Papers with PoS
A Study on Using Semantic Word Associations to Predict the Success of a Novel (2021.starsem-1)
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Syeda Jannatus Saba, Biddut Sarker Bijoy, Henry Gorelick, Sabir Ismail, Md Saiful Islam, Mohammad Ruhul Amin
| Challenge: | Existing methods for book success prediction are not effective. |
| Approach: | They propose to represent a book as a spectrum of concepts based on the association score between its content embedding and a global embeddment for a set of semantically linked word clusters. |
| Outcome: | The proposed method outperforms the previous methods for book success prediction. |
Building a Part-of-Speech Tagged Corpus for Drenjongke (Bhutia) (2020.aacl-srw)
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| Challenge: | a corpus of sentences and 1379 tokens were generated for the first Drenjongke corpus . the language is considered "vulnerable," "definitely endangered" and "severely endangered." |
| Approach: | They propose to generate the first corpus of the Tibetan language using a phrase book . they propose to use 34 Part-of-Speech (PoS) tags to define the first Drenjongke corpus . |
| Outcome: | The first corpus of the Drenjongke language comprises 275 sentences and 1379 tokens . the paper plans to expand with other materials to promote further studies of the language . |
Parsing linearizations appreciate PoS tags - but some are fussy about errors (2022.aacl-short)
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| Challenge: | Recent work on the impact of PoS tags on graph- and transition-based parsers suggests that they are only useful when tagging accuracy is prohibitively high or in low-resource scenarios. |
| Approach: | They examine the impact of PoS tags on graph- and transition-based parsers and propose to use them in a new paradigm for sequence labeling. |
| Outcome: | The proposed model is best when tagging accuracy and resource availability are high. |
SyMCoM - Syntactic Measure of Code Mixing A Study Of English-Hindi Code-Mixing (2022.findings-acl)
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| Challenge: | Recent work on code mixing in computational settings has leveraged social media code mixed texts to train NLP models. |
| Approach: | They propose to use language ID tags to measure syntactic variety in code-mixed text and their relationship with computational model performance. |
| Outcome: | The proposed measure can be applied to English(en)-hindi(hi) code-mixed datasets and compares them with other measures. |
AlignFreeze: Navigating the Impact of Realignment on the Layers of Multilingual Models Across Diverse Languages (2025.naacl-short)
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| Challenge: | Realignment techniques are often employed to enhance cross-lingual transfer in multilingual language models, but can degrade performance in languages that differ significantly from the fine-tuned source language. |
| Approach: | They propose a method that freezes either the lower half or upper half of the layers during realignment to prevent performance degradation. |
| Outcome: | The proposed method improves Part-of-Speech (PoS) tagging performance in languages where realignment fails. |
Potential Idiomatic Expression (PIE)-English: Corpus for Classes of Idioms (2022.lrec-1)
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Tosin Adewumi, Roshanak Vadoodi, Aparajita Tripathy, Konstantina Nikolaido, Foteini Liwicki, Marcus Liwicki
| Challenge: | Potential Idiomatic Expression (PIE) dataset for NLP in English contains over 20,100 samples with almost 1,200 cases of idioms from 10 classes (or senses). |
| Approach: | They present a large Potential Idiomatic Expression (PIE) dataset for Natural Language Processing (NLP) in English. |
| Outcome: | The proposed dataset contains over 20,100 samples with almost 1,200 cases of idioms (with their meanings) from 10 classes (or senses). |
PortOldBERT: Portuguese Historical Language Models (2026.eacl-long)
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| Challenge: | Historical language models are important for many tasks, but have limited application in historical Portuguese. |
| Approach: | They propose a Portuguese encoder language model that integrates historical linguistic contexts while retaining the ability to process contemporary text. |
| Outcome: | The proposed model outperforms Albertina on multiple tasks and for different historical periods. |
Decoding Part-of-Speech from Human EEG Signals (2022.acl-long)
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| Challenge: | Recent studies have shown that EEG signal magnitude and topography depend on word length, frequency and open vs. closed class. |
| Approach: | They propose to use EEG to predict Part-of-Speech (PoS) tags from neural signals measured at millisecond resolution during text reading. |
| Outcome: | The proposed techniques outperform linear-SVMs on PoS tagging of unigram and bigram data. |
Who Taught You That? Tracing Teachers in Model Distillation (2025.findings-acl)
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| Challenge: | Xu et al., 2006, show that model distillation can imbue efficient small language models with task-specific capabilities competitive with expensive teacher LLMs. |
| Approach: | They propose to distill outputs from a large teacher model to a small student model . they propose to use part-of-speech templates as higher-order linguistic features capable of capturing distinctive signals from teacher models that persist in distilled student outputs. |
| Outcome: | The proposed model distillation technique can imbue efficient small language models with task-specific capabilities competitive with (expensive) teacher LLMs. |
Korean Language Modeling via Syntactic Guide (2022.lrec-1)
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| Challenge: | Existing research on pre-trained language models focuses on widely-used languages . however, not every language can benefit from such models due to computational resources . |
| Approach: | They propose to build a pre-trained language model that understands the linguistic phenomena in the target language with low resources. |
| Outcome: | The proposed model improves the performance of Korean language understanding tasks. |
Urdu Pitch Accents and Intonation Patterns in Spontaneous Conversational Speech (2020.lrec-1)
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| Challenge: | Recent studies of Urdu intonation describe scripted and laboratory speech . |
| Approach: | They summarise Urdu pitch accents and their intonation patterns using a simplified version of the Rhythm and Pitch labelling system and a simple RAP system. |
| Outcome: | The analysis of a hand-labelled telephone conversation shows that low pitch accents play an important role in Urdu spontaneous speech. |
Leveraging Linguistically Enhanced Embeddings for Open Information Extraction (2024.lrec-main)
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| Challenge: | Open Information Extraction (OIE) is a structure prediction task in NLP that aims to extract structured n-ary tuples from free text. |
| Approach: | They propose to leverage linguistic features with a Seq2Seq PLM for OIE to improve performance. |
| Outcome: | The proposed methods give any neural OIE architecture the key performance boost from both PLMs and linguistic features in one go. |
Convergence and Divergence of Language Models under Different Random Seeds (2025.emnlp-main)
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| Challenge: | a large body of work has examined the training dynamics of language models. |
| Approach: | They investigate the convergence of language models (LMs) trained under different random seeds . they find that larger models reconverge faster in later training stages, while smaller models never actually reconverge. |
| Outcome: | The proposed model size and training checkpoints influence convergence of language models under different seeds. |