Summary of Instruct Once, Chat Consistently in Multiple Rounds: An Efficient Tuning Framework For Dialogue, by Jian Wang et al.
Instruct Once, Chat Consistently in Multiple Rounds: An Efficient Tuning Framework for Dialogue
by Jian Wang, Chak Tou Leong, Jiashuo Wang, Dongding Lin, Wenjie Li, Xiao-Yong Wei
First submitted to arxiv on: 10 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 Midi-Tuning framework is an innovative approach to building capable dialogue agents by emphasizing the interactive nature of dialogue and modeling speaker roles separately. Unlike traditional tuning methods, which treat dialogue generation as a one-way language generation task, Midi-Tuning uses two adapters built upon large language models to model the agent and user individually. The adapters are tuned via a round-level memory caching mechanism, allowing for consistent adherence to role disparities between speakers. Experimental results demonstrate that Midi-Tuning outperforms traditional fine-tuning in terms of dialogue consistency. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re having a conversation with a chatbot. You type a message, and the bot responds. Then, you type another message, and the bot responds again. But what if the chatbot keeps saying things that don’t make sense or are completely off-topic? That’s because traditional chatbots are trained to generate language without considering the back-and-forth nature of conversations. Researchers have developed a new way to train chatbots that takes into account this interactive process. They propose an approach called Midi-Tuning, which models two speakers – you and the chatbot – separately. This allows the chatbot to be more consistent in its responses and have a more natural conversation with you. |
Keywords
» Artificial intelligence » Fine tuning
