Search Results for author:
Found 5 papers, 3 papers with code
Transformers as Graph-to-Graph Models
We argue that Transformers are essentially graph-to-graph models, with sequences just being a special case.
Strong and Efficient Baselines for Open Domain Conversational Question Answering
Unlike the Open Domain Question Answering (ODQA) setting, the conversational (ODConvQA) domain has received limited attention when it comes to reevaluating baselines for both efficiency and effectiveness.
Conversational Question Answering
Open-Domain Question Answering
+2
GADePo: Graph-Assisted Declarative Pooling Transformers for Document-Level Relation Extraction
Document-level relation extraction aims to identify relationships between entities within a document.
Imposing Relation Structure in Language-Model Embeddings Using Contrastive Learning
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.
Ranked #10 on
Relation Extraction
on Adverse Drug Events (ADE) Corpus
An Incremental Turn-Taking Model For Task-Oriented Dialog Systems
To identify the point of maximal understanding in an ongoing utterance, we a) implement an incremental Dialog State Tracker which is updated on a token basis (iDST) b) re-label the Dialog State Tracking Challenge 2 (DSTC2) dataset and c) adapt it to the incremental turn-taking experimental scenario.
