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diff --git a/amu-literature.bib b/amu-literature.bib
index 786077c9882f193aa627150126a18693fb454388..d414025a688f52195d8e871121accda67ac1554b 100644
--- a/amu-literature.bib
+++ b/amu-literature.bib
@@ -1484,6 +1484,72 @@
url = {https://api.semanticscholar.org/CorpusID:276725396},
}
+@Article{liu2024ai,
+ author = {Liu, Xurong and Kong, Leilei},
+ journal = {Working notes of clef},
+ title = {AI text detection method based on perplexity features with strided sliding window},
+ year = {2024},
+ file = {:paper-261.pdf:PDF},
+ groups = {evaluation},
+}
+
+@InProceedings{wu-etal-2024-perplexing,
+ author = {Wu, Yaru and Bizzoni, Yuri and Moreira, Pascale and Nielbo, Kristoffer},
+ booktitle = {Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2024)},
+ title = {Perplexing Canon: A study on {GPT}-based perplexity of canonical and non-canonical literary works},
+ year = {2024},
+ address = {St. Julians, Malta},
+ editor = {Bizzoni, Yuri and Degaetano-Ortlieb, Stefania and Kazantseva, Anna and Szpakowicz, Stan},
+ month = mar,
+ pages = {172--184},
+ publisher = {Association for Computational Linguistics},
+ abstract = {This study extends previous research on literary quality by using information theory-based methods to assess the level of perplexity recorded by three large language models when processing 20th-century English novels deemed to have high literary quality, recognized by experts as canonical, compared to a broader control group. We find that canonical texts appear to elicit a higher perplexity in the models, we explore which textual features might concur to create such an effect. We find that the usage of a more heavily nominal style, together with a more diverse vocabulary, is one of the leading causes of the difference between the two groups. These traits could reflect {\textquotedblleft}strategies{\textquotedblright} to achieve an informationally dense literary style.},
+ file = {:2024.latechclfl-1.16.pdf:PDF},
+ groups = {evaluation, read-asap, comparison-literary-texts},
+ ranking = {rank5},
+ url = {https://aclanthology.org/2024.latechclfl-1.16/},
+}
+
+@InProceedings{jacobsen2024patterns,
+ author = {Jacobsen, Mia and Bizzoni, Yuri and Moreira, Pascale Feldkamp and Nielbo, Kristoffer L},
+ booktitle = {Proceedings of the Computational Humanities Research Conference 2024},
+ title = {Patterns of Quality: Comparing Reader Reception Across Fanfiction and Commercially Published Literature},
+ year = {2024},
+ organization = {in CEUR Workshop Proceedings},
+ pages = {718--739},
+ volume = {3834},
+ file = {:paper106.pdf:PDF},
+ groups = {comparison-literary-texts},
+}
+
+@Article{bizzoni2024good,
+ author = {Bizzoni, Yuri and Feldkamp, Pascale and Lassen, Ida Marie and Jacobsen, Mia and Thomsen, Mads Rosendahl and Nielbo, Kristoffer},
+ journal = {arXiv preprint arXiv:2404.04022},
+ title = {Good books are complex matters: Gauging complexity profiles across diverse categories of perceived literary quality},
+ year = {2024},
+ file = {:bizzoni2024good - Good Books Are Complex Matters_ Gauging Complexity Profiles across Diverse Categories of Perceived Literary Quality.pdf:PDF:http\://arxiv.org/pdf/2404.04022v2},
+ groups = {comparison-literary-texts},
+}
+
+@InProceedings{bizzoni2024matter,
+ author = {Bizzoni, Yuri and Moreira, Pascale Feldkamp and Lassen, Ida Marie S and Thomsen, Mads Rosendahl and Nielbo, Kristoffer},
+ booktitle = {Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
+ title = {A matter of perspective: Building a multi-perspective annotated dataset for the study of literary quality},
+ year = {2024},
+ pages = {789--800},
+ file = {:2024.lrec-main.71.pdf:PDF},
+ groups = {comparison-literary-texts},
+}
+
+@Article{fang2024wrong,
+ author = {Fang, Lizhe and Wang, Yifei and Liu, Zhaoyang and Zhang, Chenheng and Jegelka, Stefanie and Gao, Jinyang and Ding, Bolin and Wang, Yisen},
+ journal = {arXiv preprint arXiv:2410.23771},
+ title = {What is Wrong with Perplexity for Long-context Language Modeling?},
+ year = {2024},
+ file = {:2410.23771v3.pdf:PDF},
+ groups = {evaluation},
+}
+
@Comment{jabref-meta: databaseType:bibtex;}
@Comment{jabref-meta: grouping:
diff --git a/bizzoni2024good - Good Books Are Complex Matters_ Gauging Complexity Profiles across Diverse Categories of Perceived Literary Quality.pdf b/bizzoni2024good - Good Books Are Complex Matters_ Gauging Complexity Profiles across Diverse Categories of Perceived Literary Quality.pdf
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