Open-Domain Question Answering

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

15 leaderboard tables shown for this task, 15 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 15 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

26 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 238 papers with code (494 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
  29 Oct 2019 47 repositories listed Syntology ran 22 of 53 samples · 31 unverified · 7 pointer-only (licence)
  We evaluate a number of noising approaches, finding the best performance by both randomly shuffling the order of the original sentences and using a novel in-filling scheme, where spans of text are replaced with a single…
• Bidirectional Attention Flow for Machine Comprehension
  5 Nov 2016 27 repositories listed Syntology ran 8 of 11 samples · 3 unverified · 7 pointer-only (licence)
  Machine comprehension (MC), answering a query about a given context paragraph, requires modeling complex interactions between the context and the query.
• Dense Passage Retrieval for Open-Domain Question Answering
  10 Apr 2020 19 repositories listed Syntology ran 10 of 14 samples · 4 unverified · 9 pointer-only (licence)
  Open-domain question answering relies on efficient passage retrieval to select candidate contexts, where traditional sparse vector space models, such as TF-IDF or BM25, are the de facto method.
• Reformer: The Efficient Transformer
  13 Jan 2020 10 repositories listed Syntology ran 6 of 8 samples · 2 unverified
  Large Transformer models routinely achieve state-of-the-art results on a number of tasks but training these models can be prohibitively costly, especially on long sequences.
• Reading Wikipedia to Answer Open-Domain Questions
  31 Mar 2017 10 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  This paper proposes to tackle open- domain question answering using Wikipedia as the unique knowledge source: the answer to any factoid question is a text span in a Wikipedia article.
• Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering
  2 Jul 2020 8 repositories listed
  Generative models for open domain question answering have proven to be competitive, without resorting to external knowledge.
• Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
  10 Nov 2019 7 repositories listed Syntology ran 4 of 6 samples · 2 unverified · 4 pointer-only (licence)
  We introduce an approach for open-domain question answering (QA) that retrieves and reads a passage graph, where vertices are passages of text and edges represent relationships that are derived from an external…
• Generating Long Sequences with Sparse Transformers
  23 Apr 2019 7 repositories listed Syntology ran 5 of 6 samples · 1 unverified
  Transformers are powerful sequence models, but require time and memory that grows quadratically with the sequence length.
• REALM: Retrieval-Augmented Language Model Pre-Training
  10 Feb 2020 6 repositories listed Syntology ran 4 of 4 samples · 0 unverified
  Language model pre-training has been shown to capture a surprising amount of world knowledge, crucial for NLP tasks such as question answering.
• SpanBERT: Improving Pre-training by Representing and Predicting Spans
  24 Jul 2019 6 repositories listed Syntology ran 3 of 15 samples · 12 unverified · 4 pointer-only (licence)
  We present SpanBERT, a pre-training method that is designed to better represent and predict spans of text.
• Relevance-guided Supervision for OpenQA with ColBERT
  1 Jul 2020 5 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  In much recent work, the retriever is a learned component that uses coarse-grained vector representations of questions and passages.
• Reducing Transformer Depth on Demand with Structured Dropout
  25 Sep 2019 5 repositories listed
  Overparameterized transformer networks have obtained state of the art results in various natural language processing tasks, such as machine translation, language modeling, and question answering.
• Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval
  12 Oct 2021 4 repositories listed Syntology ran 5 of 22 samples · 17 unverified
  However, the efficiency of most existing DR models is limited by the large memory cost of storing dense vectors and the time-consuming nearest neighbor search (NNS) in vector space.
• Learning Dense Representations of Phrases at Scale
  23 Dec 2020 4 repositories listed
  Open-domain question answering can be reformulated as a phrase retrieval problem, without the need for processing documents on-demand during inference (Seo et al., 2019).
• Distilling Knowledge from Reader to Retriever for Question Answering
  8 Dec 2020 4 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  A challenge of using such methods is to obtain supervised data to train the retriever model, corresponding to pairs of query and support documents.
• ktrain: A Low-Code Library for Augmented Machine Learning
  19 Apr 2020 4 repositories listed Syntology ran 0 of 16 samples · 16 unverified
  We present ktrain, a low-code Python library that makes machine learning more accessible and easier to apply.
• Break It Down: A Question Understanding Benchmark
  31 Jan 2020 4 repositories listed
  Understanding natural language questions entails the ability to break down a question into the requisite steps for computing its answer.
• Gated-Attention Readers for Text Comprehension
  5 Jun 2016 4 repositories listed Syntology ran 1 of 3 samples · 2 unverified
  In this paper we study the problem of answering cloze-style questions over documents.
• ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction
  2 Dec 2021 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Neural information retrieval (IR) has greatly advanced search and other knowledge-intensive language tasks.
• Answer Complex Questions: Path Ranker Is All You Need
  11 Jul 2021 3 repositories listed
  Currently, the most popular method for open-domain Question Answering (QA) adopts "Retriever and Reader" pipeline, where the retriever extracts a list of candidate documents from a large set of documents followed by a…
• Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study
  7 Jun 2021 3 repositories listed
  Recent advancements in open-domain question answering (ODQA), i.
• What Makes Good In-Context Examples for GPT-$3$?
  17 Jan 2021 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Inspired by the recent success of leveraging a retrieval module to augment large-scale neural network models, we propose to retrieve examples that are semantically-similar to a test sample to formulate its corresponding…
• What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
  28 Sep 2020 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Open domain question answering (OpenQA) tasks have been recently attracting more and more attention from the natural language processing (NLP) community.
• KILT: a Benchmark for Knowledge Intensive Language Tasks
  4 Sep 2020 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  We test both task-specific and general baselines, evaluating downstream performance in addition to the ability of the models to provide provenance.
• Contextualized Sparse Representations for Real-Time Open-Domain Question Answering
  7 Nov 2019 3 repositories listed Syntology ran 10 of 18 samples · 8 unverified
  Open-domain question answering can be formulated as a phrase retrieval problem, in which we can expect huge scalability and speed benefit but often suffer from low accuracy due to the limitation of existing phrase…
• ERNIE 2.0: A Continual Pre-training Framework for Language Understanding
  29 Jul 2019 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  Recently, pre-trained models have achieved state-of-the-art results in various language understanding tasks, which indicates that pre-training on large-scale corpora may play a crucial role in natural language…
• ELI5: Long Form Question Answering
  22 Jul 2019 3 repositories listed Syntology ran 4 of 11 samples · 7 unverified · 4 pointer-only (licence)
  We introduce the first large-scale corpus for long-form question answering, a task requiring elaborate and in-depth answers to open-ended questions.
• Latent Retrieval for Weakly Supervised Open Domain Question Answering
  1 Jun 2019 3 repositories listed
  We show for the first time that it is possible to jointly learn the retriever and reader from question-answer string pairs and without any IR system.
• Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question Answering
  28 Aug 2018 3 repositories listed
  In this paper we propose a retriever-reader model that learns to attend on essential terms during the question answering process.
• SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine
  18 Apr 2017 3 repositories listed
  We publicly release a new large-scale dataset, called SearchQA, for machine comprehension, or question-answering.

Syntology lines on 21 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.