Who cites «Curriculum Learning» · page 4

659 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

Curating Datasets for Better Performance with Example Training Dynamics — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
Curricular Next Conversation Prediction Pretraining for Transcript Segmentation — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
Curriculum Learning for Graph Neural Networks: A Multiview Competence-based Approach — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Data Selection Curriculum for Abstractive Text Summarization — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
Data Selection for Language Models via Importance Resampling — 2023 · arXiv:2302.03169
Detecting Contradictory COVID-19 Drug Efficacy Claims from Biomedical Literature — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Easy-to-Hard Learning for Information Extraction — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
Efficient Methods for Natural Language Processing: A Survey — 2023 · Transactions of the Association for Computational Linguistics
Empower Nested Boolean Logic via Self-Supervised Curriculum Learning — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Eureka: Human-Level Reward Design via Coding Large Language Models — 2023 · arXiv:2310.12931
Few-Shot Structured Policy Learning for Multi-Domain and Multi-Task Dialogues — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
Fixed Input Parameterization for Efficient Prompting — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
Fixing MoE Over-Fitting on Low-Resource Languages in Multilingual Machine Translation — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
GPT-wee: How Small Can a Small Language Model Really Get? — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
Generalization on the Unseen, Logic Reasoning and Degree Curriculum — 2023 · arXiv:2301.13105
Gradual Language Model Adaptation Using Fine-Grained Typology — 2023 · Proceedings of the 5th Workshop on Research in Computational Linguistic Typology and Multilingual NLP
How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases — 2023 · arXiv:2305.19905
How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
HuCurl: Human-induced Curriculum Discovery — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
INFORM : Information eNtropy based multi-step reasoning FOR large language Models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Improving Autoregressive Grammatical Error Correction with Non-autoregressive Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
In-sample Curriculum Learning by Sequence Completion for Natural Language Generation — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Knowledge Tracing: A Survey — 2023 · ACM Computing Surveys 55(11)
LaSQuE: Improved Zero-Shot Classification from Explanations Through Quantifier Modeling and Curriculum Learning — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
Leveraging Domain Adaptation and Data Augmentation to Improve Qur'anic IR in English and Arabic — 2023 · Proceedings of ArabicNLP 2023
Ling-CL: Understanding NLP Models through Linguistic Curricula — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
M2DF: Multi-grained Multi-curriculum Denoising Framework for Multimodal Aspect-based Sentiment Analysis — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Measuring Pointwise $\mathcalV$-Usable Information In-Context-ly — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
Mitigating Data Imbalance and Representation Degeneration in Multilingual Machine Translation — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
Mmi01 at The BabyLM Challenge: Linguistically Motivated Curriculum Learning for Pretraining in Low-Resource Settings — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
Modeling Easiness for Training Transformers with Curriculum Learning — 2023 · Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
Multi-Agent Language Learning: Symbolic Mapping — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
Multi-Row, Multi-Span Distant Supervision For Table+Text Question Answering — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
MultiTabQA: Generating Tabular Answers for Multi-Table Question Answering — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
NLU on Data Diets: Dynamic Data Subset Selection for NLP Classification Tasks — 2023 · Proceedings of the Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP)
Non-compositional Expression Generation Based on Curriculum Learning and Continual Learning — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
OMNI: Open-endedness via Models of human Notions of Interestingness — 2023 · arXiv:2306.01711
On the Benefits of Learning to Route in Mixture-of-Experts Models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
On the effect of curriculum learning with developmental data for grammar acquisition — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
Optimizing GPT-2 Pretraining on BabyLM Corpus with Difficulty-based Sentence Reordering — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
PCC: Paraphrasing with Bottom-k Sampling and Cyclic Learning for Curriculum Data Augmentation — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
Paloma: A Benchmark for Evaluating Language Model Fit — 2023 · arXiv:2312.10523
Path Spuriousness-aware Reinforcement Learning for Multi-Hop Knowledge Graph Reasoning — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
PolyLM: An Open Source Polyglot Large Language Model — 2023 · arXiv:2307.06018
Position: AI Evaluation Should Learn from How We Test Humans — 2023 · arXiv:2306.10512
Rethinking Label Smoothing on Multi-hop Question Answering — 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics
Rethinking Semi-supervised Learning with Language Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
Search Query Spell Correction with Weak Supervision in E-commerce — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 5: Industry Track)
Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs — 2023 · arXiv:2303.08114
SteloCoder: a Decoder-Only LLM for Multi-Language to Python Code Translation — 2023 · arXiv:2310.15539
Summarization-based Data Augmentation for Document Classification — 2023 · Proceedings of the 4th New Frontiers in Summarization Workshop
Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversations — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
TaCo: Enhancing Cross-Lingual Transfer for Low-Resource Languages in LLMs through Translation-Assisted Chain-of-Thought Processes — 2023 · arXiv:2311.10797
The NPU-MSXF Speech-to-Speech Translation System for IWSLT 2023 Speech-to-Speech Translation Task — 2023 · Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)
The Rise and Potential of Large Language Model Based Agents: A Survey — 2023 · arXiv:2309.07864
Too Much Information: Keeping Training Simple for BabyLMs — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
Tool Learning with Foundation Models — 2023 · arXiv:2304.08354
Train Global, Tailor Local: Minimalist Multilingual Translation into Endangered Languages — 2023 · Proceedings of the Sixth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2023)
Understanding Translationese in Cross-Lingual Summarization — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
Unsupervised Discontinuous Constituency Parsing with Mildly Context-Sensitive Grammars — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Vector Norms as an Approximation of Syntactic Complexity — 2023 · Proceedings of the Second Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2023)
ViStruct: Visual Structural Knowledge Extraction via Curriculum Guided Code-Vision Representation — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
WeCheck: Strong Factual Consistency Checker via Weakly Supervised Learning — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
A Generalist Neural Algorithmic Learner — 2022 · arXiv:2209.11142
A Human-machine Interface for Few-shot Rule Synthesis for Information Extraction — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: System Demonstrations
A Model-agnostic Data Manipulation Method for Persona-based Dialogue Generation — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
A Survey of Active Learning for Natural Language Processing — 2022 · arXiv:2210.10109
ALLSH: Active Learning Guided by Local Sensitivity and Hardness — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
Accelerating the Training of Video Super-Resolution Models — 2022 · arXiv:2205.05069
Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets — 2022 · arXiv:2202.02794 · 39th International Conference on Machine Learning, Baltimore, Maryland, USA, PMLR 162, 2022
Adaptor: Objective-Centric Adaptation Framework for Language Models — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
Applying Natural Annotation and Curriculum Learning to Named Entity Recognition for Under-Resourced Languages — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
Balancing Multi-Domain Corpora Learning for Open-Domain Response Generation — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
Better Language Model with Hypernym Class Prediction — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
CIAug: Equipping Interpolative Augmentation with Curriculum Learning — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Challenges of Neural Machine Translation for Short Texts — 2022 · Computational Linguistics
Clean or Annotate: How to Spend a Limited Data Collection Budget — 2022 · Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing
ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Composing Structure-Aware Batches for Pairwise Sentence Classification — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
Cross-Modal Similarity-Based Curriculum Learning for Image Captioning — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Crossroads, Buildings and Neighborhoods: A Dataset for Fine-grained Location Recognition — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Curriculum Knowledge Distillation for Emoji-supervised Cross-lingual Sentiment Analysis — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Curriculum Learning Meets Weakly Supervised Multimodal Correlation Learning — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Curriculum Prompt Learning with Self-Training for Abstractive Dialogue Summarization — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Curriculum-guided Abstractive Summarization for Mental Health Online Posts — 2022 · Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis (LOUHI)
Data Cartography for Low-Resource Neural Machine Translation — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Data Selection Curriculum for Neural Machine Translation — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Distilling Causal Effect from Miscellaneous Other-Class for Continual Named Entity Recognition — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Do Data-based Curricula Work? — 2022 · Proceedings of the Third Workshop on Insights from Negative Results in NLP
Efficient Pre-training of Masked Language Model via Concept-based Curriculum Masking — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Efficient Training of Neural Transducer for Speech Recognition — 2022 · arXiv:2204.10586
Extreme Zero-Shot Learning for Extreme Text Classification — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Feeding What You Need by Understanding What You Learned — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Finding Sub-task Structure with Natural Language Instruction — 2022 · Proceedings of the First Workshop on Learning with Natural Language Supervision
From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
Generalizing Morphological Inflection Systems to Unseen Lemmas — 2022 · Proceedings of the 19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology
Generative Entity Typing with Curriculum Learning — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Generic and Trend-aware Curriculum Learning for Relation Extraction — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Hierarchical Curriculum Learning for AMR Parsing — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)