Papers with linguistic analysis
LUX (Linguistic aspects Under eXamination): Discourse Analysis for Automatic Fake News Classification (2021.findings-acl)
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| Challenge: | Automated fact-checking is time-consuming and cannot scale due to a lack of suitable training data. |
| Approach: | They propose to use a dataset to automatically check facts and a text classifier to infer the likelihood of the input being a piece of fake-news. |
| Outcome: | The proposed dataset VERITAS and LUX use linguistic analysis to infer the likelihood of the input being a piece of fake-news. |
FAKTA: An Automatic End-to-End Fact Checking System (N19-4)
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| Challenge: | Existing studies have investigated individual components of fact checking process but none offer such a capability. |
| Approach: | They propose a framework that integrates various components of a fact-checking process. |
| Outcome: | The proposed framework integrates various components of a fact-checking process to predict the factuality of claims and provide evidence at the document and sentence level to explain its predictions. |
Dilated LSTM with attention for Classification of Suicide Notes (D19-62)
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| Challenge: | Using a dilated LSTM with attention we achieve an accuracy of 87.34% compared to baselines of 80.35% and 82.27%. |
| Approach: | They propose a dilated LSTM with attention mechanism for document-level classification of suicide notes, last statements and depressed notes. |
| Outcome: | The proposed model achieves an accuracy of 87.34% compared to baselines of 80.35% and 82.27%. |
MAGPIE: A Large Corpus of Potentially Idiomatic Expressions (2020.lrec-1)
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| Challenge: | Existing corpora cover less than 5,000 instances of less than 100 different idiom types . large corpus allows for better evaluation of assumptions about idiomatic expressions . |
| Approach: | They propose to build the largest-to-date corpus of idioms for English using crowdsourcing methods. |
| Outcome: | The proposed corpus is larger than existing resources and contains rich metadata and is made publicly available. |
Discovering Representation Sprachbund For Multilingual Pre-Training (2021.findings-emnlp)
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| Challenge: | Existing models perform poorly on many languages and cross-lingual tasks due to typological differences and contradictions between some languages. |
| Approach: | They propose to pre-train multilingual pre-trained models to handle cross-lingual tasks in one model. |
| Outcome: | The proposed model improves performance on cross-lingual tasks compared to baselines on multiple languages . |
MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder (2025.acl-industry)
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Khai Le-Duc, Phuc Phan, Tan-Hanh Pham, Bach Phan Tat, Minh-Huong Ngo, Thanh Nguyen-Tang, Truong-Son Hy
| Challenge: | Multilingual automatic speech recognition (ASR) in the medical domain is a critical foundational task, serving a wide range of downstream applications such as speech translation, spoken language understanding, and voice-activated assistants. |
| Approach: | They present the first multilingual medical ASR dataset and the first collection of small-to-large end-to end medical APR models spanning five languages: Vietnamese, English, German, French, and Mandarin Chinese. |
| Outcome: | The proposed model covers Vietnamese, English, German, French, and Mandarin Chinese, and is the first multilingual ASR dataset across five languages. |
Multi-Granularity Self-Attention for Neural Machine Translation (D19-1)
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| Challenge: | Existing neural machine translation models use a deep multi-head self-attention network with no explicit phrase information. |
| Approach: | They propose a neural network that combines multi-head self-attention and phrase modeling to train attention heads to attend to phrases in either n-gram or syntactic formalisms. |
| Outcome: | The proposed approach improves on English-to-German and NIST Chinese-to English translation tasks. |
The Royal Society Corpus 6.0: Providing 300+ Years of Scientific Writing for Humanistic Study (2020.lrec-1)
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| Challenge: | a new version of the Royal Society Corpus covers 300+ years of scientific writing . the corpus is freely available under a Creative Commons license, excluding copy-righted parts . |
| Approach: | They present a new version of the Royal Society Corpus, a diachronic corpus of scientific English covering 300+ years of scientific writing. |
| Outcome: | The extended version of the Royal Society Corpus covers 300+ years of scientific writing . the corpus is freely available under a Creative Commons license, excluding copy-righted parts . |
Analyzing the Intensity of Complaints on Social Media (2022.findings-naacl)
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| Challenge: | Prior studies on identifying the existence or the type of complaints focus on building automatic classification models for identifying complaints. |
| Approach: | They propose to measure the intensity of complaints from text using Best-Worst Scaling method to estimate the popularity of posts on social media. |
| Outcome: | The proposed model can estimate the popularity of complaints on social media with best-worst scaling (BWS) method. |
Automated Extraction of Prosodic Structure from Unannotated Sign Language Video (2024.lrec-main)
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| Challenge: | a new method for analyzing prosody in sign languages uses the velocity profile of the hands . the velocity profiles of hand movements can be used to analyse prosodic structure . |
| Approach: | They propose a method for extracting velocity information from unlabeled video of sign language using CoTracker. |
| Outcome: | The proposed method can extract prosodic information from unlabeled video clips. |
Echoes of Discord: Forecasting Hater Reactions to Counterspeech (2025.findings-naacl)
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| Challenge: | Hate speech (HS) online causes increased prejudice and discrimination, fostering an environment of hostility and social division. |
| Approach: | They analyze the Reddit Echoes of Hate dataset to assess the impact of counterspeech from the hater's perspective and focus on whether the counterspeak leads the reentry to be hateful. |
| Outcome: | The proposed model outperforms the two-stage reaction predictor and the three-way classifier to predict haters' reactions to the reentry of the conversation and determines the type of resentment. |
Explaining Generalization of AI-Generated Text Detectors Through Linguistic Analysis (2026.eacl-long)
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| Challenge: | Existing studies have reported generalization gaps in AI-text detectors, but they lack insights into the causes. |
| Approach: | They propose to analyze generalization behavior of AI-text detectors using linguistic analysis to explain performance variance. |
| Outcome: | The proposed model can generalize across unseen prompts, model families, and domains, but it can't generalize under distribution shifts. |
Analyzing Online Political Advertisements (2021.findings-acl)
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| Challenge: | Online political advertising is an integral part of modern digital election campaigning. |
| Approach: | They propose to use textual and visual information from pre-trained neural models to infer the political ideology of an ad sponsor and identify whether the sponsor is an official political party or a third-party organization. |
| Outcome: | The proposed approach outperforms state-of-the-art methods for generic commercial ad classification and linguistic analysis to study the characteristics of political ads discourse. |
Biographically Relevant Tweets – a New Dataset, Linguistic Analysis and Classification Experiments (2022.coling-1)
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| Challenge: | Unlike previous work, we do not restrict biographical relevance to a small fixed set of pre-defined relations. |
| Approach: | They propose a dataset comprising tweets for the novel task of detecting biographically relevant utterances. |
| Outcome: | The proposed dataset focuses on biographical information on ordinary users of Twitter. |
An analysis of language models for metaphor recognition (2020.coling-main)
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| Challenge: | Metaphor recognition systems that are based on language models perform substantially worse on unconventional metaphors than on conventional ones. |
| Approach: | They conduct a linguistic analysis of recent metaphor recognition systems based on language models and a variant of BERT language models to examine their performance. |
| Outcome: | The proposed systems show that they can recognise unseen words if synonyms or morphological variations have been seen before, leading to enhanced generalisation beyond word sense disambiguation. |
BanFakeNews: A Dataset for Detecting Fake News in Bangla (2020.lrec-1)
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| Challenge: | Impact of fake news is creating havoc worldwide. |
| Approach: | They propose an annotated dataset of 50K news that can be used for building automated fake news detection systems for a low resource language like Bangla. |
| Outcome: | The proposed system can be built with state-of-the-art NLP techniques for a low resource language like Bangla. |
Analyzing Political Parody in Social Media (2020.acl-main)
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| Challenge: | Parody is a figurative device used to imitate an entity for comedic or critical purposes. |
| Approach: | They propose a dataset of tweets from real politicians and their corresponding parody accounts to run supervised machine learning models for automatic classification. |
| Outcome: | The proposed models predict political parody tweets with 90% accuracy . they also identify the markers of parody through a linguistic analysis . |
IGT2P: From Interlinear Glossed Texts to Paradigms (2020.emnlp-main)
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| Challenge: | Existing systems for learning morphology have limited their use to languages with publicly available structured data, such as online dictionaries like Wiktionary. |
| Approach: | They propose a task that generates entire morphological paradigms from IGT input and a language expert cleaning noisy IGT data. |
| Outcome: | The proposed task speeds up the process and generates entire morphological paradigm tables from IGT input. |
Deep Associations, High Creativity: A Simple yet Effective Metric for Evaluating Large Language Models (2025.emnlp-main)
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| Challenge: | Recent studies evaluate the creative capabilities of large language models (LLMs) through diverse tasks, aiming to understand their strengths and limitations. |
| Approach: | They propose to ask LLMs to generate Parallel Chains of Associations to Evaluate their creativity. |
| Outcome: | The proposed framework minimizes the risk of data contamination and offers a highly efficient evaluation. |
Inference Annotation of a Chinese Corpus for Opinion Mining (2020.lrec-1)
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| Challenge: | Existing tools for opinion mining can accurately predict the writer's attitude in simple explicit sentences. |
| Approach: | They propose to define inference, classify different types and provide an annotation framework to analyze the annotation results. |
| Outcome: | The proposed framework defines inference type, polarity and topic and analyzes the results. |
Development of a General-Purpose Categorial Grammar Treebank (2020.lrec-1)
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| Challenge: | 'general-purpose' categorial grammar treebank is not tailored to specific variants of CG, but rather offers a theory-neutral linguistic resource that can be converted to different versions of 'type-logical grammar' . |
| Approach: | They propose a general-purpose categorial grammar treebank for Japanese that is not tailored to a specific variant of CG but rather offers a theory-neutral resource which can be converted to different versions of GC relatively easily. |
| Outcome: | The proposed treebank improves on the existing Japanese CG treebank on the treatment of certain linguistic phenomena (passives, causatives, and control/raising predicates). |
Sign Languages and the Online World Online Dictionaries & Lexicostatistics (L18-1)
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| Challenge: | Several online dictionaries documenting the lexicon of a variety of sign languages are available . methodological issues must be addressed regarding how these resources are used for research purposes. |
| Approach: | They propose a web-based tool for annotating the articulatory features of signs . they compare handshapes for four Asian SLs and handshape for the entire sample . |
| Outcome: | The proposed tool compares handshapes and handsights of Asian SLs with European, American, and Brazilian SL samples. |
A Crosslingual Investigation of Conceptualization in 1335 Languages (2023.acl-long)
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Yihong Liu, Haotian Ye, Leonie Weissweiler, Philipp Wicke, Renhao Pei, Robert Zangenfeind, Hinrich Schütze
| Challenge: | Conceptualizer is a method that creates a bipartite directed alignment graph between source language concepts and sets of target language strings. |
| Approach: | They propose a method that creates a bipartite directed alignment graph between source language concepts and sets of target language strings. |
| Outcome: | The proposed method has good alignment accuracy across all languages and on 32 Swadesh concepts. |
PoliBERTweet: A Pre-trained Language Model for Analyzing Political Content on Twitter (2022.lrec-1)
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| Challenge: | Pre-trained domain-specific models are useful for understanding domain-level contexts. |
| Approach: | They propose to use a pre-trained language model to better capture domain-specific contexts. |
| Outcome: | The proposed model outperforms general-purpose models on election-related tasks. |
Open-source Multi-speaker Corpora of the English Accents in the British Isles (2020.lrec-1)
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| Challenge: | Using a dataset of high-quality audio, the authors examine the accents of 120 volunteers in the British Isles. |
| Approach: | They present a dataset of high-quality audio of English sentences recorded by volunteers with different accents of the British Isles. |
| Outcome: | The transcribed audio includes pronunciations of global locations, major airlines and common personal names in different accents. |
SarcNet: A Multilingual Multimodal Sarcasm Detection Dataset (2024.lrec-main)
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| Challenge: | Sarcasm is an implicit form of sarcasm, involving an intended meaning that contradicts the literal expression . human use conflict between factual information and a statement as cues to detect sarcasm . sarkasmatic analysis is challenging due to its implicit nature . |
| Approach: | They propose a multimodal sarcasm detection dataset that uses multiple modalities to detect sarcasm. |
| Outcome: | The proposed model improves on previous models based on a single label . human sarcasm cannot be detected using a unified label across multiple modalities . |
Improving Handshape Representations for Sign Language Processing: A Graph Neural Network Approach (2025.emnlp-main)
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| Challenge: | Existing systems for sign language recognition process a signing sequence holistically, leaving handshape information implicit, which limits both recognition accuracy and linguistic analysis. |
| Approach: | They propose a graph neural network that separates temporal dynamics from static handshape configurations in continuous signing sequences. |
| Outcome: | The proposed approach achieves 46% accuracy across 37 handshape classes, compared to 25% for baseline methods. |