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Methodology
← Resources & Methods
Natural Language Processing
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Resources & Methods
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Language Modeling
1090 directly classified papers
Papers per year
2003: 2
2006: 3
2007: 5
2008: 2
2009: 2
2011: 1
2012: 3
2013: 4
2014: 2
2015: 1
2016: 10
2017: 25
2018: 33
2019: 52
2020: 93
2021: 125
2022: 232
2023: 156
2024: 139
2025: 199
2026: 1
Papers
UDParse @ SIGTYP 2024 Shared Task : Modern Language Models for Historical Languages
EACL 2024
Can Language Models Induce Grammatical Knowledge from Indirect Evidence?
EMNLP 2024
Allen Institute for AI @ SIGTYP 2024 Shared Task on Word Embedding Evaluation for Ancient and Historical Languages
EACL 2024
Neuron Specialization: Leveraging Intrinsic Task Modularity for Multilingual Machine Translation
EMNLP 2024
Structure Guided Prompt: Instructing Large Language Model in Multi-Step Reasoning by Exploring Graph Structure of the Text
EMNLP 2024
Putting Back the Stops: Integrating Syntax with Neural Topic Models
IJCAI 2024
LLMSegm: Surface-level Morphological Segmentation Using Large Language Model
COLING 2024
The Lou Dataset - Exploring the Impact of Gender-Fair Language in German Text Classification
EMNLP 2024
Semiparametric Token-Sequence Co-Supervision
ACL 2024
Dialogue for Prompting: A Policy-Gradient-Based Discrete Prompt Generation for Few-Shot Learning
AAAI 2024
SparseFit: Few-shot Prompting with Sparse Fine-tuning for Jointly Generating Predictions and Natural Language Explanations
ACL 2024
Unlabeled Debiasing in Downstream Tasks via Class-wise Low Variance Regularization
EMNLP 2024
Modeling Nonnative Sentence Processing with L2 Language Models
EMNLP 2024
TEMA: Token Embeddings Mapping for Enriching Low-Resource Language Models
EMNLP 2024
LEAF: Linguistically Enhanced Event Temporal Relation Framework
EMNLP 2023
Revisiting Entropy Rate Constancy in Text
EMNLP 2023
nanoT5: Fast & Simple Pre-training and Fine-tuning of T5 Models with Limited Resources
EMNLP 2023
Time-Aware Language Modeling for Historical Text Dating
EMNLP 2023
Mixed-domain Language Modeling for Processing Long Legal Documents
EMNLP 2023
Do Language Models Learn about Legal Entity Types during Pretraining?
EMNLP 2023
Rosetta Stone at KSAA-RD Shared Task: A Hop From Language Modeling To Word–Definition Alignment
EMNLP 2023
Arabic dialect identification: An in-depth error analysis on the MADAR parallel corpus
EMNLP 2023
Measuring Pointwise 𝒱-Usable Information In-Context-ly
EMNLP 2023
The Linearity of the Effect of Surprisal on Reading Times across Languages
EMNLP 2023
Are Language Models Sensitive to Semantic Attraction? A Study on Surprisal
ACL 2023
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