Differences

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--- nlp:question_answering [2024/07/31 01:12] – [General QA Papers] jmflanig
+++ nlp:question_answering [2025/05/13 19:46] (current) – [Overviews] jmflanig
@@ Line 6: / Line 6: @@
   * **[[https://arxiv.org/ftp/arxiv/papers/2001/2001.01582.pdf|Baradaran et al 2020 - A Survey on Machine Reading Comprehension Systems]]**
   * [[https://arxiv.org/pdf/2010.00389.pdf|Thayaparan et al 2020 - A Survey on Explainability in Machine Reading Comprehension]]
-  * **[[https://arxiv.org/pdf/2107.12708.pdf|Rogers et al 2022 - QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension]]**
+  * **[[https://arxiv.org/pdf/2107.12708.pdf|Rogers et al 2022 - QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension]]** [[https://dl.acm.org/doi/pdf/10.1145/3560260|ACM version (better)]]
 ===== Demos =====
   * [[https://demo.allennlp.org/reading-comprehension/transformer-qa|AllenNLP - RoBERTa QA Model Online Demo]]
@@ Line 32: / Line 32: @@
   * [[https://arxiv.org/pdf/2101.02235.pdf|Geva et al 2021 - Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies]]
   * [[https://arxiv.org/pdf/2104.08661.pdf|Dalvi et al 2021 - Explaining Answers with Entailment Trees]]
+===== QA with Attribution =====
+  * [[https://arxiv.org/pdf/2212.08037|Bohnet et al 2022 - Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models]]
 ===== Robust Question Answering =====
-  * [[https://arxiv.org/pdf/2004.14648.pdf|Robust Question Answering Through Sub-part Alignment]]
+  * [[https://arxiv.org/pdf/2004.14648.pdf|Chen & Durrett 2020 - Robust Question Answering Through Sub-part Alignment]]
 ===== Open-Domain Question Answering =====