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cs.CL2024
MADial-Bench: Towards Real-world Evaluation of Memory-Augmented Dialogue Generation
Junqing He, Liang Zhu, Rui Wang +3
Long-term memory is important for chatbots and dialogue systems (DS) to create consistent and human-like conversations, evidenced by numerous developed memory-augmented DS (MADS).…
cs.CL2024
CAPE: A Chinese Dataset for Appraisal-based Emotional Generation using Large Language Models
June M. Liu, He Cao, Renliang Sun +3
Generating emotionally appropriate responses in conversations with large language models presents a significant challenge due to the complexities of human emotions and cognitive pr…
cs.CL2024
Fostering Natural Conversation in Large Language Models with NICO: a Natural Interactive COnversation dataset
Renliang Sun, Mengyuan Liu, Shiping Yang +3
Benefiting from diverse instruction datasets, contemporary Large Language Models (LLMs) perform effectively as AI assistants in collaborating with humans. However, LLMs still strug…