Papers by Andrew Dai

2 papers
AirDialogue: An Environment for Goal-Oriented Dialogue Research (D18-1)

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Challenge: Recent advances in dialogue generation have inspired a number of studies on dialogue systems . however, current datasets are limited in size and the environment for training agents is relatively unsophisticated.
Approach: They propose to use a context-generator to generate travel and flight restrictions to train agents.
Outcome: The proposed model achieves a score of 0.17 while humans can reach 0.91 . the proposed model is based on a large dataset that contains 301,427 goal-oriented conversations .
PaRaDe: Passage Ranking using Demonstrations with LLMs (2023.findings-emnlp)

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Challenge: Existing studies show that large language models can be instructed to perform zero-shot passage re-ranking . Existing work like UPR demonstrate promising results for zero- shot ranking using LLMs .
Approach: They propose a demonstration selection strategy based on difficulty rather than semantic similarity . they propose to include only one demonstration in the prompt to improve re-ranking .
Outcome: The proposed method improves LLM-based re-ranking by adding one demonstration to the prompt.

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