Papers with link prediction models
Enhancing Future Link Prediction in Quantum Computing Semantic Networks through LLM-Initiated Node Features (2025.coling-industry)
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| Challenge: | Quantum computing is rapidly evolving in both physics and computer science due to its potential to solve complex quantum physics problems and accelerate computational processes. |
| Approach: | They propose to initialize node features using LLMs to enhance node representations for link prediction tasks in graph neural networks. |
| Outcome: | The proposed method compared to traditional node embedding techniques on a quantum computing semantic network and demonstrated efficacy compared with other methods. |
Beyond Model Performance: Can Link Prediction Enrich French Lexical Graphs? (2024.lrec-main)
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| Challenge: | lexical resources are essential for the development of NLP systems, but with advances in language models and deep learning, they are increasingly being replaced by web-derived text. |
| Approach: | They propose a resource-centric study of link prediction approaches over French lexical-semantic graphs. |
| Outcome: | The proposed method is more accurate and reliable than previous methods. |
Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications (N19-1)
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| Challenge: | Existing approaches focus on improving accuracy and overlook other aspects such as robustness and interpretability. |
| Approach: | They propose adversarial modifications for link prediction models that identify influential facts and evaluate their sensitivity to addition of fake facts. |
| Outcome: | The proposed model evaluates the robustness of the model to the addition of fake facts and the interpretability of the models. |