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cs.AI2024
MMMT-IF: A Challenging Multimodal Multi-Turn Instruction Following Benchmark
Elliot L. Epstein, Kaisheng Yao, Jing Li +2
Evaluating instruction following capabilities for multimodal, multi-turn dialogue is challenging. With potentially multiple instructions in the input model context, the task is tim…
cs.CL2024★ 3 cited
Unveiling the Impact of Multi-Modal Interactions on User Engagement: A Comprehensive Evaluation in AI-driven Conversations
Lichao Zhang, Jia Yu, Shuai Zhang +10
Large Language Models (LLMs) have significantly advanced user-bot interactions, enabling more complex and coherent dialogues. However, the prevalent text-only modality might not fu…