31 citations · 69 across the 5 of their papers we have counts for
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cs.CL2023★ 2 cited
Multi-Task End-to-End Training Improves Conversational Recommendation
Naveen Ram, Dima Kuzmin, Ellie Ka In Chio +4
In this paper, we analyze the performance of a multitask end-to-end transformer model on the task of conversational recommendations, which aim to provide recommendations based on a…
cs.CL2023★ 3 cited
MAQA: A Multimodal QA Benchmark for Negation
Judith Yue Li, Aren Jansen, Qingqing Huang +3
Multimodal learning can benefit from the representation power of pretrained Large Language Models (LLMs). However, state-of-the-art transformer based LLMs often ignore negations in…