Papers with English texts
PharmaCoNER: Pharmacological Substances, Compounds and proteins Named Entity Recognition track (D19-57)
Copied to clipboard
Aitor Gonzalez-Agirre, Montserrat Marimon, Ander Intxaurrondo, Obdulia Rabal, Marta Villegas, Martin Krallinger
| Challenge: | Biomedical text mining is one of the most prolific application domains of natural language processing technologies. |
| Approach: | They propose to share a task on detecting drug and chemical entities in medical documents in Spanish with other languages to improve access to biomedical text mining. |
| Outcome: | The first task on detecting drug and chemical entities in Spanish medical documents yielded competitive results with F-measures above 0.91. |
The Natural Stories Corpus (L18-1)
Copied to clipboard
Richard Futrell, Edward Gibson, Harry J. Tily, Idan Blank, Anastasia Vishnevetsky, Steven Piantadosi, Evelina Fedorenko
| Challenge: | Existing corpora of naturalistic text do not contain the low-frequency syntactic constructions needed to distinguish between theories. |
| Approach: | They propose to compare models of language processing by comparing their ability to predict behavioral and neural measures of processing difficulty to corpora of naturalistic text. |
| Outcome: | The proposed corpus contains low-frequency syntactic constructions while sounding fluent to native speakers. |
Evaluating and Mitigating Inherent Linguistic Bias of African American English through Inference (2022.coling-1)
Copied to clipboard
| Challenge: | Recent studies show that NLP models trained on standard English produce biased outcomes against underrepresented English varieties. |
| Approach: | They propose a morphosyntactically-informed rule-based translation method that uses a greedy algorithm to debiase NLP models. |
| Outcome: | The proposed framework outperforms large language models while maintaining or improving the prediction performance. |
Detection of Human and Machine-Authored Fake News in Urdu (2025.acl-long)
Copied to clipboard
| Challenge: | Existing methods for fake news detection focus on binary classification and English texts, ignoring the distinction between machine-generated true vs. fake news and low-resource languages. |
| Approach: | They propose to include machine-generated news focusing on Urdu to improve accuracy and robustness. |
| Outcome: | The proposed strategy improves accuracy and robustness across four datasets in various settings. |
SEA-SafeguardBench: Culturally Grounded Safety Benchmark for Southeast Asian Languages (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing multilingual safety benchmarks rely on machine-translated English data, which fails to capture nuances in low-resource languages. |
| Approach: | They propose to use a human-verified safety benchmark for Southeast Asian languages to validate their safety and cultural diversity. |
| Outcome: | The proposed model outperforms existing models in general, in-the-wild, and content generation across eight languages and 21,640 samples across three subsets: general, and in- the-wild. |
Annotating Arguments in a Corpus of Opinion Articles (2022.lrec-1)
Copied to clipboard
Gil Rocha, Luís Trigo, Henrique Lopes Cardoso, Rui Sousa-Silva, Paula Carvalho, Bruno Martins, Miguel Won
| Challenge: | Argument annotation is the process of exposing and justifying one's points of view, with the aim of conveying a logical reasoning through a set of semantically related propositions. |
| Approach: | They propose to use argumentative discourse units to annotate arguments in Portuguese using a multi-layered process to analyze the annotations produced. |
| Outcome: | The proposed model exploits the best practices identified in previous studies while fostering the potential use of the resulting annotated corpus for new purposes. |
Adapting Event Extractors to Medical Data: Bridging the Covariate Shift (2021.eacl-main)
Copied to clipboard
| Challenge: | a new study examines the performance of event extractors to new domains without labeled data . event extraction is a key sub-task of interest for text understanding pipelines in multiple domains . |
| Approach: | They propose to align marginal distributions of source and target domains to adapt event extractors to new domains . they use clinical notes and doctor-patient conversations as a testbed . |
| Outcome: | The proposed models reach F1 scores of 70.0 and 72.9 on notes and conversations respectively. |
Gated Transformer for Robust De-noised Sequence-to-Sequence Modelling (2021.findings-emnlp)
Copied to clipboard
| Challenge: | Noisy texts are common in user-generated texts that appear abundant in social media platforms like SMS, online chat, email, blogs, wikis etc. |
| Approach: | They propose a sequence-to-sequence architecture that uses a gating mechanism to detect types of corrections required from English texts. |
| Outcome: | The proposed architecture performs better than non-gated models on machine translation and Summarization tasks. |
COVID-19 Mythbusters in World Languages (2022.lrec-1)
Copied to clipboard
| Challenge: | 115 languages are included in the database, including the original English texts . character bi-grams with normalization is an effective proxy for measuring the similarity of the languages and the affinity ranking of language pairs can be obtained. |
| Approach: | They propose a multi-lingual database containing translated COVID-19 mythbusters texts . they use character bi-grams with normalization to measure similarity of languages . |
| Outcome: | The proposed database has translations into 115 languages and the original English texts, of which the original texts are published by the World Health Organization (WHO). |
Parameter-Efficient Cross-lingual Transfer of Vision and Language Models via Translation-based Alignment (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing cross-lingual transfer methods that use labeled data and linguistic resources would consume excessive resources for a large number of languages. |
| Approach: | They propose a parameter-efficient cross-lingual transfer learning framework that utilizes a translation-based alignment method to mitigate multilingual disparities. |
| Outcome: | The proposed framework reduces disparities among languages and improves cross-lingual transfer results in low-resource scenarios while keeping and fine-tuning only a small number of parameters. |
Temperature-scaling surprisal estimates improve fit to human reading times – but does it do so for the “right reasons”? (2024.acl-long)
Copied to clipboard
| Challenge: | a wide body of evidence shows that human language processing difficulty is predicted by the information-theoretic measure surprisal, a word’s negative log probability in context. |
| Approach: | They propose to use large language models to predict the surprisal of a word's negative log probability in context to test their predictive power. |
| Outcome: | The proposed model can be significantly more accurate than humans because it has more data. |
Investigating the Relationship Between Romanian Financial News and Closing Prices from the Bucharest Stock Exchange (2022.lrec-1)
Copied to clipboard
| Challenge: | a new data set is used to extract information related to one company . a model that is based on previous information about transactions is not enough . |
| Approach: | They use a Romanian financial news website to extract only information related to one company . they use lexicon-based Vader tool, Financial BERT and Transformer-based models . |
| Outcome: | The proposed model shows that the extracted sentiment scores correlate with stock closing prices . the proposed model is based on data from a Romanian financial news website . |
Cross-lingual Aspect-based Sentiment Analysis with Aspect Term Code-Switching (2021.emnlp-main)
Copied to clipboard
| Challenge: | Existing studies on Aspect-based sentiment analysis (ABSA) focus on English texts, but handling it in resource-poor languages remains a challenge. |
| Approach: | They propose an unsupervised cross-lingual transfer method for the Aspect-based sentiment analysis task . they propose an aspect code-switching mechanism to augment training data with code-linked bilingual sentences . |
| Outcome: | The proposed method preserves task-specific knowledge in the target language. |
Human Raters Cannot Distinguish English Translations from Original English Texts (2023.emnlp-main)
Copied to clipboard
| Challenge: | Prior work on translationese has identified common hallmarks of translationeses, but human accuracy of identifying translated text is understudied. |
| Approach: | They perform an evaluation of English original/translated texts to examine whether raters can classify texts as being original or translated English and the features that lead rater to judge text as being translated. |
| Outcome: | The results provide critical insight into work in translation studies and context for assessments of translationese classifiers. |