52 citations · 77 across the 8 of their papers we have counts for
10 papers
Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation
Patrick Fernandes, Aman Madaan, Emmy Liu +8
Many recent advances in natural language generation have been fueled by training large language models on internet-scale data. However, this paradigm can lead to models that genera…
Efficient Methods for Natural Language Processing: A Survey
Marcos Treviso, Ji-Ung Lee, Tianchu Ji +19
Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance mea…
Chunk-based Nearest Neighbor Machine Translation
Pedro Henrique Martins, Zita Marinho, André F. T. Martins
Semi-parametric models, which augment generation with retrieval, have led to impressive results in language modeling and machine translation, due to their ability to retrieve fine-…
Efficient Machine Translation Domain Adaptation
Pedro Henrique Martins, Zita Marinho, André F. T. Martins
Machine translation models struggle when translating out-of-domain text, which makes domain adaptation a topic of critical importance. However, most domain adaptation methods focus…
-former: Infinite Memory Transformer
Pedro Henrique Martins, Zita Marinho, André F. T. Martins
Transformers are unable to model long-term memories effectively, since the amount of computation they need to perform grows with the context length. While variations of efficient t…
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal +53
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of auto…
Sparse Text Generation
Pedro Henrique Martins, Zita Marinho, André F. T. Martins
Current state-of-the-art text generators build on powerful language models such as GPT-2, achieving impressive performance. However, to avoid degenerate text, they require sampling…
Sparse and Structured Visual Attention
Pedro Henrique Martins, Vlad Niculae, Zita Marinho +1
Visual attention mechanisms are widely used in multimodal tasks, as visual question answering (VQA). One drawback of softmax-based attention mechanisms is that they assign some pro…
Joint Learning of Named Entity Recognition and Entity Linking
Pedro Henrique Martins, Zita Marinho, André F. T. Martins
Named entity recognition (NER) and entity linking (EL) are two fundamentally related tasks, since in order to perform EL, first the mentions to entities have to be detected. Howeve…
A deep learning approach for understanding natural language commands for mobile service robots
Pedro Henrique Martins, Luís Custódio, Rodrigo Ventura
Using natural language to give instructions to robots is challenging, since natural language understanding is still largely an open problem. In this paper we address this problem b…