Papers with syntactic complexity
Controllable Text Simplification with Lexical Constraint Loss (P19-2)
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| Challenge: | Existing models that only consider the sentence level generate words beyond the target level. |
| Approach: | They propose a method to control the level of a sentence in a text simplification task . they add the target grade level as input and weight words in the loss function . |
| Outcome: | The proposed method improves both BLEU and SARI scores and achieves aggressive rewriting. |
MovieCORE: COgnitive REasoning in Movies (2025.emnlp-main)
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Gueter Josmy Faure, Min-Hung Chen, Jia-Fong Yeh, Ying Cheng, Hung-Ting Su, Yung-Hao Tang, Shang-Hong Lai, Winston H. Hsu
| Challenge: | MovieCORE is a video question answering dataset that focuses on surface-level comprehension. |
| Approach: | They propose a video question-answer dataset that uses large language models as thought agents to generate and refine high-quality question-anchor pairs. |
| Outcome: | The proposed model improves model reasoning capabilities post-training by 25% . the proposed model is based on a large language model and is scalable to a wide range of tasks . |
Linguistic Complexity Loss in Text-Based Therapy (2021.naacl-main)
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| Challenge: | linguistic complexity loss in text-based therapy can be used to identify patterns of mental health . authors: clients who reported more anxiety used less lexically diverse language . |
| Approach: | They analyze linguistic complexity loss in online therapy conversations as it relates to mental health . they find that clients used less lexically diverse language when they were more anxious . |
| Outcome: | The proposed analysis shows that therapists use more complex language when clients are anxious . the authors show that analyzing linguistic complexity can identify meaningful patterns in mental health . |
Measuring the Impact of (Psycho-)Linguistic and Readability Features and Their Spill Over Effects on the Prediction of Eye Movement Patterns (2022.acl-long)
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| Challenge: | Existing work to predict gaze patterns during naturalistic reading has not been conducted on general text characteristics. |
| Approach: | They propose to use two eye-tracking corpora of naturalistic reading and two language models to test their performance. |
| Outcome: | The proposed models predict eye-tracking measures during naturalistic reading and language processing. |
EXPRES Corpus for A Field-specific Automated Exploratory Study of L2 English Expert Scientific Writing (2022.lrec-1)
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| Challenge: | Developing proficient writing skills in English is a debated topic since the 1990s . RAs are an academic genre that hold a central place in academia . |
| Approach: | They propose to use a linguistic assessment model to assess the linguistic profile of research articles written in L2 English. |
| Outcome: | The proposed model can help scholars adapt to the writing norms of their communities of practice. |
Limited Linguistic Diversity in Embodied AI Datasets (2026.acl-long)
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Selma Liliane Wanna, Agnes Luhtaru, Jonathan Salfity, Ryan Barron, Juston Moore, Cynthia Matuszek, Mitch Pryor
| Challenge: | Language is a key modality in Vision-Language-Action (VLA) models, yet its linguistic characteristics are poorly documented. |
| Approach: | They propose to audit VLA corpora to characterize what kinds of instructions they contain . they quantify instruction language along complementary dimensions including lexical variety, duplication and overlap, semantic similarity, and syntactic complexity. |
| Outcome: | The proposed dataset audit of several widely used VLA datasets shows that many datasets rely on highly repetitive, template-like commands with limited structural variation yielding a narrow distribution of instruction forms. |
Controllable Sentence Simplification (2020.lrec-1)
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| Challenge: | Text simplification is often considered an all-purpose generic task where the same simplifications are suitable for all but multiple audiences can benefit from simplified text in different ways. |
| Approach: | They propose a controllable simplification model that provides explicit control on simplification systems based on Sequence-to-Sequence models. |
| Outcome: | The proposed model outperforms standard models on simplification benchmarks. |
WojoodRelations: Arabic Relation Extraction Corpus and Modeling (2025.emnlp-main)
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| Challenge: | Existing work on Arabic RE remains limited due to the language’s rich morphology and syntactic complexity, and the lack of large, high-quality datasets. |
| Approach: | They propose to use WojoodRelations to extract relation relationships from Arabic textual data using relation-aware templates and GPT-Joint to perform relation-based retrieval. |
| Outcome: | The proposed method achieves a Cohen’s of 0.92, indicating high reliability, and supervised models achieve 92.89% F1 for RE, while LLMs obtain 72.73% F1 . |
AI Argues Differently: Distinct Argumentative and Linguistic Patterns of LLMs in Persuasive Contexts (2025.emnlp-main)
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| Challenge: | Distinguishing LLM-generated text from human-written is a key challenge for safe and ethical NLP, especially in high-stake settings such as persuasive online discourse. |
| Approach: | They propose to use general-purpose linguistic features and domain-specific features related to argument quality to compare human- and LLM-authored arguments. |
| Outcome: | The proposed framework compares arguments by humans and three LLMs using two easily-interpretable feature sets. |