Papers with multi-party conversations
Is ChatGPT a Good Multi-Party Conversation Solver? (2023.findings-emnlp)
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| Challenge: | Large Language Models (LLMs) are powerful tools for multi-party conversations, but their capacity to handle multi-parties remains unexplored. |
| Approach: | They propose to evaluate ChatGPT and GPT-4's zero-shot learning capabilities within the context of multi-party conversations (MPCs) they also propose to incorporate MPC structures, encompassing both speaker and addressee architecture. |
| Outcome: | The proposed models perform poorly on a number of MPC tasks while GPT-4 performs well on speaker and addressee architecture. |
MuCDN: Mutual Conversational Detachment Network for Emotion Recognition in Multi-Party Conversations (2022.coling-1)
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| Challenge: | Emotion recognition in multi-party conversations is a challenging task that predicts the emotion for each utterance. |
| Approach: | They propose to separate conversations into detached threads to capture emotional clues in conversational context . they propose to use mutual detachment networks to perform context and speaker-specific modeling within detached thread. |
| Outcome: | The proposed model outperforms baseline models on two datasets. |
GIFT: Graph-Induced Fine-Tuning for Multi-Party Conversation Understanding (2023.acl-long)
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| Challenge: | Existing methods on understanding multi-party conversations typically embed interlocutors and utterances into sequential information flows or use superficial graph structures. |
| Approach: | They propose a plug-and-play method which adapts Transformer-based pre-trained language models for universal MPC understanding. |
| Outcome: | The proposed method can adapt Transformer-based pre-trained language models for universal MPC understanding. |
Persona-aware Multi-party Conversation Response Generation (2024.lrec-main)
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| Challenge: | Recent advances in natural language generation have addressed multi-turn dialogues . interactions with more than 2 participants pose new and interesting challenges for MPC modeling . |
| Approach: | They propose to include persona attributes of speaker and addressee relevant to each utterance in a multi-party conversation dataset and a persona-aware heterogeneous graph transformer response generation model. |
| Outcome: | The proposed model includes persona attributes of speaker and addressee relevant to each utterance. |