Papers with PRISMA
A Modular Approach for Multimodal Summarization of TV Shows (2024.acl-long)
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| Challenge: | In this paper, we address the task of summarizing television shows, which touches key areas in AI research. |
| Approach: | They propose a modular approach where separate components perform specialized sub-tasks . they propose atomic facts to measure precision and recall of generated summaries . |
| Outcome: | The proposed method produces higher quality summaries than comparison models on a recently released dataset. |
An “Integrative Survey on Mental Health Conversational Agents to Bridge Computer Science and Medical Perspectives” (2023.emnlp-main)
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| Challenge: | Mental health conversational agents (a.k.a. chatbots) are widely studied for their potential to offer accessible support to those experiencing mental health challenges. |
| Approach: | They review 534 papers on building mental health-related conversational agents . they recommend a few recommendations to bridge the disciplinary divide . |
| Outcome: | The systematic review reveals 136 key papers on building mental health-related conversational agents with diverse characteristics of modeling and experimental design techniques. |
PersonalityDBench: A Dataset for Personality Disorders - from Modeling to Controlled Generation (2026.acl-long)
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| Challenge: | Personality disorders are chronic, rigid patterns of thinking, behavior, and emotions that deviate from cultural norms and persist in social settings. |
| Approach: | They propose a large-scale, clinically grounded dataset that supports multidimensional study of personality pathology and standardized evaluation of LLM steering toward clinically ground behavioral targets. |
| Outcome: | The PersonalityDBench dataset supports multidimensional study of personality pathology and evaluation of LLM steering toward clinically grounded behavioral targets. |
PRISMA: Preference-Reinforced Self-Training Approach for Interpretable Emotionally Intelligent Negotiation Dialogues (2026.acl-long)
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| Challenge: | Emotion plays a pivotal role in shaping negotiation outcomes, influencing trust, cooperation, and long-term relationships. |
| Approach: | They propose an Emotion-aware Negotiation Strategy-informed Chain-of-Thought reasoning mechanism which mimics human negotiation by perceiving, understanding, using, and managing emotions. |
| Outcome: | The proposed system generates interpretable emotions and improves negotiation effectiveness on job interviews and resource allocation datasets. |