---
title: "CoNLL 2026 — all accepted papers with summaries and citations"
description: "All 47 papers of CoNLL 2026, the most cited first; those with our summary link to it. Among them: Discovering Lexical Gaps Using…"
canonical: "https://research.elamur.ai/free/en/venues/conll/2026/papers/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/venues/conll/2026/papers/)

[home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [CoNLL](https://md.research.elamur.ai/free/en/venues/conll/) / [2026](https://md.research.elamur.ai/free/en/venues/conll/2026/) / papers

# CoNLL 2026: all accepted papers

47 papers · the most cited first · [← CoNLL 2026](https://md.research.elamur.ai/free/en/venues/conll/2026/)

1. **[Discovering Lexical Gaps Using Embeddings from Multilingual LLMs ↗](https://aclanthology.org/2026.conll-main.39/)**Yoonwon Jung, Aaron S. Cohen, Ben Bergen*1 citation*
2. **[Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions](https://md.research.elamur.ai/free/en/papers/scivetti-2026-language-models-learn-constructional-semantics/)**Wesley Scivetti, Ethan Gotlieb Wilcox, Nathan Schneider et al.*1 citation · our summary*
3. **[Symbolic Grounding Reveals Representational Bottlenecks in Abstract Visual Reasoning](https://md.research.elamur.ai/free/en/papers/vaishnav-2026-symbolic-grounding-reveals-representational-bottlenecks/)**Mohit Vaishnav, Tanel Tammet*1 citation · our summary*
4. **[Syntactically-guided Information Maintenance in Sentence Comprehension ↗](https://aclanthology.org/2026.conll-main.5/)**Shinnosuke Isono, Kohei Kajikawa*1 citation*
5. **[A Dataset for Oral Reading in Young English Readers](https://md.research.elamur.ai/free/en/papers/rose-2026-dataset-oral-reading-young-english/)**Madison Rose, Michael Bennie, Valeria Pagliai et al.*our summary*
6. **[A Method for Learning Large-Scale Computational Construction Grammars from Semantically Annotated Corpora](https://md.research.elamur.ai/free/en/papers/eecke-2026-method-learning-large-scale-computational/)**Paul Van Eecke, Katrien Beuls*our summary*
7. **[A framework for analyzing concept representations in neural models](https://md.research.elamur.ai/free/en/papers/naowarat-2026-framework-analyzing-concept-representations-neural/)**Burin Naowarat, Hao Tang, Sharon Goldwater*our summary*
8. **[Addressing the Ecological Fallacy in Larger LMs with Human Context](https://md.research.elamur.ai/free/en/papers/soni-2026-addressing-ecological-fallacy-larger-lms/)**Nikita 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 ↗](https://aclanthology.org/2026.conll-main.43/)**Nolan Chai, Tianqi Zhang, Alex Warstadt
10. **[Automated Refinement of Essay Scoring Rubrics for Language Models via Reflect-and-Revise ↗](https://aclanthology.org/2026.conll-main.47/)**Keno Harada, Lui Yoshida, Takeshi Kojima et al.
11. **[Bridging Linguistic Structure and Mechanistic Interpretability for Conceptual Interpretation in Language Models](https://md.research.elamur.ai/free/en/papers/aljaafari-2026-bridging-linguistic-structure-mechanistic-interpretability/)**Nura Aljaafari, Danilo Carvalho, Andre Freitas*our summary*
12. **[CAIT: A Syntactic Parsing Toolkit for Child–Adult InTeractions](https://md.research.elamur.ai/free/en/papers/padovani-2026-cait-syntactic-parsing-toolkit-child/)**Francesca Padovani, Xiulin Yang, Bastian Bunzeck et al.*our summary*
13. **[Capturing Classic Authorial Style in Long-Form Story Generation with GRPO Fine-Tuning ↗](https://aclanthology.org/2026.conll-main.31/)**Jinlong Liu, Mark G. Lee, Mohammed Bahja et al.
14. **[Child-directed speech facilitates production, not comprehension, in BabyLMs](https://md.research.elamur.ai/free/en/papers/bunzeck-2026-child-directed-speech-facilitates-production/)**Bastian Bunzeck, Sina Zarrieß*our summary*
15. **[Cognitively Inspired Developmental Trajectories Improve Explore-Exploit Dynamics in Neural Agent Emergent Communication ↗](https://aclanthology.org/2026.conll-main.8/)**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 networks](https://md.research.elamur.ai/free/en/papers/hobbs-2026-collocational-bootstrapping-hypothesis-about-learning/)**Claire Hobbs, R. Thomas McCoy*our summary*
17. **[Could language models win the International Linguistics Olympiad? ↗](https://aclanthology.org/2026.conll-main.28/)**Jamie Garnham, Ehsan Shareghi
18. **[Differences in Typological Alignment in Language Models' Treatment of Differential Argument Marking ↗](https://aclanthology.org/2026.conll-main.16/)**Iskar Deng, Nathalia Xu, Shane Steinert-Threlkeld
19. **[Evaluating Humanlike Memory Effects in Transformers Using Item Recognition Tasks ↗](https://aclanthology.org/2026.conll-main.1/)**Christian Clark, William Schuler
20. **[Event-Guided Slot Interaction for Multi-Domain Dialogue State Tracking](https://md.research.elamur.ai/free/en/papers/xia-2026-event-guided-slot-interaction-multi/)**Ying Xia, Wei Liu*our summary*
21. **[Examining Large Language Models' form-meaning mappings of information structure constructions in Mandarin Chinese ↗](https://aclanthology.org/2026.conll-main.37/)**Shihui Li, Xiaojuan Tan, Jelke Bloem
22. **[From Dependency to CCG to Incremental CCG: Approaches to Flexible Word Order in Turkish ↗](https://aclanthology.org/2026.conll-main.36/)**Özge Bakay, Oğuz Kerem Yıldız, Rajesh Bhatt et al.
23. **[From Sparse to Sense-Grounded: Wikipedia Training for Ukrainian Visual-WSD ↗](https://aclanthology.org/2026.conll-main.29/)**Yurii Laba, Rostyslav O. Hryniv
24. **[Harnessing Linguistic Dissimilarity for Language Generalization on Unseen Low-Resource Varieties ↗](https://aclanthology.org/2026.conll-main.17/)**Jinju Kim, Haeji Jung, Youjeong Roh et al.
25. **[Information-Theoretic Storage Cost in Sentence Comprehension ↗](https://aclanthology.org/2026.conll-main.2/)**Kohei Kajikawa, Shinnosuke Isono, Ethan Gotlieb Wilcox
26. **[Linguistic Profiling of Transformer Embedding Geometry ↗](https://aclanthology.org/2026.conll-main.10/)**Lucia Domenichelli, Dominique Brunato, Felice Dell'Orletta
27. **[Logic-Level Evaluation of Logical Table-to-Text Generation](https://md.research.elamur.ai/free/en/papers/trigg-2026-logic-level-evaluation-logical-table/)**Lena Trigg, Dean F. Hougen, Ahsan Bilal*our summary*
28. **[Measuring the Effects of Visual Salience in Human and AI Descriptions with Image Editing ↗](https://aclanthology.org/2026.conll-main.18/)**Nina Gregorio, Edoardo Ponti, Sharon Goldwater
29. **[Mechanistic Interpretability of Animacy Effects on Structure Choice in GPT-2 ↗](https://aclanthology.org/2026.conll-main.38/)**Yue Li, Yan Cong, Elaine J. Francis
30. **[Metric Grammars: A usage-based grammatical formalism that supports generation, parsing and morphological innovation](https://md.research.elamur.ai/free/en/papers/tabor-2026-metric-grammars-usage-based-grammatical/)**Whitney Tabor, Hyosun Lee*our summary*
31. **[Modeling Human Adversarial Strategy Adaptation in Multi-Turn Language Model Interactions ↗](https://aclanthology.org/2026.conll-main.22/)**Zijun Ding
32. **[Now They See It, Now They Don't: Multimodal Reward Models Exhibit Unreliability in Physical World Constraints ↗](https://aclanthology.org/2026.conll-main.20/)**Sadaf Ghaffari, Nikhil Krishnaswamy
33. **[On the scaling relationship between cloze probabilities and language model next-token prediction ↗](https://aclanthology.org/2026.conll-main.32/)**Cassandra L Jacobs, Morgan Grobol
34. **[Presupposition and Reasoning in Conditionals: A Theory-Based Study of Humans and LLMs ↗](https://aclanthology.org/2026.conll-main.26/)**Tara Azin, Yongan Yu, Raj Singh et al. · 🏆 Outstanding Paper
35. **[RECAP: Resistance Capture in Text-based Mental Health Counseling with Large Language Models ↗](https://aclanthology.org/2026.conll-main.33/)**Anqi Li, Yuqian Chen, Yu Lu et al.
36. **[Readers make targeted regressions to plausible errors in reanalysis of “noisy-channel garden-path” sentences ↗](https://aclanthology.org/2026.conll-main.25/)**Thomas Hikaru Clark, Roger P. Levy, Edward Gibson · 🏆 Outstanding Paper
37. **[Revisiting Age of Acquisition in Curriculum Learning: Disentangling Lexical Features and Semantic Structure ↗](https://aclanthology.org/2026.conll-main.40/)**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 Task](https://md.research.elamur.ai/free/en/papers/petersen-2026-sense-sensitivity-reasoning-models-are/)**Dawson Petersen, Abhishek Purushothama, Nathan Schneider*our summary*
39. **[Similar Predictions, Different Processes: A Multi-Level Comparison of Human and Multimodal LLM Language Prediction](https://md.research.elamur.ai/free/en/papers/wang-2026-similar-predictions-different-processes-multi/)**Shuqi Wang, Zhenguang Cai*our summary*
40. **[ThinkStruct: RST-Aware Attention for Logical Reasoning in Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/tran-2026-thinkstruct-rst-aware-attention-logical/)**Nhi Thao Tran, Tien Le, Toan Pham et al.*our summary*
41. **[Traces of Social Competence in Large Language Models ↗](https://aclanthology.org/2026.conll-main.45/)**Tom Kouwenhoven, Michiel T. van der Meer, Max J. van Duijn
42. **[Uncovering Autoregressive LLM Knowledge of Thematic Fit in Event Representation ↗](https://aclanthology.org/2026.conll-main.11/)**Safeyah Khaled Alshemali, Daniel Bauer, Yuval Marton
43. **[What Brain Data Adds to Language Model Training](https://md.research.elamur.ai/free/en/papers/merlin-2026-what-brain-data-adds-language/)**Gabriele Merlin, Omer Moussa, Mariya Toneva*our summary*
44. **[What Exactly do Children Receive in Language Acquisition? A Case Study on CHILDES with Automated Detection of Filler-Gap Dependencies](https://md.research.elamur.ai/free/en/papers/zhou-2026-what-exactly-do-children-receive/)**Zhenghao Zhou, William Dai, Maya Viswanathan et al.*our summary*
45. **[When transformers learn “impossible” languages, what do they learn? ↗](https://aclanthology.org/2026.conll-main.24/)**Ram Janarthan, Coleman Haley, Sharon Goldwater · 🏆 Best Paper
46. **[Who Generates More Empathetic Responses–-Humans or LLMs? A Comparative Evaluation with Human and LLM Judges](https://md.research.elamur.ai/free/en/papers/welivita-2026-who-generates-more-empathetic-responses/)**Anuradha Welivita, Fawzia Zeitoun, Pearl Pu*our summary*
47. **[Word predictability estimates from language models are not robust to tokenizer vocabulary](https://md.research.elamur.ai/free/en/papers/nguyen-2026-word-predictability-estimates-language-models/)**Kien Nguyen, Suhas Arehalli*our summary*
- [← back to](https://md.research.elamur.ai/free/en/venues/conll/2026/) — CoNLL 2026