Categories: FAANG

KG-TRICK: Unifying Textual and Relational Information Completion of Knowledge for Multilingual Knowledge Graphs

Multilingual knowledge graphs (KGs) provide high-quality relational and textual information for various NLP applications, but they are often incomplete, especially in non-English languages. Previous research has shown that combining information from KGs in different languages aids either Knowledge Graph Completion (KGC), the task of predicting missing relations between entities, or Knowledge Graph Enhancement (KGE), the task of predicting missing textual information for entities. Although previous efforts have considered KGC and KGE as independent tasks, we hypothesize that they are…
AI Generated Robotic Content

Recent Posts

SamsungCam UltraReal – Qwen-Image LoRA

Hey everyone, Just dropped the first version of a LoRA I've been working on: SamsungCam…

8 hours ago

40 Best Early Amazon Prime Day Deals on WIRED-Tested Gear (2025)

Amazon Prime Day is back, starting on October 7, but we’ve already found good deals…

9 hours ago

These little robots literally walk on water

HydroSpread, a breakthrough fabrication method, lets scientists build ultrathin soft robots directly on water. These…

9 hours ago

VHS filters work great with AI footage (WAN 2.2 + NTSC-RS)

submitted by /u/mtrx3 [link] [comments]

1 day ago

Algorithm Showdown: Logistic Regression vs. Random Forest vs. XGBoost on Imbalanced Data

Imbalanced datasets are a common challenge in machine learning.

1 day ago

Unlock global AI inference scalability using new global cross-Region inference on Amazon Bedrock with Anthropic’s Claude Sonnet 4.5

Organizations are increasingly integrating generative AI capabilities into their applications to enhance customer experiences, streamline…

1 day ago