143 citations · 213 across the 5 of their papers we have counts for
6 papers
End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering
Devendra Singh Sachan, Siva Reddy, William Hamilton +2
We present an end-to-end differentiable training method for retrieval-augmented open-domain question answering systems that combine information from multiple retrieved documents wh…
A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective
Stephen Bonner, Ian P Barrett, Cheng Ye +5
Drug discovery and development is a complex and costly process. Machine learning approaches are being investigated to help improve the effectiveness and speed of multiple stages of…
Stronger Transformers for Neural Multi-Hop Question Generation
Devendra Singh Sachan, Lingfei Wu, Mrinmaya Sachan +1
Prior work on automated question generation has almost exclusively focused on generating simple questions whose answers can be extracted from a single document. However, there is a…
Do Syntax Trees Help Pre-trained Transformers Extract Information?
Devendra Singh Sachan, Yuhao Zhang, Peng Qi +1
Much recent work suggests that incorporating syntax information from dependency trees can improve task-specific transformer models. However, the effect of incorporating dependency…
A Universal Representation Transformer Layer for Few-Shot Image Classification
Lu Liu, William Hamilton, Guodong Long +2
Few-shot classification aims to recognize unseen classes when presented with only a small number of samples. We consider the problem of multi-domain few-shot image classification,…
Actor Critic with Differentially Private Critic
Jonathan Lebensold, William Hamilton, Borja Balle +1
Reinforcement learning algorithms are known to be sample inefficient, and often performance on one task can be substantially improved by leveraging information (e.g., via pre-train…