23 citations · 39 across the 5 of their papers we have counts for
13 papers
Knowledge Transfer from Answer Ranking to Answer Generation
Matteo Gabburo, Rik Koncel-Kedziorski, Siddhant Garg +2
Recent studies show that Question Answering (QA) based on Answer Sentence Selection (AS2) can be improved by generating an improved answer from the top-k ranked answer sentences (t…
Answer Generation for Retrieval-based Question Answering Systems
Chao-Chun Hsu, Eric Lind, Luca Soldaini +1
Recent advancements in transformer-based models have greatly improved the ability of Question Answering (QA) systems to provide correct answers; in particular, answer sentence sele…
Modeling Context in Answer Sentence Selection Systems on a Latency Budget
Rujun Han, Luca Soldaini, Alessandro Moschitti
Answer Sentence Selection (AS2) is an efficient approach for the design of open-domain Question Answering (QA) systems. In order to achieve low latency, traditional AS2 models scor…
The Cascade Transformer: an Application for Efficient Answer Sentence Selection
Luca Soldaini, Alessandro Moschitti
Large transformer-based language models have been shown to be very effective in many classification tasks. However, their computational complexity prevents their use in application…
Don't Parse, Generate! A Sequence to Sequence Architecture for Task-Oriented Semantic Parsing
Subendhu Rongali, Luca Soldaini, Emilio Monti +1
Virtual assistants such as Amazon Alexa, Apple Siri, and Google Assistant often rely on a semantic parsing component to understand which action(s) to execute for an utterance spoke…
Improving Spoken Language Understanding By Exploiting ASR N-best Hypotheses
Mingda Li, Weitong Ruan, Xinyue Liu +3
In a modern spoken language understanding (SLU) system, the natural language understanding (NLU) module takes interpretations of a speech from the automatic speech recognition (ASR…