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Read and reap the rewards: Learning to play atari with the help of instruction manuals
High sample complexity has long been a challenge for RL. On the other hand, humans learn
to perform tasks not only from interaction or demonstrations, but also by reading …
to perform tasks not only from interaction or demonstrations, but also by reading …
Mention memory: incorporating textual knowledge into transformers through entity mention attention
Natural language understanding tasks such as open-domain question answering often
require retrieving and assimilating factual information from multiple sources. We propose to …
require retrieving and assimilating factual information from multiple sources. We propose to …
Fido: Fusion-in-decoder optimized for stronger performance and faster inference
Fusion-in-Decoder (FiD) is a powerful retrieval-augmented language model that sets the
state-of-the-art on many knowledge-intensive NLP tasks. However, the architecture used for …
state-of-the-art on many knowledge-intensive NLP tasks. However, the architecture used for …
NextLevelBERT: Masked language modeling with higher-level representations for long documents
While (large) language models have significantly improved over the last years, they still
struggle to sensibly process long sequences found, eg, in books, due to the quadratic …
struggle to sensibly process long sequences found, eg, in books, due to the quadratic …
Narrative question answering with cutting-edge open-domain qa techniques: A comprehensive study
Recent advancements in open-domain question answering (ODQA), that is, finding answers
from large open-domain corpus like Wikipedia, have led to human-level performance on …
from large open-domain corpus like Wikipedia, have led to human-level performance on …