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Sentence embeddings (e.g., SBERT) are powerful -- but we just don't know what is crammed into a %&!$# vector 😵💫.
💥So in our new paper, we use Abstract Meaning Representation (AMR) to make sentence embeddings more explainable! #AACL2022 #nlproc #MachineLearning (1/3)
💥So in our new paper, we use Abstract Meaning Representation (AMR) to make sentence embeddings more explainable! #AACL2022 #nlproc #MachineLearning (1/3)
Interesting: Yes, we use AMR -- but we don't need an AMR parser🤯. Therefore, we don't lose efficiency 🚀. The accuracy 🎯 is also preserved, and sometimes even improved (for argument similarity, we achieve a new state-of-the-art). (2/3)
