Summary of Synthdst: Synthetic Data Is All You Need For Few-shot Dialog State Tracking, by Atharva Kulkarni et al.
SynthDST: Synthetic Data is All You Need for Few-Shot Dialog State Tracking
by Atharva Kulkarni, Bo-Hsiang Tseng, Joel Ruben Antony Moniz, Dhivya Piraviperumal, Hong Yu, Shruti Bhargava
First submitted to arxiv on: 3 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed method, a data generation framework tailored for Dialog State Tracking (DST) utilizing Large Language Models (LLMs), addresses the challenge of efficiently generating synthetic data for few-shot prompting. By requiring only the dialogue schema and a few hand-crafted dialogue templates, our approach synthesizes natural, coherent, and free-flowing dialogues with DST annotations. This enables few-shot learning to achieve 4-5% improvement in Joint Goal Accuracy over the zero-shot baseline on MultiWOZ 2.1 and 2.4. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about using large language models to help computers understand conversations. Right now, we need a lot of labeled training data to make this work well, but that can be hard to get. Some people are working on zero-shot learning, which doesn’t require any training data, but it’s not as good as when we do have some data. The question is: “Can we find a way to create fake training data for any kind of conversation?” The answer is yes! We propose a new method that can generate synthetic dialogues with labels, just by knowing what the conversation should be about and a few examples of how it might go. This helps us learn quickly even with very little training data. |
Keywords
* Artificial intelligence * Few shot * Prompting * Synthetic data * Tracking * Zero shot
