📰 CoNLL 2024: all accepted papers

69 papers · the most cited first · ← CoNLL 2024

1. Translating Across Cultures: LLMs for Intralingual Cultural Adaptation ↗Pushpdeep Singh, Mayur Patidar, Lovekesh Vig12 citations
2. An Empirical Comparison of Vocabulary Expansion and Initialization Approaches For Language Models ↗Nandini Mundra, Aditya Nanda Kishore Khandavally, Raj Dabre et al.5 citations
3. Global-Pruner: A Stable and Efficient Pruner for Retraining-Free Pruning of Encoder-Based Language Models ↗Guangzhen Yao, Yuehan Wang, Hui Xu et al.5 citations
4. Revisiting Hierarchical Text Classification: Inference and Metrics ↗Roman Plaud, Matthieu Labeau, Antoine Saillenfest et al.5 citations
5. Continuous Attentive Multimodal Prompt Tuning for Few-Shot Multimodal Sarcasm Detection ↗Soumyadeep Jana, Animesh Dey, Ranbir Singh Sanasam4 citations
6. Explaining the Hardest Errors of Contextual Embedding Based Classifiers ↗Claudio Moisés Valiense De Andrade, Washington Cunha, Guilherme Fonseca et al.4 citations
7. Information Association for Language Model Updating by Mitigating LM-Logical Discrepancy ↗Pengfei Yu, Heng Ji4 citations
8. Lossy Context Surprisal Predicts Task-Dependent Patterns in Relative Clause Processing ↗Kate McCurdy, Michael Hahn4 citations
9. Multi-Cultural Norm Base: Frame-based Norm Discovery in Multi-Cultural Settings ↗Viet Thanh Pham, Shilin Qu, Farhad Moghimifar et al.4 citations
10. Critical Questions Generation: Motivation and Challenges ↗Blanca Calvo Figueras, Rodrigo Agerri3 citations
11. Text2Afford: Probing Object Affordance Prediction abilities of Language Models solely from Text ↗Sayantan Adak, Daivik Agrawal, Animesh Mukherjee et al.3 citations
12. The Effect of Surprisal on Reading Times in Information Seeking and Repeated Reading ↗Keren Gruteke Klein, Yoav Meiri, Omer Shubi et al.3 citations
13. A Multimodal Large Language Model “Foresees” Objects Based on Verb Information but Not Gender ↗Shuqi Wang, Xufeng Duan, Zhenguang Cai2 citations
14. Advancing Arabic Sentiment Analysis: ArSen Benchmark and the Improved Fuzzy Deep Hybrid NetworkYang Fang, Cheng Xu, Shuhao Guan et al.2 citations · our summary
15. CrowdCounter: A benchmark type-specific multi-target counterspeech dataset ↗Punyajoy Saha, Abhilash Datta, Abhik Jana et al.2 citations
16. Generalizations across filler-gap dependencies in neural language models ↗Katherine Howitt, Sathvik Nair, Allison Dods et al.2 citations
17. Leveraging a Cognitive Model to Measure Subjective Similarity of Human and GPT-4 Written Content ↗Tyler Malloy, Maria José Ferreira, Fei Fang et al.2 citations
18. On Functional Competence of LLMs for Linguistic Disambiguation ↗Raihan Kibria, Sheikh Intiser Uddin Dipta, Muhammad Abdullah Adnan2 citations
19. Words That Stick: Using Keyword Cohesion to Improve Text Segmentation ↗Amit Maraj, Miguel Vargas Martin, Masoud Makrehchi2 citations
20. AIStorySimilarity: Quantifying Story Similarity Using Narrative for Search, IP Infringement, and Guided Creativity ↗Jon Chun1 citation
21. EditEval: An Instruction-Based Benchmark for Text Improvements ↗Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang et al.1 citation
22. Further Compressing Distilled Language Models via Frequency-aware Partial Sparse Coding of Embeddings ↗Kohki Tamura, Naoki Yoshinaga, Masato Neishi1 citation
23. Is Structure Dependence Shaped for Efficient Communication?: A Case Study on Coordination ↗Kohei Kajikawa, Yusuke Kubota, Yohei Oseki1 citation
24. Large Language Model Recall Uncertainty is Modulated by the Fan Effect ↗Jesse Roberts, Kyle Moore, Douglas Fisher et al.1 citation
25. SPAWNing Structural Priming Predictions from a Cognitively Motivated Parser ↗Grusha Prasad, Tal Linzen1 citation
26. Self-supervised speech representations display some human-like cross-linguistic perceptual abilities ↗Joselyn Rodriguez, Kamala Sreepada, Ruolan Leslie Famularo et al.1 citation
27. A Novel Instruction Tuning Method for Vietnamese Mathematical Reasoning using Trainable Open-Source Large Language Models ↗Quang-Vinh Nguyen, Thanh-Do Nguyen, Van-Vinh Nguyen et al.
28. A surprisal oracle for when every layer counts ↗Xudong Hong, Sharid Loáiciga, Asad Sayeed
29. Aligning Alignments: Do Colexification and Distributional Similarity Align as Measures of cross-lingual Lexical Alignment? ↗Taelin Karidi, Eitan Grossman, Omri Abend
30. AntLM: Bridging Causal and Masked Language Models ↗Xinru Yu, Bin Guo, Shiwei Luo et al.
31. Are BabyLMs Second Language Learners? ↗Lukas Edman, Lisa Bylinina, Faeze Ghorbanpour et al.
32. Automatic Quality Estimation for Data Selection and Curriculum Learning ↗Hiep Nguyen, Lynn Yip, Justin DeBenedetto
33. BERTtime Stories: Investigating the Role of Synthetic Story Data in Language Pre-training ↗Nikitas Theodoropoulos, Giorgos Filandrianos, Vassilis Lyberatos et al.
34. BabyHGRN: Exploring RNNs for Sample-Efficient Language Modeling ↗Patrick Haller, Jonas Golde, Alan Akbik
35. BabyLM Challenge: Experimenting with Self-Distillation and Reverse-Distillation for Language Model Pre-Training on Constrained Datasets ↗Aakarsh Nair, Alina Hancharova, Mayank Kumar et al.
36. BabyLM Challenge: Exploring the effect of variation sets on language model training efficiency ↗Akari Haga, Akiyo Fukatsu, Miyu Oba et al.
37. BabyLlama-2: Ensemble-Distilled Models Consistently Outperform Teachers With Limited Data ↗Jean-Loup Tastet, Inar Timiryasov
38. Causal ATE Mitigates Unintended Bias in Controlled Text Generation ↗Rahul Madhavan, Kahini Wadhawan
39. Choosy Babies Need One Coach: Inducing Mode-Seeking Behavior in BabyLlama with Reverse KL Divergence ↗Shaozhen Shi, Yevgen Matusevych, Malvina Nissim
40. ConcreteGPT: A Baby GPT-2 Based on Lexical Concreteness and Curriculum Learning ↗Luca Capone, Alessandro Bondielli, Alessandro Lenci
41. Developmentally Plausible Multimodal Language Models Are Highly Modular ↗Alina Klerings, Christian Bartelt, Aaron Mueller
42. Different Ways to Forget: Linguistic Gates in Recurrent Neural Networks ↗Cristiano Chesi, Veronica Bressan, Matilde Barbini et al.
43. Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible DataBadr AlKhamissi, Yingtian Tang, Abdülkadir Gökce et al.our summary
44. ELC-ParserBERT: Low-Resource Language Modeling Utilizing a Parser Network With ELC-BERT ↗Rufus Behr
45. Exploring Curriculum Learning for Vision-Language Tasks: A Study on Small-Scale Multimodal Training ↗Rohan Saha, Abrar Fahim, Alona Fyshe et al.
46. Extending the BabyLM Initiative : Promoting Diversity in Datasets and Metrics through High-Quality Linguistic Corpora ↗Laurent Prévot, Sheng-Fu Wang, Jou-An Chi et al.
47. Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora ↗Michael Y. Hu, Aaron Mueller, Candace Ross et al.
48. From Babble to Words: Pre-Training Language Models on Continuous Streams of Phonemes ↗Zébulon Goriely, Richard Diehl Martinez, Andrew Caines et al.
49. GPT or BERT: why not both? ↗Lucas Georges Gabriel Charpentier, David Samuel
50. Global Learning with Triplet Relations in Abstractive Summarization ↗Fengyu Lu, Jiaxin Duan, Junfei Liu
51. Graphemes vs. phonemes: battling it out in character-based language models ↗Bastian Bunzeck, Daniel Duran, Leonie Schade et al.
52. How Are Metaphors Processed by Language Models? The Case of Analogies ↗Joanne Boisson, Asahi Ushio, Hsuvas Borkakoty et al.
53. Image-conditioned human language comprehension and psychometric benchmarking of visual language models ↗Subha Nawer Pushpita, Roger P. Levy
54. Integrating Quasi-symbolic Conceptual Knowledge into Language Model Pre-training ↗Gábor Berend
55. Investigating large language models for their competence in extracting grammatically sound sentences from transcribed noisy utterances ↗Alina Wróblewska
56. Less is More: Pre-Training Cross-Lingual Small-Scale Language Models with Cognitively-Plausible Curriculum Learning Strategies ↗Suchir Salhan, Richard Diehl Martinez, Zébulon Goriely et al.
57. NeLLCom-X: A Comprehensive Neural-Agent Framework to Simulate Language Learning and Group Communication ↗Yuchen Lian, Tessa Verhoef, Arianna Bisazza
58. Of Models and Men: Probing Neural Networks for Agreement Attraction with Psycholinguistic Data ↗Maxim Bazhukov, Ekaterina Voloshina, Sergey Pletenev et al.
59. One-Vs-Rest Neural Network English Grapheme Segmentation: A Linguistic Perspective ↗Samuel Rose, Nina Dethlefs, C. Kambhampati
60. PRACT: Optimizing Principled Reasoning and Acting of LLM Agent ↗Zhiwei Liu, Weiran Yao, Jianguo Zhang et al.
61. Solving the Challenge Set without Solving the Task: On Winograd Schemas as a Test of Pronominal Coreference Resolution ↗Ian Porada, Jackie CK Cheung
62. Teaching Tiny Minds: Exploring Methods to Enhance Knowledge Distillation for Small Language Models ↗Hong Meng Yam, Nathan Paek
63. Towards Data-Efficient Language Models: A Child-Inspired Approach to Language Learning ↗Mohammad Amin Ghanizadeh, Mohammad Javad Dousti
64. TpT-ADE: Transformer Based Two-Phase ADE Extraction ↗Suryamukhi Kuchibhotla, Manish Singh
65. Transformer verbatim in-context retrieval across time and scale ↗Kristijan Armeni, Marko Pranjić, Senja Pollak
66. Using Curriculum Masking Based on Child Language Development to Train a Large Language Model with Limited Training DataEvan Lucas, Dylan Gaines, Tagore Rao Kosireddy et al.our summary
67. What should Baby Models read? Exploring Sample-Efficient Data Composition on Model Performance ↗Hong Meng Yam, Nathan Paek
68. WhatIf: Leveraging Word Vectors for Small-Scale Data Augmentation ↗Alex Lyman, Bryce Hepner
69. When Babies Teach Babies: Can student knowledge sharing outperform Teacher-Guided Distillation on small datasets? ↗Srikrishna Iyer

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