Browse › Natural Language Processing › Question Answering › MultiRC
MultiRC Benchmark (Question Answering)
Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.
The archive carries no text for this table; the description above is the archive's text for the task Question Answering. archive 2025-07-28
Over time archive 2025-07-28
The chart needs JavaScript; the table below carries every value.
Direction inferred from the metric name, not from the archive: F1 (higher is better). Not inferred (points only, no best-so-far line): EM. Points are placed at the row's paper date; 30 of 30 rows carry one.
Results archive 2025-07-28
Archive rows end at the archive snapshot, 2025-07-28: no result published after that date is in this table. Rank is the archive's row order at that snapshot; not re-ranked here. Metric values are the archive's strings. Column headers sort the table in your browser; each row keeps its archive rank.
| Paper | Code | Ran Syntology | Report | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | PaLM 540B (finetuned) | 90.1 | 69.2 | – | Paper | Code | 2022 | 30 of 37 ran · 7 unverified | report |
| 2 | ST-MoE-32B 269B (fine-tuned) | 89.6 | – | Paper | Code | 2022 | 5 of 5 ran · 0 unverified | report | |
| 3 | Turing NLR v5 XXL 5.4B (fine-tuned) | 88.4 | 63 | – | Paper | – | 2022 | no code linked | report |
| 4 | DeBERTa-1.5B | 88.2 | 63.7 | – | Paper | Code | 2020 | 4 of 13 ran · 9 unverified | report |
| 5 | Vega v2 6B (fine-tuned) | 88.2 | 62.4 | – | Paper | – | 2022 | no code linked | report |
| 6 | PaLM 2-L (one-shot) | 88.2 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 7 | T5-XXL 11B (fine-tuned) | 88.1 | – | Paper | Code | 2019 | 2 of 31 ran · 29 unverified | report | |
| 8 | ST-MoE-L 4.1B (fine-tuned) | 86 | – | Paper | Code | 2022 | 5 of 5 ran · 0 unverified | report | |
| 9 | PaLM 2-M (one-shot) | 84.1 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 10 | PaLM 2-S (one-shot) | 84.0 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 11 | FLAN 137B (prompt-tuned) | 83.4 | – | Paper | Code | 2021 | 0 of 1 ran · 1 unverified | report | |
| 12 | FLAN 137B (zero-shot) | 77.5 | – | Paper | Code | 2021 | 0 of 1 ran · 1 unverified | report | |
| 13 | GPT-3 175B (Few-Shot) | 75.4 | – | Paper | Code | 2020 | 15 of 65 ran · 50 unverified | report | |
| 14 | FLAN 137B (1-shot) | 72.1 | – | Paper | Code | 2021 | 0 of 1 ran · 1 unverified | report | |
| 15 | KELM (finetuning BERT-large based single model) | 70.8 | 27.2 | – | Paper | Code | 2021 | 1 of 6 ran · 5 unverified | report |
| 16 | BERT-large(single model) | 70.0 | 24.1 | – | Paper | Code | 2018 | 204 of 659 ran · 455 unverified | report |
| 17 | Neo-6B (QA + WS) | 63.8 | – | Paper | Code | 2022 | 2 of 2 ran · 0 unverified | report | |
| 18 | Bloomberg GPT 50B (1-shot) | 62.3 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 19 | N-Grammer 343M | 62 | 11.3 | – | Paper | Code | 2022 | 0 of 6 ran · 6 unverified | report |
| 20 | Neo-6B (few-shot) | 60.8 | – | Paper | Code | 2022 | 2 of 2 ran · 0 unverified | report | |
| 21 | AlexaTM 20B | 59.6 | – | Paper | Code | 2022 | 1 of 1 ran · 0 unverified | report | |
| 22 | Neo-6B (QA) | 58.8 | – | Paper | Code | 2022 | 2 of 2 ran · 0 unverified | report | |
| 23 | BLOOM 176B (1-shot) | 26.7 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 24 | GPT-NeoX 20B (1-shot) | 22.9 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 25 | OPT 66B (1-shot) | 18.8 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 26 | T5-11B | 63.3 | – | Paper | Code | 2019 | 2 of 31 ran · 29 unverified | report | |
| 27 | Hybrid H3 355M (3-shot, logit scoring) | 59.7 | – | Paper | Code | 2022 | 7 of 15 ran · 8 unverified | report | |
| 28 | Hybrid H3 355M (0-shot, logit scoring) | 59.5 | – | Paper | Code | 2022 | 7 of 15 ran · 8 unverified | report | |
| 29 | Hybrid H3 125M (0-shot, logit scoring) | 51.4 | – | Paper | Code | 2022 | 7 of 15 ran · 8 unverified | report | |
| 30 | Hybrid H3 125M (3-shot, logit scoring) | 48.9 | – | Paper | Code | 2022 | 7 of 15 ran · 8 unverified | report |
All 30 rows shown. 30 link to a paper page on this site; 0 are marked as using additional training data in the archive. No GitHub stars are tracked; "Code" is the first repository the archive lists for the row. The archive carries no row tags, review links or community-submitted rows for this table; none are shown. archive 2025-07-28
Syntology Ran reads "N of M ran · U unverified": of the M code samples Syntology harvested from repositories linked to that row's paper (joined by arXiv id), N executed on a synthesized input and the other U = M−N are unverified (harvested, no recorded run). It counts code from repositories linked to that row's paper, not this result: the row's number was not reproduced and nothing here is a correctness claim. The other cell texts mean no graph line for the row: "linked, not harvested" (the archive links code, Syntology has not harvested it), "no code linked" (no code link in the archive), "not matched" (the row's paper URL matched no paper on this site). 21 rows have a graph line, from 12 distinct papers; 17 rows (10 papers) have at least one sample that ran. Counting each paper once: Syntology ran 271 of 841 samples; 570 unverified. Separately, 161 of those 841 are pointer-only (licence): the site points at that code rather than redistributing it, a licence property recorded for ran and unverified samples alike; each cell's tooltip carries the row's own pointer-only count. Read from the graph 2026-09-24. Per-sample status is on the paper page.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections