure and the contact polygon centroid.

Pasquale Marra, Gabriele M. Caddeo, Ugo Pattacini, Lorenzo Natale2026-03-10💻 cs

MV-Fashion: Towards Enabling Virtual Try-On and Size Estimation with Multi-View Paired Data

This paper introduces MV-Fashion, a large-scale multi-view video dataset featuring 3,273 sequences with pixel-level annotations, ground-truth material properties, and paired flat/worn garment images, designed to bridge the realism and annotation gaps in existing datasets for virtual try-on and size estimation tasks.

Hunor Laczkó, Libang Jia, Loc-Phat Truong, Diego Hernández, Sergio Escalera, Jordi Gonzalez, Meysam Madadi2026-03-10💻 cs

Soundscapes in Spectrograms: Pioneering Multilabel Classification for South Asian Sounds

This paper proposes a novel spectrogram-based Convolutional Neural Network (CNN) approach for multilabel environmental sound classification that significantly outperforms traditional MFCC-based methods on the South Asian SAS-KIIT and UrbanSound8K datasets, offering a more robust solution for complex, overlapping acoustic environments.

Sudip Chakrabarty, Pappu Bishwas, Rajdeep Chatterjee, Tathagata Bandyopadhyay, Digonto Biswas, Bibek Howlader2026-03-10💻 cs

The Differential Effects of Agreeableness and Extraversion on Older Adults' Perceptions of Conversational AI Explanations in Assistive Settings

This mixed factorial study of 140 older adults reveals that while an LLM-based voice assistant's agreeableness significantly influences perceptions of empathy and likeability without affecting perceived intelligence, highly agreeable users are particularly sensitive to low-agreeableness agents, highlighting the importance of personality congruence and context-aware explanations in assistive settings.

Niharika Mathur, Hasibur Rahman, Smit Desai2026-03-10💻 cs

An explainable hybrid deep learning-enabled intelligent fault detection and diagnosis approach for automotive software systems validation

This paper proposes a novel explainable hybrid deep learning framework combining 1D-CNN and GRU architectures with interpretability techniques like IGs and SHAP to enhance fault detection, diagnosis, and root cause analysis in automotive software system validation while overcoming the limitations of traditional black-box models.

Mohammad Abboush, Ehab Ghannoum, Andreas Rausch2026-03-10💻 cs

Evidence-Driven Reasoning for Industrial Maintenance Using Heterogeneous Data

This paper introduces the Condition Insight Agent, a deployed decision-support framework that integrates heterogeneous industrial data sources through constrained, rule-verified LLM reasoning to generate evidence-grounded maintenance explanations and actionable advice while ensuring reliability and human oversight.

Fearghal O'Donncha, Nianjun Zhou, Natalia Martinez, James T Rayfield, Fenno F. Heath III, Abigail Langbridge, Roman Vaculin2026-03-10💻 cs

MERLIN: Building Low-SNR Robust Multimodal LLMs for Electromagnetic Signals

The paper introduces MERLIN, a novel training framework accompanied by the EM-100k dataset and EM-Bench benchmark, to overcome data scarcity, evaluation gaps, and low-SNR fragility in building robust Multimodal Large Language Models for electromagnetic signals.

Junyu Shen, Zhendong She, Chenghanyu Zhang, Yuchuang Sun, Luqing Luo, Dingwei Tan, Zonghao Guo, Bo Guo, Zehua Han, Wupeng Xie, Yaxin Mu, Peng Zhang, Peipei Li, Fengxiang Wang, Yangang Sun, Maosong Sun2026-03-10💻 cs

Privacy-Preserving End-to-End Full-Duplex Speech Dialogue Models

This paper reveals that hidden states in end-to-end full-duplex speech models like SALM-Duplex and Moshi significantly leak speaker identity, and proposes two streaming anonymization methods using Stream-Voice-Anon that effectively mitigate this privacy risk while maintaining low-latency dialogue performance.

Nikita Kuzmin, Tao Zhong, Jiajun Deng, Yingke Zhu, Tristan Tsoi, Tianxiang Cao, Simon Lui, Kong Aik Lee, Eng Siong Chng2026-03-10💻 cs

Human-AI Collaboration for Scaling Agile Regression Testing: An Agentic-AI Teammate from Manual to Automated Testing

This paper presents a retrieval-augmented, multi-agent AI system developed in partnership with Hacon that accelerates agile regression testing by automatically generating executable scripts from validated specifications, thereby significantly increasing throughput and reducing manual effort while highlighting the continued necessity of human oversight and clear requirements for quality assurance.

Moustapha El Outmani, Manthan Venkataramana Shenoy, Ahmad Hatahet, Andreas Rausch, Tim Niklas Kniep, Thomas Raddatz, Benjamin King2026-03-10💻 cs

MM-TS: Multi-Modal Temperature and Margin Schedules for Contrastive Learning with Long-Tail Data

This paper proposes MM-TS, a novel framework for multi-modal contrastive learning that dynamically adjusts temperature and margin schedules based on local data distribution to address long-tail imbalances, unifying InfoNCE and max-margin objectives to achieve state-of-the-art performance across multiple image- and video-language datasets.

Siarhei Sheludzko, Dhimitrios Duka, Bernt Schiele, Hilde Kuehne, Anna Kukleva2026-03-10💻 cs

Alignment-Aware and Reliability-Gated Multimodal Fusion for Unmanned Aerial Vehicle Detection Across Heterogeneous Thermal-Visual Sensors

This paper proposes two novel fusion strategies, Registration-aware Guided Image Fusion (RGIF) and Reliability-Gated Modality-Attention Fusion (RGMAF), which effectively integrate heterogeneous thermal and visual sensor data to significantly enhance unmanned aerial vehicle detection performance across diverse perspectives and resolutions.

Ishrat Jahan, Molla E Majid, M Murugappan, Muhammad E. H. Chowdhury, N. B. Prakash, Saad Bin Abul Kashem, Balamurugan Balusamy, Amith Khandakar2026-03-10💻 cs

Multi-Objective Evolutionary Optimization of Chance-Constrained Multiple-Choice Knapsack Problems with Implicit Probability Distributions

This paper addresses the multi-objective chance-constrained multiple-choice knapsack problem with implicit probability distributions by proposing an efficient order-preserving Monte Carlo evaluation method and a hybrid evolutionary algorithm (NHILS) that outperforms state-of-the-art optimizers in solving real-world 5G network configuration challenges.

Xuanfeng Li, Shengcai Liu, Wenjie Chen, Yew-Soon Ong, Ke Tang2026-03-10💻 cs