% Use this file for citations not found in the ACL Anthology (contained in "anthology.bib").

@book{Aho:72,
    author  = {Alfred V. Aho and Jeffrey D. Ullman},
    title   = {The Theory of Parsing, Translation and Compiling},
    year    = "1972",
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    address = {Englewood Cliffs, NJ}
}
@article{jeyaraj2021mnet,
  title={MNet-Sim: A Multi-layered Semantic Similarity Network to Evaluate Sentence Similarity},
  author={Jeyaraj, Manuela Nayantara and Kasthurirathna, Dharshana},
  journal={arXiv preprint arXiv:2111.05412},
  year={2021}
}
%requested citations
@inproceedings{asaadi2019big,
  title={Big BiRD: A large, fine-grained, bigram relatedness dataset for examining semantic composition},
  author={Asaadi, Shima and Mohammad, Saif and Kiritchenko, Svetlana},
  booktitle={Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)},
  pages={505--516},
  year={2019}
}
@article{merkx2021semantic,
  title={Semantic sentence similarity: size does not always matter},
  author={Merkx, Danny and Frank, Stefan L and Ernestus, Mirjam},
  journal={arXiv preprint arXiv:2106.08648},
  year={2021}
}
@article{hammerl2023exploring,
  title={Exploring Anisotropy and Outliers in Multilingual Language Models for Cross-Lingual Semantic Sentence Similarity},
  author={H{\"a}mmerl, Katharina and Fastowski, Alina and Libovick{\`y}, Jind{\v{r}}ich and Fraser, Alexander},
  journal={arXiv preprint arXiv:2306.00458},
  year={2023}
}
@article{wei2023synwmd,
  title={Synwmd: Syntax-aware word mover’s distance for sentence similarity evaluation},
  author={Wei, Chengwei and Wang, Bin and Kuo, C-C Jay},
  journal={Pattern Recognition Letters},
  volume={170},
  pages={48--55},
  year={2023},
  publisher={Elsevier}
}
@article{abdalla2021makes,
  title={What makes sentences semantically related: A textual relatedness dataset and empirical study},
  author={Abdalla, Mohamed and Vishnubhotla, Krishnapriya and Mohammad, Saif M},
  journal={arXiv preprint arXiv:2110.04845},
  year={2021}
}
@book{APA:83,
    author  = {{American Psychological Association}},
    title   = {Publications Manual},
    year    = "1983",
    publisher = {American Psychological Association},
    address = {Washington, DC}
}

@article{Chandra:81,
	author = {Ashok K. Chandra and Dexter C. Kozen and Larry J. Stockmeyer},
	year = "1981",
	title = {Alternation},
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}

@inproceedings{andrew2007scalable,
  title={Scalable training of {$L_1$}-regularized log-linear models},
  author={Andrew, Galen and Gao, Jianfeng},
  booktitle={Proceedings of the 24th International Conference on Machine Learning},
  pages={33--40},
  year={2007},
  url={https://dl.acm.org/doi/abs/10.1145/1273496.1273501}
}

@book{Gusfield:97,
    author  = {Dan Gusfield},
    title   = {Algorithms on Strings, Trees and Sequences},
    year    = "1997",
    publisher = {Cambridge University Press},
    address = {Cambridge, UK},
    url={https://www.cambridge.org/core/books/algorithms-on-strings-trees-and-sequences/F0B095049C7E6EF5356F0A26686C20D3}
}

@article{rasooli-tetrault-2015,
    author    = {Mohammad Sadegh Rasooli and Joel R. Tetreault},
    title     = {Yara Parser: {A} Fast and Accurate Dependency Parser},
    journal   = {Computing Research Repository},
    volume    = {arXiv:1503.06733},
    year      = {2015},
    url       = {http://arxiv.org/abs/1503.06733},
    note    = {version 2}
}

@article{Ando2005,
	Acmid = {1194905},
	Author = {Ando, Rie Kubota and Zhang, Tong},
	Issn = {1532-4435},
	Issue_Date = {12/1/2005},
	Journal = {Journal of Machine Learning Research},
	Month = dec,
	Numpages = {37},
	Pages = {1817--1853},
	Publisher = {JMLR.org},
	Title = {A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data},
	Volume = {6},
	Year = {2005},
	url={https://www.jmlr.org/papers/volume6/ando05a/ando05a.pdf}
}

@article{ct1965,
  title={An algorithm for the machine calculation of complex {F}ourier series},
  author={Cooley, James W. and Tukey, John W.},
  journal={Mathematics of Computation},
  volume={19},
  number={90},
  pages={297--301},
  year={1965},
  url={https://www.ams.org/journals/mcom/1965-19-090/S0025-5718-1965-0178586-1/S0025-5718-1965-0178586-1.pdf}
}

@book{halliday2014cohesion,
  title={Cohesion in english},
  author={Halliday, Michael Alexander Kirkwood and Hasan, Ruqaiya},
  number={9},
  year={2014},
  publisher={Routledge}
}

@article{miller1991contextual,
  title={Contextual correlates of semantic similarity},
  author={Miller, George A and Charles, Walter G},
  journal={Language and cognitive processes},
  volume={6},
  number={1},
  pages={1--28},
  year={1991},
  publisher={Taylor \& Francis}
}
@article{scikit-learn,
  title={Scikit-learn: Machine Learning in {P}ython},
  author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
          and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
          and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
          Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
  journal={Journal of Machine Learning Research},
  volume={12},
  pages={2825--2830},
  year={2011}
}
@misc{semrel2024dataset,
      title={SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 14 Languages}, 
      author={Nedjma Ousidhoum and Shamsuddeen Hassan Muhammad and Mohamed Abdalla and Idris Abdulmumin and Ibrahim Said Ahmad and Sanchit Ahuja and Alham Fikri Aji and Vladimir Araujo and Abinew Ali Ayele and Pavan Baswani and Meriem Beloucif and Chris Biemann and Sofia Bourhim and Christine De Kock and Genet Shanko Dekebo and Oumaima Hourrane and Gopichand Kanumolu and Lokesh Madasu and Samuel Rutunda and Manish Shrivastava and Thamar Solorio and Nirmal Surange and Hailegnaw Getaneh Tilaye and Krishnapriya Vishnubhotla and Genta Winata and Seid Muhie Yimam and Saif M. Mohammad},
      year={2024},
      eprint={2402.08638},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
@article{sarzynska2021detecting,
  title={Detecting formal thought disorder by deep contextualized word representations},
  author={Sarzynska-Wawer, Justyna and Wawer, Aleksander and Pawlak, Aleksandra and Szymanowska, Julia and Stefaniak, Izabela and Jarkiewicz, Michal and Okruszek, Lukasz},
  journal={Psychiatry Research},
  volume={304},
  pages={114135},
  year={2021},
  publisher={Elsevier}
}
@inproceedings{reimers-2020-multilingual-sentence-bert,
  title = "Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation",
  author = "Reimers, Nils and Gurevych, Iryna",
  booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing",
  month = "11",
  year = "2020",
  publisher = "Association for Computational Linguistics",
  url = "https://arxiv.org/abs/2004.09813",
}


@inproceedings{semrel2024task, 
title = "{S}em{E}val-2024 Task 1: Semantic Textual Relatedness for African and Asian Languages",
author = "Ousidhoum, Nedjma and Muhammad, Shamsuddeen Hassan and Abdalla, Mohamed and Abdulmumin, Idris and
Ahmad,Ibrahim Said and Ahuja, Sanchit and Aji, Alham Fikri and Araujo, Vladimir and     Beloucif, Meriem and
De Kock, Christine and Hourrane, Oumaima and Shrivastava, Manish and Solorio, Thamar and Surange, Nirmal and
Vishnubhotla, Krishnapriya and Yimam, Seid Muhie and Mohammad, Saif M.",
booktitle = "Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)",
year = "2024",
publisher = "Association for Computational Linguistics"
}

@misc{ousidhoum2024semrel2024,
title={SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 14 Languages}, 
author={Nedjma Ousidhoum and Shamsuddeen Hassan Muhammad and Mohamed Abdalla and Idris Abdulmumin and Ibrahim Said Ahmad and
Sanchit Ahuja and Alham Fikri Aji and Vladimir Araujo and Abinew Ali Ayele and Pavan Baswani and Meriem Beloucif and
Chris Biemann and Sofia Bourhim and Christine De Kock and Genet Shanko Dekebo and
Oumaima Hourrane and Gopichand Kanumolu and Lokesh Madasu and Samuel Rutunda and Manish Shrivastava and
Thamar Solorio and Nirmal Surange and Hailegnaw Getaneh Tilaye and Krishnapriya Vishnubhotla and Genta Winata and
Seid Muhie Yimam and Saif M. Mohammad},
      year={2024},
      eprint={2402.08638},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
@inproceedings{mohammad2016dataset,
  title={A dataset for detecting stance in tweets},
  author={Mohammad, Saif and Kiritchenko, Svetlana and Sobhani, Parinaz and Zhu, Xiaodan and Cherry, Colin},
  booktitle={Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)},
  pages={3945--3952},
  year={2016}
}
@inproceedings{ohman2022self,
  title={SELF \& FEIL: Emotion Lexicons for Finnish},
  author={{\"O}hman, Emily},
  booktitle={Proceedings of the 6th Digital Humanities in the Nordic and Baltic Countries conference. CEUR Workshop Proceedings},
  year={2022}
}
@inproceedings{horn2014learning,
  title={Learning a lexical simplifier using Wikipedia},
  author={Horn, Colby and Manduca, Cathryn and Kauchak, David},
  booktitle={Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  pages={458--463},
  year={2014}
}
@inproceedings{amjad2020data,
  title={Data augmentation using machine translation for fake news detection in the Urdu language},
  author={Amjad, Maaz and Sidorov, Grigori and Zhila, Alisa},
  booktitle={Proceedings of the Twelfth Language Resources and Evaluation Conference},
  pages={2537--2542},
  year={2020}
}
@article{cer2017semeval,
  title={Semeval-2017 task 1: Semantic textual similarity-multilingual and cross-lingual focused evaluation},
  author={Cer, Daniel and Diab, Mona and Agirre, Eneko and Lopez-Gazpio, Inigo and Specia, Lucia},
  journal={arXiv preprint arXiv:1708.00055},
  year={2017}
}
@article{bowman2015large,
  title={A large annotated corpus for learning natural language inference},
  author={Bowman, Samuel R and Angeli, Gabor and Potts, Christopher and Manning, Christopher D},
  journal={arXiv preprint arXiv:1508.05326},
  year={2015}
}
@article{deode2023l3cube,
  title={L3Cube-IndicSBERT: A simple approach for learning cross-lingual sentence representations using multilingual BERT},
  author={Deode, Samruddhi and Gadre, Janhavi and Kajale, Aditi and Joshi, Ananya and Joshi, Raviraj},
  journal={arXiv preprint arXiv:2304.11434},
  year={2023}
}
@article{hamalainen2021endangered,
  title={Endangered Languages are not Low-Resourced!},
  author={H{\"a}m{\"a}l{\"a}inen, Mika},
  journal={arXiv preprint arXiv:2103.09567},
  year={2021}
}
@inproceedings{hedderich2021survey,
  title={A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios},
  author={Hedderich, Michael A and Lange, Lukas and Adel, Heike and Str{\"o}tgen, Jannik and Klakow, Dietrich},
  booktitle={Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
  pages={2545--2568},
  year={2021}
}
@article{devlin2018bert,
  title={Bert: Pre-training of deep bidirectional transformers for language understanding},
  author={Devlin, Jacob and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina},
  journal={arXiv preprint arXiv:1810.04805},
  year={2018}
}

@article{vulic2020probing,
  title={Probing pretrained language models for lexical semantics},
  author={Vuli{\'c}, Ivan and Ponti, Edoardo Maria and Litschko, Robert and Glava{\v{s}}, Goran and Korhonen, Anna},
  journal={arXiv preprint arXiv:2010.05731},
  year={2020}
}
@article{marreddy2022resource,
  title={Am I a Resource-Poor Language? Data Sets, Embeddings, Models and Analysis for four different NLP Tasks in Telugu Language},
  author={Marreddy, Mounika and Oota, Subba Reddy and Vakada, Lakshmi Sireesha and Chinni, Venkata Charan and Mamidi, Radhika},
  journal={ACM Transactions on Asian and Low-Resource Language Information Processing},
  volume={22},
  number={1},
  pages={1--34},
  year={2022},
  publisher={ACM New York, NY}
}
@inproceedings{zhang2020semantics,
  title={Semantics-aware BERT for language understanding},
  author={Zhang, Zhuosheng and Wu, Yuwei and Zhao, Hai and Li, Zuchao and Zhang, Shuailiang and Zhou, Xi and Zhou, Xiang},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={34},
  number={05},
  pages={9628--9635},
  year={2020}
}
@inproceedings{wan2018,
author = {Wan, Mengting and McAuley, Julian},
title = {Item recommendation on monotonic behavior chains},
year = {2018},
isbn = {9781450359016},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3240323.3240369},
doi = {10.1145/3240323.3240369},
abstract = { 'Explicit' and 'implicit' feedback in recommender systems have been studied for many years, as two relatively isolated areas. However many real-world systems involve a spectrum of both implicit and explicit signals, ranging from clicks and purchases, to ratings and reviews. A natural question is whether implicit signals (which are dense but noisy) might help to predict explicit signals (which are sparse but reliable), or vice versa. Thus in this paper, we propose an item recommendation framework which jointly models this full spectrum of interactions. Our main observation is that in many settings, feedback signals exhibit monotonic dependency structures, i.e., any signal necessarily implies the presence of a weaker (or more implicit) signal (a 'review' action implies a 'purchase' action, which implies a 'click' action, etc.). We refer to these structures as 'monotonic behavior chains,' for which we develop new algorithms that exploit these dependencies. Using several new and existing datasets that exhibit a variety of feedback types, we demonstrate the quantitative performance of our approaches. We also perform qualitative analysis to uncover the relationships between different stages of implicit vs. explicit signals.},
booktitle = {Proceedings of the 12th ACM Conference on Recommender Systems},
pages = {86–94},
numpages = {9},
location = {Vancouver, British Columbia, Canada},
series = {RecSys '18}
}




@article{rao2018dear,
  title={Dear sir or madam, may I introduce the GYAFC dataset: Corpus, benchmarks and metrics for formality style transfer},
  author={Rao, Sudha and Tetreault, Joel},
  journal={arXiv preprint arXiv:1803.06535},
  year={2018}
}
@article{BATET2016365,
title = {Improving Semantic Relatedness Assessments: Ontologies Meet Textual Corpora},
journal = {Procedia Computer Science},
volume = {96},
pages = {365-374},
year = {2016},
note = {A paper we can use to show that we understand the difference between semantic relatedness and semantic similarity and looked into potential approaches/methods in order to improve the accuracy of our work.},
issn = {1877-0509},
doi = {https://doi.org/10.1016/j.procs.2016.08.149},
url = {https://www.sciencedirect.com/science/article/pii/S1877050916319500},
author = {Montserrat Batet and David Sánchez},
keywords = {knowledge, semantics, semantic relatednes, semantic similarity, ontologies, textual information distribution.},
abstract = {Even though the calculation of the semantic similarity between textual entities has received a lot of attention by the research community, the more general notion of semantic relatedness (which considers both taxonomic and non-taxonomic knowledge) has been significantly less studied and, in general, stays one step behind in terms of accuracy. In this paper, we improve semantic relatedness assessments by aggregating the highly-accurate ontology-based estimation of semantic similarity with the distributional resemblance of textual terms computed from large textual corpora. As a result, our approach is able to improve the accuracy of related works on a standard benchmark.}
}
@inproceedings{abdalla-etal-2023-makes,
    title = "What Makes Sentences Semantically Related? A Textual Relatedness Dataset and Empirical Study",
    author = "Abdalla, Mohamed  and
      Vishnubhotla, Krishnapriya  and
      Mohammad, Saif",
    editor = "Vlachos, Andreas  and
      Augenstein, Isabelle",
    booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics",
    month = may,
    year = "2023",
    address = "Dubrovnik, Croatia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.eacl-main.55",
    doi = "10.18653/v1/2023.eacl-main.55",
    pages = "782--796",
    abstract = "The degree of semantic relatedness of two units of language has long been considered fundamental to understanding meaning. Additionally, automatically determining relatedness has many applications such as question answering and summarization. However, prior NLP work has largely focused on semantic similarity, a subset of relatedness, because of a lack of relatedness datasets. In this paper, we introduce a dataset for Semantic Textual Relatedness, STR-2022, that has 5,500 English sentence pairs manually annotated using a comparative annotation framework, resulting in fine-grained scores. We show that human intuition regarding relatedness of sentence pairs is highly reliable, with a repeat annotation correlation of 0.84. We use the dataset to explore questions on what makes sentences semantically related. We also show the utility of STR-2022 for evaluating automatic methods of sentence representation and for various downstream NLP tasks. Our dataset, data statement, and annotation questionnaire can be found at: \url{https://doi.org/10.5281/zenodo.7599667}.",
}

@article{joshi2022l3cubemahasbert,
  title={L3Cube-MahaSBERT and HindSBERT: Sentence BERT Models and Benchmarking BERT Sentence Representations for Hindi and Marathi},
  author={Joshi, Ananya and Kajale, Aditi and Gadre, Janhavi and Deode, Samruddhi and Joshi, Raviraj},
  journal={arXiv preprint arXiv:2211.11187},
  year={2022}
}

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "http://arxiv.org/abs/1908.10084",
}

@inproceedings{remy-et-al-2023-biolord,
    title = "{B}io{LORD}: Semantic Textual Representations Fusing LLM and Clinical Knowledge Graph Insights",
    author = "Remy, François  and
      Demuynck, Kris  and
      Demeester, Thomas",
    month = nov,
    year = "2023",
    eprint={2311.16075},
    archivePrefix={arXiv},
    primaryClass={cs.CL}}

@misc{fan2020englishcentric,
      title={Beyond English-Centric Multilingual Machine Translation}, 
      author={Angela Fan and Shruti Bhosale and Holger Schwenk and Zhiyi Ma and Ahmed El-Kishky and Siddharth Goyal and Mandeep Baines and Onur Celebi and Guillaume Wenzek and Vishrav Chaudhary and Naman Goyal and Tom Birch and Vitaliy Liptchinsky and Sergey Edunov and Edouard Grave and Michael Auli and Armand Joulin},
      year={2020},
      eprint={2010.11125},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@online{sts-benchmark,
    title ={Semantic Textual Similarity Wiki},
    url={https://ixa2.si.ehu.eus/stswiki/index.php/Main_Page},
}

