Semanlink - Favoris ; Attention mechanism ; Knowledge-augmented Language Models AND NLP@IBM

Search Tag:

Search Doc:

Preferences...

Tag Cloud

Arxiv Doc - Language Models + Knowledge - Memory in deep learning - Michael Glass - NLP@IBM - Question Answering - Transformers -

Favoris ; Attention mechanism ; Knowledge-augmented Language Models AND NLP@IBM

Common descendants

1 Document

[1909.04120] Span Selection Pre-training for Question Answering

Tags:

> a **new pre-training task inspired by reading
comprehension** and an **effort to avoid encoding general knowledge in the transformer network itself**

Current transformer architectures store general knowledge -> large models, long pre-training time. Better to offload the requirement of general knowledge to a sparsely activated network.

"Span selection" as an additional auxiliary task: the query is a sentence drawn from a corpus
with a term replaced with a special token: [BLANK]. The term replaced by the blank is the answer term. The passage is
relevant as determined by a BM25 search, and answer-bearing (containing the answer
term). Unlike BERT’s cloze task, where the answer must be drawn from the model itself, the answer is found in a passage
using language understanding.

> **We hope to progress to a model of general purpose language modeling that uses an indexed long
term memory to retrieve world knowledge, rather than holding it in the densely activated transformer encoder layers.**

2019-09-18 About