29 citations · 93 across the 9 of their papers we have counts for
10 papers
DoLFIn: Distributions over Latent Features for Interpretability
Phong Le, Willem Zuidema
Interpreting the inner workings of neural models is a key step in ensuring the robustness and trustworthiness of the models, but work on neural network interpretability typically f…
Revisiting Unsupervised Relation Extraction
Thy Thy Tran, Phong Le, Sophia Ananiadou
Unsupervised relation extraction (URE) extracts relations between named entities from raw text without manually-labelled data and existing knowledge bases (KBs). URE methods can be…
Boosting Entity Linking Performance by Leveraging Unlabeled Documents
Phong Le, Ivan Titov
Modern entity linking systems rely on large collections of documents specifically annotated for the task (e.g., AIDA CoNLL). In contrast, we propose an approach which exploits only…
Distant Learning for Entity Linking with Automatic Noise Detection
Phong Le, Ivan Titov
Accurate entity linkers have been produced for domains and languages where annotated data (i.e., texts linked to a knowledge base) is available. However, little progress has been m…
Improving Entity Linking by Modeling Latent Relations between Mentions
Phong Le, Ivan Titov
Entity linking involves aligning textual mentions of named entities to their corresponding entries in a knowledge base. Entity linking systems often exploit relations between textu…
Optimizing Differentiable Relaxations of Coreference Evaluation Metrics
Phong Le, Ivan Titov
Coreference evaluation metrics are hard to optimize directly as they are non-differentiable functions, not easily decomposable into elementary decisions. Consequently, most approac…