QFE

Reported on 6 benchmarks across 1 task · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing6 results

Question AnsweringonHotpotQA
ANS-EM· 2019-05-21
0.287
best: 0.727 (Beam Retrieval)
Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction arXiv:1905.08511
Question AnsweringonHotpotQA
ANS-F1· 2019-05-21
0.381
best: 0.85 (Beam Retrieval)
Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction arXiv:1905.08511
Question AnsweringonHotpotQA
JOINT-EM· 2019-05-21
0.087
best: 0.505 (Beam Retrieval)
Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction arXiv:1905.08511
Question AnsweringonHotpotQA
JOINT-F1· 2019-05-21
0.231
best: 0.775 (Beam Retrieval)
Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction arXiv:1905.08511
Question AnsweringonHotpotQA
SUP-EM· 2019-05-21
0.142
best: 0.663 (Beam Retrieval)
Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction arXiv:1905.08511
Question AnsweringonHotpotQA
SUP-F1· 2019-05-21
0.444
best: 0.901 (Beam Retrieval)
Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction arXiv:1905.08511