AndreiCComan
Research Assistant at Idiap Research Institute | PhD Student at École polytechnique fédérale de Lausanne
Martigny, Switzerland
AndreiCComan's Stars
Qiskit/rustworkx
A high performance Python graph library implemented in Rust.
amazon-science/ReFinED
ReFinED is an efficient and accurate entity linking (EL) system.
idiap/g2g-transformer
Pytorch implementation of “Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement”
mariosasko/datasets_sql
An extension package of 🤗 Datasets that provides support for executing arbitrary SQL queries on HF datasets
christos42/CLDR_CLNER_models
Though language model text embeddings have revolutionized NLP research, their ability to capture high-level semantic information, such as relations between entities in text, is limited. In this paper, we propose a novel contrastive learning framework that trains sentence embeddings to encode the relations in a graph structure. Given a sentence (unstructured text) and its graph, we use contrastive learning to impose relation-related structure on the token level representations of the sentence obtained with a CharacterBERT (El Boukkouri et al., 2020) model. The resulting relation-aware sentence embeddings achieve state-of-the-art results on the relation extraction task using only a simple KNN classifier, thereby demonstrating the success of the proposed method. Additional visualization by a tSNE analysis shows the effectiveness of the learned representation space compared to baselines. Furthermore, we show that we can learn a different space for named entity recognition, again using a contrastive learning objective, and demonstrate how to successfully combine both representation spaces in an entity-relation task.
jkulhanek/pytorch-sparse-adamw
Sparse AdamW PyTorch optimizer