Papers with linguistic analysis

27 papers
LUX (Linguistic aspects Under eXamination): Discourse Analysis for Automatic Fake News Classification (2021.findings-acl)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations