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Evaluation of Question Answering Systems: Complexity of Judging a Natural Language

https://doi.org/10.1145/3744663
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/widm.1303openalex-snapshot
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Simplifying Paragraph-Level Question Generation via Transformer Language Models
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inferredcites →https://doi.org/10.1007/s11023-020-09548-1openalex-snapshot
GPT-3: Its Nature, Scope, Limits, and Consequences
inferredcites →https://doi.org/10.1016/j.cviu.2017.05.001openalex-snapshot
Visual question answering: A survey of methods and datasets
inferredcites →https://doi.org/10.1016/j.eswa.2017.03.006openalex-snapshot
Enhanced question understanding with dynamic memory networks for textual question answering
inferredcites →https://doi.org/10.1016/j.ins.2011.07.047openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.jksuci.2014.10.007openalex-snapshot
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Learning to ask relevant questions
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Natural language interfaces to databases – an introduction
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Building applied natural language generation systems
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inferredcites →https://doi.org/10.1073/pnas.92.22.9977openalex-snapshot
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Temporal Reasoning via Audio Question Answering
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Baseball
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From Question to Text
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A Review on Question Generation from Natural Language Text
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A Survey of Evaluation Metrics Used for NLG Systems
inferredcites →https://doi.org/10.1145/3560260openalex-snapshot
QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension
inferredcites →https://doi.org/10.1147/jrd.2012.2184356openalex-snapshot
Introduction to “This is Watson”
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CoQA: A Conversational Question Answering Challenge
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Sentence Mover’s Similarity: Automatic Evaluation for Multi-Sentence Texts
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chrF: character n-gram F-score for automatic MT evaluation
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Blend: a Novel Combined MT Metric Based on Direct Assessment — CASICT-DCU submission to WMT17 Metrics Task
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RUSE: Regressor Using Sentence Embeddings for Automatic Machine Translation Evaluation
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Best practices for the human evaluation of automatically generated text
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Evaluating the Evaluators: Subjective Bias and Consistency in Human Evaluation of Natural Language Generation
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A Pilot Study of Biomedical Text Comprehension using an Attention-Based Deep Neural Reader: Design and Experimental Analysis
inferredcites →https://doi.org/10.24963/ijcai.2019openalex-snapshot
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inferredcites →https://doi.org/10.24963/ijcai.2021openalex-snapshot
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inferredcites →https://doi.org/10.3115/1073445.1073465openalex-snapshot
Automatic evaluation of summaries using N-gram co-occurrence statistics
inferredcites →https://doi.org/10.3115/1219840.1219866openalex-snapshot
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deltaBLEU: A Discriminative Metric for Generation Tasks with Intrinsically Diverse Targets
inferredcites →https://doi.org/10.3115/v1/w14-3354openalex-snapshot
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inferredcites →https://doi.org/10.3233/sw-140134openalex-snapshot
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inferredcites →https://doi.org/10.32604/cmc.2019.06045openalex-snapshot
Deep Feature Fusion Model for Sentence Semantic Matching
inferredcites →https://doi.org/10.3389/frai.2020.00004openalex-snapshot
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inferredcites →https://doi.org/10.5555/3241691.3241693openalex-snapshot
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Incoming claims: where this work appears in other papers’ reference lists and arguments.

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inferred← citeshttps://doi.org/10.1007/s44196-026-01497-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.engappai.2025.110997openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icsadl67539.2026.11451936openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3789692.3789784openalex-snapshot
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inferred← citeshttps://doi.org/10.17977/um018v6i22023p129-144openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/app16126156openalex-snapshot
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