Comparison of the Intimacy Process between Real and Acting-based Long-term Text Chats (2024.lrec-main)
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| Challenge: | Recent open-domain chatbots can generate natural responses over multiple turns using large-scale language models, but they do not address the speaker intimacy process and thus cannot sustain natural dialogue over multiple days and weeks. |
| Approach: | They propose to train systems with multi-session chat data to simulate relationship-building between speakers. |
| Outcome: | The proposed multi-session chat data can simulate relationship-building between speakers but has not been tested in Japanese. |
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| Challenge: | open-domain chatbots focus on short single-session dialogue, neglecting the potential need for understanding contextual information in multiple consecutive sessions. |
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| Challenge: | Despite recent improvements in open-domain dialogue models, state of the art models are trained and evaluated on short conversations with little context. |
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| Challenge: | Existing studies on long-term open-domain dialogues focus on evaluating responses within contexts spanning no more than five chat sessions. |
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| Challenge: | Recent intelligent open-domain chatbots have made substantial progress thanks to the rapid development of large-scale pre-training approaches. |
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