Papers with reading process
GECO-MT: The Ghent Eye-tracking Corpus of Machine Translation (2022.lrec-1)
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| Challenge: | Despite improvements in machine translation output, remarkable differences can be observed when comparing machine translations (MT) and human translations. |
| Approach: | They describe a corpus of eye movement data collected during natural reading of a human translation and a machine translation of . they use this corpus to investigate the effect of machine translation on the reading process and the effects of various error types on reading. |
| Outcome: | The proposed corpus will be used in future research to investigate the effect of machine translation on the reading process and the effects of various error types on reading. |
Syntopical Graphs for Computational Argumentation Tasks (2021.acl-long)
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Joe Barrow, Rajiv Jain, Nedim Lipka, Franck Dernoncourt, Vlad Morariu, Varun Manjunatha, Douglas Oard, Philip Resnik, Henning Wachsmuth
| Challenge: | adler and van Doren (1940) proposed a formalized manual process for understanding a topic based on multiple viewpoints. |
| Approach: | They propose a syntopical reading process that emphasizes comparing and contrasting viewpoints to improve topic understanding. |
| Outcome: | The proposed method outperforms approaches that do not use collection-level information. |
Answering Ambiguous Questions via Iterative Prompting (2023.acl-long)
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| Challenge: | Empirical studies show that AmbigPrompt achieves state-of-the-art or competitive results while using less memory and having a lower inference latency than competing approaches. |
| Approach: | They propose an answering model with a prompting model to address imperfections in open-domain question answering . Empirical studies show AmbigPrompt achieves state-of-the-art or competitive results . |
| Outcome: | The proposed framework improves on two commonly-used open benchmarks and achieves state-of-the-art or competitive results while using less memory and having a lower inference latency. |