Papers with logistic regression model
OpusFilter: A Configurable Parallel Corpus Filtering Toolbox (2020.acl-demos)
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| Challenge: | OpusFilter is a toolbox for filtering parallel corpora using noisy training data. |
| Approach: | They propose a toolbox for filtering parallel corpora with heuristic filters, language identification libraries, character-based language models and word alignment tools. |
| Outcome: | The proposed tool outperforms a similar tool on a Finnish-English news translation task using noisy web crawls. |
Prediction for the Newsroom: Which Articles Will Get the Most Comments? (N18-3)
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| Challenge: | a new method to support manual moderation of discussion sections is proposed. |
| Approach: | They propose to support manual moderation by proactively drawing attention of moderators to articles that most likely need their intervention. |
| Outcome: | The proposed method outperforms the current state-of-the-art methods on a 7-million-comment dataset. |
Dual Mechanism Priming Effects in Hindi Word Order (2022.aacl-main)
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| Challenge: | Existing studies have shown that word order choices can be primed by preceding sentences. |
| Approach: | They propose to model lexical priming and lexically-independent syntactic priming using a logistic regression model. |
| Outcome: | The proposed hypothesis supports multiple cognitive mechanisms . the experimental record shows that lexical priming and lexically-independent priming affect complementary sets of verb classes. |
Linguistically Motivated Features for Classifying Shorter Text into Fiction and Non-Fiction Genre (2022.coling-1)
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| Challenge: | linguistically motivated features are used to classify paragraph-level text into fiction and non-fiction genres. |
| Approach: | They deploy linguistically motivated features to classify paragraph-level text into fiction and non-fiction genres using a logistic regression model. |
| Outcome: | The proposed model gives 15.56% accuracy jump over baseline model . the proposed model also transfers over to another dataset, Baby BNC corpus . |
A Framework for Fine-Grained Complexity Control in Health Answer Generation (2025.acl-srw)
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| Challenge: | Health literacy is the ability to obtain, process, and understand basic health information. |
| Approach: | They propose a framework for automatically generating health answers at multiple, precisely controlled complexity levels. |
| Outcome: | The proposed framework allows users to generate health questions at multiple complexity levels. |
Error Analysis of NLP Models and Non-Native Speakers of English Identifying Sarcasm in Reddit Comments (2024.lrec-main)
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| Challenge: | sarcasm detection remains an issue for both humans and natural language processing models . |
| Approach: | They analysed 300 comments from the FigLang 2020 Reddit Dataset and 39 non-native speakers of English to see if they were sarcastic. |
| Outcome: | The results show that the models and models have similar performance and weaknesses when the comments include political topics or are phrased as questions. |
When Instructions Multiply: Measuring and Estimating LLM Capabilities of Multiple Instructions Following (2025.findings-emnlp)
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Keno Harada, Yudai Yamazaki, Masachika Taniguchi, Edison Marrese-Taylor, Takeshi Kojima, Yusuke Iwasawa, Yutaka Matsuo
| Challenge: | a large number of languages are increasingly used to evaluate their ability to follow multiple instructions simultaneously. |
| Approach: | They propose two benchmarks to evaluate LLMs' ability to follow multiple instructions simultaneously . they use many instruction-following eval and style-aware Mostly Basic programming problems . |
| Outcome: | The proposed models predict performance on unseen instruction combinations and not used during training with 10% error. |