Papers by Priyansh Trivedi
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. |
Message Passing for Hyper-Relational Knowledge Graphs (2020.emnlp-main)
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| Challenge: | Existing approaches to link prediction over knowledge graphs (KGs) are designed to work over triple-based models, where facts are represented as binary relations between entities. |
| Approach: | They propose a message passing based graph encoder - StarE capable of modeling hyper-relational knowledge graphs (KGs) they propose to encode an arbitrary number of additional information along with the main triple while keeping the semantic roles of qualifiers and triples intact. |
| Outcome: | The proposed model outperforms existing models across multiple benchmarks and shows that leveraging qualifiers is vital for link prediction. |