--- title: "Conference on Computational Natural Language… — works, page" description: "123 works of Conference on Computational Natural Language Learning (CoNLL) in our library · page 2 of 2, the most cited first." canonical: "https://research.elamur.ai/free/en/venues/conll/works/page/2/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/venues/conll/works/page/2/) [home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [Conference on Computational Natural Language…](https://md.research.elamur.ai/free/en/venues/conll/) / [works](https://md.research.elamur.ai/free/en/venues/conll/works/) / page 2 # Works of Conference on Computational Natural Language Learning (CoNLL) 123 works · page 2 of 2 · the most cited first · [← Conference on Computational Natural Language…](https://md.research.elamur.ai/free/en/venues/conll/) [← prev](https://md.research.elamur.ai/free/en/venues/conll/works/) [1](https://md.research.elamur.ai/free/en/venues/conll/works/) **2** 101. [**Sense and Sensitivity: “Reasoning” Models are More Robust, but can Diverge from Human Consensus in a Legal Interpretation Task**Dawson Petersen, Abhishek Purushothama, Nathan Schneider*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/petersen-2026-sense-sensitivity-reasoning-models-are/) 102. [**Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions**Wesley Scivetti, Ethan Gotlieb Wilcox, Nathan Schneider, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/scivetti-2026-language-models-learn-constructional-semantics/) 103. [**Addressing the Ecological Fallacy in Larger LMs with Human Context**Nikita Soni, Dhruv Vijay Kunjadiya, Pratham Piyush Shah, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/soni-2026-addressing-ecological-fallacy-larger-lms/) 104. [**Symbolic Grounding Reveals Representational Bottlenecks in Abstract Visual Reasoning**Mohit Vaishnav, Tanel Tammet*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/vaishnav-2026-symbolic-grounding-reveals-representational-bottlenecks/) 105. [**What Exactly do Children Receive in Language Acquisition? A Case Study on CHILDES with Automated Detection of Filler-Gap Dependencies**Zhenghao Zhou, William Dai, Maya Viswanathan, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zhou-2026-what-exactly-do-children-receive/) 106. [**Bridging the Socioeconomic Gap in Education: A Hybrid AI and Human Annotation Approach**Nahed Abdelgaber, Labiba Jahan, Arham Vinit Doshi, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/abdelgaber-2025-bridging-socioeconomic-gap-education-hybrid/) 107. [**Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data**Badr AlKhamissi, Yingtian Tang, Abdülkadir Gökce, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alkhamissi-2024-dreaming-out-loud-self-synthesis/) 108. [**Universal Joint Morph-Syntactic Processing: The Open University of Israel's Submission to The CoNLL 2017 Shared Task**Amir More, Reut Tsarfaty*2017 · 1 citation*](https://md.research.elamur.ai/free/en/papers/more-2017-universal-joint-morph-syntactic-processing/) 109. [**Bridging Linguistic Structure and Mechanistic Interpretability for Conceptual Interpretation in Language Models**Nura Aljaafari, Danilo Carvalho, Andre Freitas*2026*](https://md.research.elamur.ai/free/en/papers/aljaafari-2026-bridging-linguistic-structure-mechanistic-interpretability/) 110. [**Child-directed speech facilitates production, not comprehension, in BabyLMs**Bastian Bunzeck, Sina Zarrieß*2026*](https://md.research.elamur.ai/free/en/papers/bunzeck-2026-child-directed-speech-facilitates-production/) 111. [**A Method for Learning Large-Scale Computational Construction Grammars from Semantically Annotated Corpora**Paul Van Eecke, Katrien Beuls*2026*](https://md.research.elamur.ai/free/en/papers/eecke-2026-method-learning-large-scale-computational/) 112. [**Collocational bootstrapping: A hypothesis about the learning of subject-verb agreement in humans and neural networks**Claire Hobbs, R. Thomas McCoy*2026*](https://md.research.elamur.ai/free/en/papers/hobbs-2026-collocational-bootstrapping-hypothesis-about-learning/) 113. [**What Brain Data Adds to Language Model Training**Gabriele Merlin, Omer Moussa, Mariya Toneva*2026*](https://md.research.elamur.ai/free/en/papers/merlin-2026-what-brain-data-adds-language/) 114. [**A framework for analyzing concept representations in neural models**Burin Naowarat, Hao Tang, Sharon Goldwater*2026*](https://md.research.elamur.ai/free/en/papers/naowarat-2026-framework-analyzing-concept-representations-neural/) 115. [**Word predictability estimates from language models are not robust to tokenizer vocabulary**Kien Nguyen, Suhas Arehalli*2026*](https://md.research.elamur.ai/free/en/papers/nguyen-2026-word-predictability-estimates-language-models/) 116. [**A Dataset for Oral Reading in Young English Readers**Madison Rose, Michael Bennie, Valeria Pagliai, et al.*2026*](https://md.research.elamur.ai/free/en/papers/rose-2026-dataset-oral-reading-young-english/) 117. [**Metric Grammars: A usage-based grammatical formalism that supports generation, parsing and morphological innovation**Whitney Tabor, Hyosun Lee*2026*](https://md.research.elamur.ai/free/en/papers/tabor-2026-metric-grammars-usage-based-grammatical/) 118. [**ThinkStruct: RST-Aware Attention for Logical Reasoning in Machine Reading Comprehension**Nhi Thao Tran, Tien Le, Toan Pham, et al.*2026*](https://md.research.elamur.ai/free/en/papers/tran-2026-thinkstruct-rst-aware-attention-logical/) 119. [**Logic-Level Evaluation of Logical Table-to-Text Generation**Lena Trigg, Dean F. Hougen, Ahsan Bilal*2026*](https://md.research.elamur.ai/free/en/papers/trigg-2026-logic-level-evaluation-logical-table/) 120. [**CAIT: A Syntactic Parsing Toolkit for Child–Adult InTeractions**Francesca Padovani, Xiulin Yang, Bastian Bunzeck, et al.*2026*](https://md.research.elamur.ai/free/en/papers/padovani-2026-cait-syntactic-parsing-toolkit-child/) 121. [**Similar Predictions, Different Processes: A Multi-Level Comparison of Human and Multimodal LLM Language Prediction**Shuqi Wang, Zhenguang Cai*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-similar-predictions-different-processes-multi/) 122. [**Who Generates More Empathetic Responses–-Humans or LLMs? A Comparative Evaluation with Human and LLM Judges**Anuradha Welivita, Fawzia Zeitoun, Pearl Pu*2026*](https://md.research.elamur.ai/free/en/papers/welivita-2026-who-generates-more-empathetic-responses/) 123. [**Event-Guided Slot Interaction for Multi-Domain Dialogue State Tracking**Ying Xia, Wei Liu*2026*](https://md.research.elamur.ai/free/en/papers/xia-2026-event-guided-slot-interaction-multi/) [← prev](https://md.research.elamur.ai/free/en/venues/conll/works/) [1](https://md.research.elamur.ai/free/en/venues/conll/works/) **2** - [← back to](https://md.research.elamur.ai/free/en/venues/conll/) — Conference on Computational Natural Language Learning (CoNLL)