text: 310,190,1359517751212138501,1117927926152990720,Ramon Astudillo,Are implicit word node-alignments useful for AMR parsing? They do help in multi-lingual settings!. We propose a multi-lingual AMR alignment method which applied to the stack-Transformer yields best results till date for multi-lingual AMR (EACL2021) <LINK> Work led by @JanakiSheth while interning at IBM!,https://arxiv.org/abs/2102.02189,"We develop high performance multilingualAbstract Meaning Representation (AMR) sys-tems by projecting English AMR annotationsto other languages with weak supervision. Weachieve this goal by bootstrapping transformer-based multilingual word embeddings, in partic-ular those from cross-lingual RoBERTa (XLM-R large). We develop a novel technique forforeign-text-to-English AMR alignment, usingthe contextual word alignment between En-glish and foreign language tokens. This wordalignment is weakly supervised and relies onthe contextualized XLM-R word embeddings.We achieve a highly competitive performancethat surpasses the best published results forGerman, Italian, Spanish and Chinese. ",Bootstrapping Multilingual AMR with Contextual Word Alignments,2,"['Are implicit word node-alignments useful for AMR parsing? They do help in multi-lingual settings!. We propose a multi-lingual AMR alignment method which applied to the stack-Transformer yields best results till date for multi-lingual AMR (EACL2021) <LINK>', 'Work led by @JanakiSheth while interning at IBM!']",21,02,304