Tootfinder

New paper: Semantic differences in visually similar face emojis 📝
We show that even #emojis that look similar (like 😊, ☺️) have subtle, reliable meaning differences, supporting a lexicalist approach. #linguistics

Over the last few weeks, I’ve been a really big fan of PicoCSS. Drop a #CSS file in an #HTML file, write some semantic HTML, and it looks nice.
https://picocs…

Pico CSS • Minimal CSS Framework for semantic HTML
Minimalist and lightweight starter kit that prioritizes semantic syntax, making every HTML element responsive and elegant by default.

Generation of Asset Administration Shell with Large Language Model Agents: Interoperability in Digital Twins with Semantic Node
Yuchen Xia, Zhewen Xiao, Nasser Jazdi, Michael Weyrich
https://arxiv.org/abs/2403.17209

Generation of Asset Administration Shell with Large Language Model Agents: Interoperability in Digital Twins with Semantic Node
This research introduces a novel approach for assisting the creation of Asset Administration Shell (AAS) instances for digital twin modeling within the context of Industry 4.0, aiming to enhance interoperability in smart manufacturing and reduce manual effort. We construct a "semantic node" data structure to capture the semantic essence of textual data. Then, a system powered by large language models is designed and implemented to process "semantic node" and generate AAS instance models from te…

Latency-Aware Generative Semantic Communications with Pre-Trained Diffusion Models
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao, Chuan Heng Foh, Pei Xiao, Mehdi Bennis
https://arxiv.org/abs/2403.17256

Latency-Aware Generative Semantic Communications with Pre-Trained Diffusion Models
Generative foundation AI models have recently shown great success in synthesizing natural signals with high perceptual quality using only textual prompts and conditioning signals to guide the generation process. This enables semantic communications at extremely low data rates in future wireless networks. In this paper, we develop a latency-aware semantic communications framework with pre-trained generative models. The transmitter performs multi-modal semantic decomposition on the input signal a…

Semantic Communication-Enabled Wireless Adaptive Panoramic Video Transmission
Haixiao Gao, Mengying Sun, Xiaodong Xu, Shujun Han
https://arxiv.org/abs/2402.16581

Semantic Communication-Enabled Wireless Adaptive Panoramic Video Transmission
In this paper, we propose an adaptive panoramic video semantic transmission (APVST) network built on the deep joint source-channel coding (Deep JSCC) structure for the efficient end-to-end transmission of panoramic videos. The proposed APVST network can adaptively extract semantic features of panoramic frames and achieve semantic feature encoding. To achieve high spectral efficiency and save bandwidth, we propose a transmission rate control mechanism for the APVST via the entropy model and the …

This https://arxiv.org/abs/2403.11542 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Topology Data Analysis-based Error Detection for Semantic Image Transmission with Incremental Knowledge-based HARQ
Semantic communication (SemCom) aims to achieve high fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy. Nevertheless, semantic communication still suffers from unexpected channel volatility and thus developing a re-transmission mechanism (e.g., hybrid automatic repeat request [HARQ]) is indispensable. In that regard, instead of discarding previously transmitted information, the incremental knowledge-based HARQ (IK-HARQ) is deemed as a more …

This https://arxiv.org/abs/2309.11038 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

CaveSeg: Deep Semantic Segmentation and Scene Parsing for Autonomous Underwater Cave Exploration
In this paper, we present CaveSeg - the first visual learning pipeline for semantic segmentation and scene parsing for AUV navigation inside underwater caves. We address the problem of scarce annotated training data by preparing a comprehensive dataset for semantic segmentation of underwater cave scenes. It contains pixel annotations for important navigation markers (e.g. caveline, arrows), obstacles (e.g. ground plain and overhead layers), scuba divers, and open areas for servoing. Through com…

Codebook-enabled Generative End-to-end Semantic Communication Powered by Transformer
Peigen Ye, Yaping Sun, Shumin Yao, Hao Chen, Xiaodong Xu, Shuguang Cui
https://arxiv.org/abs/2402.16868

Codebook-enabled Generative End-to-end Semantic Communication Powered by Transformer
Codebook-based generative semantic communication attracts increasing attention, since only indices are required to be transmitted when the codebook is shared between transmitter and receiver. However, due to the fact that the semantic relations among code vectors are not necessarily related to the distance of the corresponding code indices, the performance of the codebook-enabled semantic communication system is susceptible to the channel noise. Thus, how to improve the system robustness agains…

This https://arxiv.org/abs/2403.11693 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

Beamforming Design for Semantic-Bit Coexisting Communication System
Semantic communication (SemCom) is emerging as a key technology for future sixth-generation (6G) systems. Unlike traditional bit-level communication (BitCom), SemCom directly optimizes performance at the semantic level, leading to supe- rior communication efficiency. Nevertheless, the task-oriented nature of SemCom renders it challenging to completely replace BitCom. Consequently, it is desired to consider a semantic-bit coexisting communication system, where a base station (BS) serves SemCom u…

Pragmatic Goal-Oriented Communications under Semantic-Effectiveness Channel Errors
Tom\'as H\"uttebr\"aucker, Mohamed Sana, Emilio Calvanese Strinati
https://arxiv.org/abs/2402.16858

Pragmatic Goal-Oriented Communications under Semantic-Effectiveness Channel Errors
In forthcoming AI-assisted 6G networks, integrating semantic, pragmatic, and goal-oriented communication strategies becomes imperative. This integration will enable sensing, transmission, and processing of exclusively pertinent task data, ensuring conveyed information possesses understandable, pragmatic semantic significance, aligning with destination needs and goals. Without doubt, no communication is error free. Within this context, besides errors stemming from typical wireless communication …