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David Reitter

3 accepted papers

2022

CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning

EMNLP 2022main

Compared to standard retrieval tasks, passage retrieval for conversational question answering (CQA) poses new challenges in understanding the current user question, as each question needs to be interpreted within the dialogue context. Moreover, it can be expensive to re-train well-established retrie…

2022

Dungeons and Dragons as a Dialog Challenge for Artificial Intelligence

EMNLP 2022main

AI researchers have posited Dungeons and Dragons (D&D) as a challenge problem to test systems on various language-related capabilities. In this paper, we frame D&D specifically as a dialogue system challenge, where the tasks are to both generate the next conversational turn in the game and predict t…

Cited by 48SourcePDFScholar
2021

Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features

ACL 2021long

Knowledge-grounded dialogue systems are intended to convey information that is based on evidence provided in a given source text. We discuss the challenges of training a generative neural dialogue model for such systems that is controlled to stay faithful to the evidence. Existing datasets contain a…

Cited by 115SourcePDFScholar