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home / docs / papers / cited-by / Who cites «Curriculum Learning» · page 2

Who cites «Curriculum Learning» · page 2

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

Pages: 1 · 2 · 3 · 4 · 5 · 6 · 7

  1. Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum — 2024 · arXiv:2405.13226
  2. Decoder-only Streaming Transformer for Simultaneous Translation — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  3. Development of Cognitive Intelligence in Pre-trained Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  4. Discovering and Articulating Frames of Communication from Social Media Using Chain-of-Thought Reasoning — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  5. Do LLMs learn a true syntactic universal? — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  6. Efficient Continual Pre-training for Building Domain Specific Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  7. Empowering Tree-structured Entailment Reasoning: Rhetorical Perception and LLM-driven Interpretability — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  8. Enhancing Agent Learning through World Dynamics Modeling — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  9. Enhancing Alignment using Curriculum Learning & Ranked Preferences — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  10. Exploring Curriculum Learning for Vision-Language Tasks: A Study on Small-Scale Multimodal Training — 2024 · The 2nd BabyLM Challenge at the 28th Conference on Computational Natural Language Learning
  11. FIRE: A Dataset for Financial Relation Extraction — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  12. FairFlow: Mitigating Dataset Biases through Undecided Learning for Natural Language Understanding — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  13. From General LLM to Translation: How We Dramatically Improve Translation Quality Using Human Evaluation Data for LLM Finetuning — 2024 · Proceedings of the Ninth Conference on Machine Translation
  14. Generating from AMRs into High and Low-Resource Languages using Phylogenetic Knowledge and Hierarchical QLoRA Training (HQL) — 2024 · Proceedings of the 17th International Natural Language Generation Conference
  15. GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  16. HiCuLR: Hierarchical Curriculum Learning for Rhetorical Role Labeling of Legal Documents — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  17. IT2ACL Learning Easy-to-Hard Instructions via 2-Phase Automated Curriculum Learning for Large Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  18. Instruction Tuning with Human Curriculum — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  19. Is Child-Directed Speech Effective Training Data for Language Models? — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  20. LeanAgent: Lifelong Learning for Formal Theorem Proving — 2024 · arXiv:2410.06209
  21. Meme-ingful Analysis: Enhanced Understanding of Cyberbullying in Memes Through Multimodal Explanations — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  22. Metaphor Detection with Context Enhancement and Curriculum Learning — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  23. Multi-Step Reasoning with Large Language Models, a Survey — 2024 · arXiv:2407.11511
  24. Neuro-Symbolic Data Generation for Math Reasoning — 2024 · arXiv:2412.04857
  25. Orion-14B: Open-source Multilingual Large Language Models — 2024 · arXiv:2401.12246
  26. PopALM: Popularity-Aligned Language Models for Social Media Trendy Response Prediction — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  27. Recent Trends in Personalized Dialogue Generation: A Review of Datasets, Methodologies, and Evaluations — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  28. SceMQA: A Scientific College Entrance Level Multimodal Question Answering Benchmark — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
  29. Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models — 2024 · arXiv:2401.01335
  30. Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models -- The Story Goes On — 2024 · arXiv:2407.08348
  31. Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization — 2024 · arXiv:2402.14270
  32. The Role of Data Curation in Image Captioning — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  33. The Unreasonable Effectiveness of Easy Training Data for Hard Tasks — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  34. Towards Data-Efficient Language Models: A Child-Inspired Approach to Language Learning — 2024 · The 2nd BabyLM Challenge at the 28th Conference on Computational Natural Language Learning
  35. Tree-Instruct: A Preliminary Study of the Intrinsic Relationship between Complexity and Alignment — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  36. TriSum: Learning Summarization Ability from Large Language Models with Structured Rationale — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  37. Tuning LLMs with Contrastive Alignment Instructions for Machine Translation in Unseen, Low-resource Languages — 2024 · Proceedings of the Seventh Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2024)
  38. WavChat: A Survey of Spoken Dialogue Models — 2024 · arXiv:2411.13577
  39. Zamba: A Compact 7B SSM Hybrid Model — 2024 · arXiv:2405.16712
  40. A Survey of Large Language Models — 2023 · arXiv:2303.18223 · Frontiers of Computer Science, Volume 20, Issue 12, Article 2012627 (2026)
  41. A surprisal oracle for active curriculum language modeling — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
  42. Accelerating Multiple Intent Detection and Slot Filling via Targeted Knowledge Distillation — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  43. Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
  44. BabyLM Challenge: Curriculum learning based on sentence complexity approximating language acquisition — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
  45. Breaking the Language Barrier: Improving Cross-Lingual Reasoning with Structured Self-Attention — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  46. Byte-ranked Curriculum Learning for BabyLM Strict-small Shared Task 2023 — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
  47. CLCL: Non-compositional Expression Detection with Contrastive Learning and Curriculum Learning — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  48. CLIMB – Curriculum Learning for Infant-inspired Model Building — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
  49. Can training neural language models on a curriculum with developmentally plausible data improve alignment with human reading behavior? — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
  50. Code Execution with Pre-trained Language Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  51. Complexity-Guided Curriculum Learning for Text Graphs — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  52. Data Selection Curriculum for Abstractive Text Summarization — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  53. Data Selection for Language Models via Importance Resampling — 2023 · arXiv:2302.03169
  54. 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)
  55. Efficient Methods for Natural Language Processing: A Survey — 2023 · Transactions of the Association for Computational Linguistics
  56. Empower Nested Boolean Logic via Self-Supervised Curriculum Learning — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  57. Eureka: Human-Level Reward Design via Coding Large Language Models — 2023 · arXiv:2310.12931
  58. Fixed Input Parameterization for Efficient Prompting — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  59. Fixing MoE Over-Fitting on Low-Resource Languages in Multilingual Machine Translation — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  60. 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
  61. Generalization on the Unseen, Logic Reasoning and Degree Curriculum — 2023 · arXiv:2301.13105
  62. How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases — 2023 · arXiv:2305.19905
  63. How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  64. HuCurl: Human-induced Curriculum Discovery — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  65. INFORM : Information eNtropy based multi-step reasoning FOR large language Models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  66. Improving Autoregressive Grammatical Error Correction with Non-autoregressive Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  67. 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)
  68. Knowledge Tracing: A Survey — 2023 · ACM Computing Surveys 55(11)
  69. Leveraging Domain Adaptation and Data Augmentation to Improve Qur'anic IR in English and Arabic — 2023 · Proceedings of ArabicNLP 2023
  70. Ling-CL: Understanding NLP Models through Linguistic Curricula — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  71. 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
  72. 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
  73. Mitigating Data Imbalance and Representation Degeneration in Multilingual Machine Translation — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  74. 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
  75. Modeling Easiness for Training Transformers with Curriculum Learning — 2023 · Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
  76. 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)
  77. 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)
  78. 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)
  79. Non-compositional Expression Generation Based on Curriculum Learning and Continual Learning — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  80. OMNI: Open-endedness via Models of human Notions of Interestingness — 2023 · arXiv:2306.01711
  81. 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
  82. 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
  83. 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
  84. 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
  85. Paloma: A Benchmark for Evaluating Language Model Fit — 2023 · arXiv:2312.10523
  86. 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
  87. PolyLM: An Open Source Polyglot Large Language Model — 2023 · arXiv:2307.06018
  88. Position: AI Evaluation Should Learn from How We Test Humans — 2023 · arXiv:2306.10512
  89. Rethinking Label Smoothing on Multi-hop Question Answering — 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics
  90. Rethinking Semi-supervised Learning with Language Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  91. 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)
  92. Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs — 2023 · arXiv:2303.08114
  93. 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)
  94. TaCo: Enhancing Cross-Lingual Transfer for Low-Resource Languages in LLMs through Translation-Assisted Chain-of-Thought Processes — 2023 · arXiv:2311.10797
  95. The Rise and Potential of Large Language Model Based Agents: A Survey — 2023 · arXiv:2309.07864
  96. Too Much Information: Keeping Training Simple for BabyLMs — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
  97. Tool Learning with Foundation Models — 2023 · arXiv:2304.08354
  98. Understanding Translationese in Cross-Lingual Summarization — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  99. 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)
  100. ViStruct: Visual Structural Knowledge Extraction via Curriculum Guided Code-Vision Representation — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

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