Research map / Large language models / Language, safety and interpretability
Mechanism-Aware Neural Machine for Dialogue Response Generation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add mechanism-aware diverter with latent responding mechanisms | RNNencdec · Tencent Weibo human eval | Top-5 acceptable %: 53.13 -> 64.40 | Helped |
| MARM vs best baseline MMI-bidi | dialogue generation · Tencent Weibo human eval | Top-5 acceptable %: 54.60 -> 64.40 | Helped |
| add mechanism-aware diverter | RNNencdec · Tencent Weibo human eval | diversity: 1.183 -> 2.687 | Helped |
| add attention to encoder-decoder | RNNencdec · Tencent Weibo human eval | Top-5 acceptable %: 53.13 -> 45.13 | Hurt |
Closest papers by meaning
- A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues (AAAI 2017 · similarity 0.91)
- Elastic Responding Machine for Dialog Generation with Dynamically Mechanism Selecting (AAAI 2018 · similarity 0.90)
- Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models (AAAI 2016 · similarity 0.90)
- DialogBERT: Discourse-Aware Response Generation via Learning to Recover and Rank Utterances (AAAI 2021 · similarity 0.89)
- Zero-Resource Knowledge-Grounded Dialogue Generation (NeurIPS 2020 · similarity 0.88)
- From Retrieval to Generation: A Simple and Unified Generative Model for End-to-End Task-Oriented Dialogue (AAAI 2024 · similarity 0.87)
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