Papers with dialogue analysis
Predicting Client Emotions and Therapist Interventions in Psychotherapy Dialogues (2024.eacl-long)
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| Challenge: | Recent studies have focused on the role of client emotions and therapist interventions in predicting treatment outcomes from psychotherapy dialogues. |
| Approach: | They propose to model the therapist-intervention-prediction-based dialogue acts at the utterance-level using a pan-theoretical schema and fine-tuned language models. |
| Outcome: | The proposed model predicts the coherence between client self-reports on emotion and utterance-level emotions. |
A Multi-source Graph Representation of the Movie Domain for Recommendation Dialogues Analysis (2022.lrec-1)
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| Challenge: | Graph databases are well-suited for crossreferencing information from multiple sources to support machine learning tasks. |
| Approach: | They propose a graph-based structure of multiple resources enriched with graph analytics approaches to provide an encompassing view of the movie recommendation domain and of the way people talk about it during the recommendation task. |
| Outcome: | The proposed graph-based structure provides an encompassing view of the domain and of the way people talk about it during the recommendation task. |
The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue (P19-1)
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| Challenge: | Using the PhotoBook dataset, we investigate shared dialogue history accumulating during conversation . human interlocutors are known to collaboratively establish a shared repository of mutual information during a conversation - this common ground is then used to optimise understanding and communication efficiency. |
| Approach: | They propose a data-collection task formulated as a collaborative game prompting two online participants to refer to images utilising both their visual context and previously established referring expressions. |
| Outcome: | The proposed model takes into account shared information accumulated in a reference chain and is important to resolve later descriptions. |
From Long Videos to Engaging Clips: A Human-Inspired Video Editing Framework with Multimodal Narrative Understanding (2025.emnlp-industry)
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Xiangfeng Wang, Xiao Li, Yadong Wei, null Songxueyu, Yang Song, null Xiaxiaoqiang, Fangrui Zeng, Zaiyi Chen, null Liuliu, Gu Xu, Tong Xu
| Challenge: | Existing methods for video editing rely on textual cues from ASR transcripts and segment selection, often neglecting rich visual context. |
| Approach: | They propose a human-inspired automatic video editing framework that leverages multimodal narrative understanding to address these limitations. |
| Outcome: | The proposed framework outperforms existing baselines across general and advertisement-oriented editing tasks. |
MultiAgentESC: A LLM-based Multi-Agent Collaboration Framework for Emotional Support Conversation (2025.emnlp-main)
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| Challenge: | Existing studies focus on generating responses directly and neglect integration of domain-specific reasoning and expert interaction. |
| Approach: | They propose a training-free multi-agent collaboration framework for ESC to emulate human-like process of providing emotional support through dialogue analysis, strategy deliberation, and response generation. |
| Outcome: | The proposed framework excels at providing emotional support and diversifying support strategy selection. |
When did you become so smart, oh wise one?! Sarcasm Explanation in Multi-modal Multi-party Dialogues (2022.acl-long)
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| Challenge: | Indirect speech achieves a constellation of discourse goals in human communication, but it is challenging for AI agents to comprehend such idiosyncrasies. |
| Approach: | They propose a task to generate natural language explanations of satirical conversations using a multimodal and code-mixed dataset to capture multimodality. |
| Outcome: | The proposed task generates natural language explanations of satirical conversations in a multimodal and code-mixed setting and surpasses baselines on almost all metrics. |