Tootfinder

Capsule Network-Based Semantic Intent Modeling for Human-Computer Interaction
Shixiao Wang, Yifan Zhuang, Runsheng Zhang, Zhijun Song
https://arxiv.org/abs/2507.00540

Capsule Network-Based Semantic Intent Modeling for Human-Computer Interaction
This paper proposes a user semantic intent modeling algorithm based on Capsule Networks to address the problem of insufficient accuracy in intent recognition for human-computer interaction. The method represents semantic features in input text through a vectorized capsule structure. It uses a dynamic routing mechanism to transfer information across multiple capsule layers. This helps capture hierarchical relationships and part-whole structures between semantic entities more effectively. The mod…

# Simondon: um outro ponto de vista sobre a técnica
Ozanan Carrara
Gilbert #Simondon (1924-1989) é um filósofo francês que se dedicou ao estudo filosófico da #técnica, deixando uma contribuição original nessa šrea, a qual é retomada hoje, na

EVOKS (Editor for Vocabularies to Know Semantics) "allows you to:
- create a #SKOS vocabulary from scratch
- import SKOS vocabularies in RDF/XML or Turtle format
- edit SKOS vocabularies without using its textual representation
- work collaborativley
- publish the vocabulary with a single click in the vocabulary browser

Something To Talk About
Great Australian Pods Podcast Directory: #GreatAusPods

Something To Talk About | Great Australian Pods Podcast Directory
Podcast: Something To Talk About Host: Sarrah Le Marquand Category: Society & Culture Sub-Category: Commentary & Conversations, Entertainment News First Episode: 2021 When Australia’s celebrities are…

Context-Driven Knowledge Graph Completion with Semantic-Aware Relational Message Passing
Siyuan Li, Ruitong Liu, Yan Wen, Te Sun
https://arxiv.org/abs/2506.23141

Context-Driven Knowledge Graph Completion with Semantic-Aware Relational Message Passing
Semantic context surrounding a triplet $(h, r, t)$ is crucial for Knowledge Graph Completion (KGC), providing vital cues for prediction. However, traditional node-based message passing mechanisms, when applied to knowledge graphs, often introduce noise and suffer from information dilution or over-smoothing by indiscriminately aggregating information from all neighboring edges. To address this challenge, we propose a semantic-aware relational message passing. A core innovation of this framework …

SoK: Semantic Privacy in Large Language Models
Baihe Ma, Yanna Jiang, Xu Wang, Guangshen Yu, Qin Wang, Caijun Sun, Chen Li, Xuelei Qi, Ying He, Wei Ni, Ren Ping Liu
https://arxiv.org/abs/2506.23603

SoK: Semantic Privacy in Large Language Models
As Large Language Models (LLMs) are increasingly deployed in sensitive domains, traditional data privacy measures prove inadequate for protecting information that is implicit, contextual, or inferable - what we define as semantic privacy. This Systematization of Knowledge (SoK) introduces a lifecycle-centric framework to analyze how semantic privacy risks emerge across input processing, pretraining, fine-tuning, and alignment stages of LLMs. We categorize key attack vectors and assess how curre…

Rate Maximization for Fluid Antenna System Assisted Semantic Communication
Siyun Liang, Chen Zhu, Zhaohui Yang, Changsheng You, Dusit Niyato, Kai-Kit Wong, Zhaoyang Zhang
https://arxiv.org/abs/2506.22943

Rate Maximization for Fluid Antenna System Assisted Semantic Communication
In this paper, we investigate the problem of rate maximization in a fluid antenna system (FAS) assisted semantic communication system. In the considered model, a base station (BS) with multiple static antennas employs semantic extraction techniques to compress the data ready to be sent to a user. The user equipped with a fluid antenna is located in the near field coverage region of the BS. Our aim is to jointly optimize the transmit beamforming and the semantic compression rate at the BS, as …

Towards 3D Semantic Image Synthesis for Medical Imaging
Wenwu Tang, Khaled Seyam, Bin Yang
https://arxiv.org/abs/2507.00206 https://a…

Towards 3D Semantic Image Synthesis for Medical Imaging
In the medical domain, acquiring large datasets is challenging due to both accessibility issues and stringent privacy regulations. Consequently, data availability and privacy protection are major obstacles to applying machine learning in medical imaging. To address this, our study proposes the Med-LSDM (Latent Semantic Diffusion Model), which operates directly in the 3D domain and leverages de-identified semantic maps to generate synthetic data as a method of privacy preservation and data augme…

Semantics-Guided Generative Image Compression
Cheng-Lin Wu, Hyomin Choi, Ivan V. Baji\'c
https://arxiv.org/abs/2505.24015 https://

Semantics-Guided Generative Image Compression
Advancements in text-to-image generative AI with large multimodal models are spreading into the field of image compression, creating high-quality representation of images at extremely low bit rates. This work introduces novel components to the existing multimodal image semantic compression (MISC) approach, enhancing the quality of the generated images in terms of PSNR and perceptual metrics. The new components include semantic segmentation guidance for the generative decoder, as well as content…

A Diagrammatic Calculus for a Functional Model of Natural Language Semantics
Matthieu Pierre Boyer
https://arxiv.org/abs/2507.00782 https://

A Diagrammatic Calculus for a Functional Model of Natural Language Semantics
In this paper, we study a functional programming approach to natural language semantics, allowing us to increase the expressivity of a more traditional denotation style. We will formalize a category based type and effect system, and construct a diagrammatic calculus to model parsing and handling of effects, and use it to efficiently compute the denotations for sentences.