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--- |
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license: apache-2.0 |
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datasets: |
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- Nuo97/Dolphin-DPO |
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language: |
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- zh |
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metrics: |
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- bleu |
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pipeline_tag: conversational |
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--- |
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# COMEDY: COmpressive Memory-Enhanced Dialogue sYstems framework. |
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Github: https://github.com/nuochenpku/COMEDY |
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<br> |
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<div align="center"> |
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<img src="comedy.png" width="40%" title="Introduction Figure"> |
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</div> |
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### Task: Long-Term Conversation Dialogue Generation |
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Different from previous retrieval-based methods, COMEDY doesn't rely on any **retrieval module or database**. |
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Instead, COMEDY adopts a groundbreaking ''**One-for-All**'' approach, utilizing a single, unified model to manage the entire process from memory generation, compression to final response generation for long-term memory dialogue generation. |
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- COMEDY firstly involves distilling session-specific memory from past dialogues, encompassing fine-grained session summaries, including event recaps, and detailed user and bot portraits; |
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- In a break from traditional systems, COMEDY eschews the use of a memory database for storing these insights. Instead, it reprocesses and condenses memories from all past interactions, forming a *Compressive Memory*: The first part is the **concise events** that have occurred throughout all the conversations, creating a historical narrative that the system can draw upon. The second and third parts consist of a **detailed user profile** and the **dynamic relationship changes** between the user and chatbot across sessions, both derived from past conversational events. |
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- Finally, COMEDY skillfully integrates this compressive memory into ongoing conversations, enabling contextually memory-enhanced interactions. |
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### Training Dataset |
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**Dolphin**, the biggest Chinese long-term conversation dataset, from actual online user-chatbot interactions. |
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This dataset contains three tasks: |
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**Session-Level Memory Summarization**; |
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**Memory Compression**; |
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**Memory-Grounded Response Generation**, |
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comprising an extensive collection of 100k samples. |
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Dolphin is available at [**Dolphin**](https://huggingface.co/datasets/Nuo97/Dolphin-DPO) |
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### Training Strategy |
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Our training strategies include two stages: Mixed-task training and DPO Alignment. |
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<br> |
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<div align="center"> |
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<img src="training_strategy.png" width="90%" title="Introduction Figure"> |
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</div> |
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