📰 CoNLL 2026: all accepted papers

47 papers · the most cited first · ← CoNLL 2026

1. Discovering Lexical Gaps Using Embeddings from Multilingual LLMs ↗Yoonwon Jung, Aaron S. Cohen, Ben Bergen1 citation
2. Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus ConstructionsWesley Scivetti, Ethan Gotlieb Wilcox, Nathan Schneider et al.1 citation · our summary
3. Symbolic Grounding Reveals Representational Bottlenecks in Abstract Visual ReasoningMohit Vaishnav, Tanel Tammet1 citation · our summary
4. Syntactically-guided Information Maintenance in Sentence Comprehension ↗Shinnosuke Isono, Kohei Kajikawa1 citation
5. A Dataset for Oral Reading in Young English ReadersMadison Rose, Michael Bennie, Valeria Pagliai et al.our summary
6. A Method for Learning Large-Scale Computational Construction Grammars from Semantically Annotated CorporaPaul Van Eecke, Katrien Beulsour summary
7. A framework for analyzing concept representations in neural modelsBurin Naowarat, Hao Tang, Sharon Goldwaterour summary
8. Addressing the Ecological Fallacy in Larger LMs with Human ContextNikita Soni, Dhruv Vijay Kunjadiya, Pratham Piyush Shah et al.our summary
9. An Information-Theoretic Study of RLHF-Induced Uniformity in Large Language Model Outputs ↗Nolan Chai, Tianqi Zhang, Alex Warstadt
10. Automated Refinement of Essay Scoring Rubrics for Language Models via Reflect-and-Revise ↗Keno Harada, Lui Yoshida, Takeshi Kojima et al.
11. Bridging Linguistic Structure and Mechanistic Interpretability for Conceptual Interpretation in Language ModelsNura Aljaafari, Danilo Carvalho, Andre Freitasour summary
12. CAIT: A Syntactic Parsing Toolkit for Child–Adult InTeractionsFrancesca Padovani, Xiulin Yang, Bastian Bunzeck et al.our summary
13. Capturing Classic Authorial Style in Long-Form Story Generation with GRPO Fine-Tuning ↗Jinlong Liu, Mark G. Lee, Mohammed Bahja et al.
14. Child-directed speech facilitates production, not comprehension, in BabyLMsBastian Bunzeck, Sina Zarrießour summary
15. Cognitively Inspired Developmental Trajectories Improve Explore-Exploit Dynamics in Neural Agent Emergent Communication ↗Jan Dziewoński, Flor Miriam Plaza-del-Arco, Tessa Verhoef
16. Collocational bootstrapping: A hypothesis about the learning of subject-verb agreement in humans and neural networksClaire Hobbs, R. Thomas McCoyour summary
17. Could language models win the International Linguistics Olympiad? ↗Jamie Garnham, Ehsan Shareghi
18. Differences in Typological Alignment in Language Models' Treatment of Differential Argument Marking ↗Iskar Deng, Nathalia Xu, Shane Steinert-Threlkeld
19. Evaluating Humanlike Memory Effects in Transformers Using Item Recognition Tasks ↗Christian Clark, William Schuler
20. Event-Guided Slot Interaction for Multi-Domain Dialogue State TrackingYing Xia, Wei Liuour summary
21. Examining Large Language Models' form-meaning mappings of information structure constructions in Mandarin Chinese ↗Shihui Li, Xiaojuan Tan, Jelke Bloem
22. From Dependency to CCG to Incremental CCG: Approaches to Flexible Word Order in Turkish ↗Özge Bakay, Oğuz Kerem Yıldız, Rajesh Bhatt et al.
23. From Sparse to Sense-Grounded: Wikipedia Training for Ukrainian Visual-WSD ↗Yurii Laba, Rostyslav O. Hryniv
24. Harnessing Linguistic Dissimilarity for Language Generalization on Unseen Low-Resource Varieties ↗Jinju Kim, Haeji Jung, Youjeong Roh et al.
25. Information-Theoretic Storage Cost in Sentence Comprehension ↗Kohei Kajikawa, Shinnosuke Isono, Ethan Gotlieb Wilcox
26. Linguistic Profiling of Transformer Embedding Geometry ↗Lucia Domenichelli, Dominique Brunato, Felice Dell'Orletta
27. Logic-Level Evaluation of Logical Table-to-Text GenerationLena Trigg, Dean F. Hougen, Ahsan Bilalour summary
28. Measuring the Effects of Visual Salience in Human and AI Descriptions with Image Editing ↗Nina Gregorio, Edoardo Ponti, Sharon Goldwater
29. Mechanistic Interpretability of Animacy Effects on Structure Choice in GPT-2 ↗Yue Li, Yan Cong, Elaine J. Francis
30. Metric Grammars: A usage-based grammatical formalism that supports generation, parsing and morphological innovationWhitney Tabor, Hyosun Leeour summary
31. Modeling Human Adversarial Strategy Adaptation in Multi-Turn Language Model Interactions ↗Zijun Ding
32. Now They See It, Now They Don't: Multimodal Reward Models Exhibit Unreliability in Physical World Constraints ↗Sadaf Ghaffari, Nikhil Krishnaswamy
33. On the scaling relationship between cloze probabilities and language model next-token prediction ↗Cassandra L Jacobs, Morgan Grobol
34. Presupposition and Reasoning in Conditionals: A Theory-Based Study of Humans and LLMs ↗Tara Azin, Yongan Yu, Raj Singh et al. · 🏆 Outstanding Paper
35. RECAP: Resistance Capture in Text-based Mental Health Counseling with Large Language Models ↗Anqi Li, Yuqian Chen, Yu Lu et al.
36. Readers make targeted regressions to plausible errors in reanalysis of “noisy-channel garden-path” sentences ↗Thomas Hikaru Clark, Roger P. Levy, Edward Gibson · 🏆 Outstanding Paper
37. Revisiting Age of Acquisition in Curriculum Learning: Disentangling Lexical Features and Semantic Structure ↗Ian Gifford, Aaron Shah, Catherine Chen et al.
38. Sense and Sensitivity: “Reasoning” Models are More Robust, but can Diverge from Human Consensus in a Legal Interpretation TaskDawson Petersen, Abhishek Purushothama, Nathan Schneiderour summary
39. Similar Predictions, Different Processes: A Multi-Level Comparison of Human and Multimodal LLM Language PredictionShuqi Wang, Zhenguang Caiour summary
40. ThinkStruct: RST-Aware Attention for Logical Reasoning in Machine Reading ComprehensionNhi Thao Tran, Tien Le, Toan Pham et al.our summary
41. Traces of Social Competence in Large Language Models ↗Tom Kouwenhoven, Michiel T. van der Meer, Max J. van Duijn
42. Uncovering Autoregressive LLM Knowledge of Thematic Fit in Event Representation ↗Safeyah Khaled Alshemali, Daniel Bauer, Yuval Marton
43. What Brain Data Adds to Language Model TrainingGabriele Merlin, Omer Moussa, Mariya Tonevaour summary
44. What Exactly do Children Receive in Language Acquisition? A Case Study on CHILDES with Automated Detection of Filler-Gap DependenciesZhenghao Zhou, William Dai, Maya Viswanathan et al.our summary
45. When transformers learn “impossible” languages, what do they learn? ↗Ram Janarthan, Coleman Haley, Sharon Goldwater · 🏆 Best Paper
46. Who Generates More Empathetic Responses–-Humans or LLMs? A Comparative Evaluation with Human and LLM JudgesAnuradha Welivita, Fawzia Zeitoun, Pearl Puour summary
47. Word predictability estimates from language models are not robust to tokenizer vocabularyKien Nguyen, Suhas Arehalliour summary

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/venues/conll/2026/papers/