Who cites «RACE: Large-scale ReAding Comprehension Dataset From Examinations» · page 2

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

Navigating the Landscape of Hint Generation Research: From the Past to the Future — 2025
Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
NeurIPS 2025 E2LM Competition : Early Training Evaluation of Language Models — 2025 · arXiv:2506.07731
Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts — 2025 · Proceedings of The Third Arabic Natural Language Processing Conference
Open-DeBias: Toward Mitigating Open-Set Bias in Language Models — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Option Symbol Matters: Investigating and Mitigating Multiple-Choice Option Symbol Bias of Large Language Models — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
PATCH: Learnable Tile-level Hybrid Sparsity for LLMs — 2025 · arXiv:2509.23410
PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity — 2025 · arXiv:2505.21411
Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUs — 2025 · arXiv:2504.07866
PersianMCQ-Instruct: A Comprehensive Resource for Generating Multiple-Choice Questions in Persian — 2025 · Proceedings of the First Workshop on Language Models for Low-Resource Languages
Position IDs Matter: An Enhanced Position Layout for Efficient Context Compression in Large Language Models — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Probing and Boosting Large Language Models Capabilities via Attention Heads — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Prompt Compression for Large Language Models: A Survey — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
RECALL: REpresentation-aligned Catastrophic-forgetting ALLeviation via Hierarchical Model Merging — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Recipes for Pre-training LLMs with MXFP8 — 2025 · arXiv:2506.08027
RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems? — 2025 · arXiv:2501.11284
Rubrik''s Cube: Testing a New Rubric for Evaluating Explanations on the CUBE dataset — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
SCOP: Evaluating the Comprehension Process of Large Language Models from a Cognitive View — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
SMoE: An Algorithm-System Co-Design for Pushing MoE to the Edge via Expert Substitution — 2025 · arXiv:2508.18983
SSMLoRA: Enhancing Low-Rank Adaptation with State Space Model — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Second Language (Arabic) Acquisition of LLMs via Progressive Vocabulary Expansion — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Self-Adjust Softmax — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Stochastic activations — 2025 · arXiv:2509.22358
TEEMIL : Towards Educational MCQ Difficulty Estimation in Indic Languages — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
TORSO: Template-Oriented Reasoning Towards General Tasks — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
The Gaps between Fine Tuning and In-context Learning in Bias Evaluation and Debiasing — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
The Threat of PROMPTS in Large Language Models: A System and User Prompt Perspective — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
The Tug of War Within: Mitigating the Fairness-Privacy Conflicts in Large Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Training Language Models to Critique With Multi-agent Feedback — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
UBench: Benchmarking Uncertainty in Large Language Models with Multiple Choice Questions — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Understanding Silent Data Corruption in LLM Training — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
Unveiling the Potential of BERT-family: A New Recipe for Building Scalable, General and Competitive Large Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
X-EcoMLA: Upcycling Pre-Trained Attention into MLA for Efficient and Extreme KV Compression — 2025 · arXiv:2503.11132
YuLan-Mini: Pushing the Limits of Open Data-efficient Language Model — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
\textit D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Models — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
État de l''art : évaluation, détection et mitigation des hallucinations des LLMs — 2025 · Actes des 18e Rencontres Jeunes Chercheurs en RI (RJCRI) et 27ème Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RECITAL)
難易度調整可能な多枝選択式読解問題自動生成手法とDirect Preference Optimizationによる難易度調整精度の向上 — 2025 · 言語処理学会第31回年次大会発表論文集 (NLP2025)
A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
A study of Vietnamese readability assessing through semantic and statistical features — 2024 · Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation
AMPO: Automatic Multi-Branched Prompt Optimization — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Adding Error Bars to Evals: A Statistical Approach to Language Model Evaluations — 2024 · arXiv:2411.00640
An Empirical Study of Mamba-based Language Models — 2024 · arXiv:2406.07887
An Information-Theoretic Approach to Analyze NLP Classification Tasks — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Analysing The Impact of Sequence Composition on Language Model Pre-Training — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Are Machines Better at Complex Reasoning? Unveiling Human-Machine Inference Gaps in Entailment Verification — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Automatic Generation and Evaluation of Reading Comprehension Test Items with Large Language Models — 2024 · Proceedings of the 3rd Workshop on Tools and Resources for People with REAding DIfficulties (READI) @ LREC-COLING 2024
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model — 2024 · arXiv:2402.07827
Bilingual Adaptation of Monolingual Foundation Models — 2024 · arXiv:2407.12869
Can GPT Redefine Medical Understanding? Evaluating GPT on Biomedical Machine Reading Comprehension — 2024 · Proceedings of the 23rd Workshop on Biomedical Natural Language Processing
Continual Learning of Large Language Models: A Comprehensive Survey — 2024 · arXiv:2404.16789
Correct after Answer: Enhancing Multi-Span Question Answering with Post-Processing Method — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
DDK: Distilling Domain Knowledge for Efficient Large Language Models — 2024 · arXiv:2407.16154
Data, Data Everywhere: A Guide for Pretraining Dataset Construction — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism — 2024 · arXiv:2401.02954
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model — 2024 · arXiv:2405.04434
DeepSeek-V3 Technical Report — 2024 · arXiv:2412.19437
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Demystifying Instruction Mixing for Fine-tuning Large Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
Desiderata For The Context Use Of Question Answering Systems — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Disperse-Then-Merge: Pushing the Limits of Instruction Tuning via Alignment Tax Reduction — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Distractor Generation Using Generative and Discriminative Capabilities of Transformer-based Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Distractor Generation in Multiple-Choice Tasks: A Survey of Methods, Datasets, and Evaluation — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Do Multilingual Large Language Models Mitigate Stereotype Bias? — 2024 · Proceedings of the 2nd Workshop on Cross-Cultural Considerations in NLP
DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
E^2-LLM: Efficient and Extreme Length Extension of Large Language Models — 2024 · arXiv:2401.06951
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling — 2024 · arXiv:2412.05271
Exploring Self-supervised Logic-enhanced Training for Large Language Models — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Eye-Tracking Features Masking Transformer Attention in Question-Answering Tasks — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
GPT-Fathom: Benchmarking Large Language Models to Decipher the Evolutionary Path towards GPT-4 and Beyond — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
GemmAr: Enhancing LLMs Through Arabic Instruction-Tuning — 2024 · arXiv:2407.02147
Generation Meets Verification: Accelerating Large Language Model Inference with Smart Parallel Auto-Correct Decoding — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs — 2024 · arXiv:2405.02774
Head-wise Shareable Attention for Large Language Models — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
HiRE: High Recall Approximate Top-$k$ Estimation for Efficient LLM Inference — 2024 · arXiv:2402.09360
Improving Bengali and Hindi Large Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Instruction Pre-Training: Language Models are Supervised Multitask Learners — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
InternLM2 Technical Report — 2024 · arXiv:2403.17297
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
KVSharer: Efficient Inference via Layer-Wise Dissimilar KV Cache Sharing — 2024 · arXiv:2410.18517
KorNAT: LLM Alignment Benchmark for Korean Social Values and Common Knowledge — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
LFED: A Literary Fiction Evaluation Dataset for Large Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
LLMBox: A Comprehensive Library for Large Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
LaCo: Large Language Model Pruning via Layer Collapse — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Language Models can Exploit Cross-Task In-context Learning for Data-Scarce Novel Tasks — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Large Language Models: A Survey — 2024 · arXiv:2402.06196
Large language models for education: A survey and outlook — 2024
LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding — 2024 · arXiv:2404.16710
LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Long Sequence Modeling with Attention Tensorization: From Sequence to Tensor Learning — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
MIND: Math Informed syNthetic Dialogues for Pretraining LLMs — 2024 · arXiv:2410.12881
Make Your LLM Fully Utilize the Context — 2024 · arXiv:2404.16811
Maximize Your Data''s Potential: Enhancing LLM Accuracy with Two-Phase Pretraining — 2024 · arXiv:2412.15285
McGill NLP Group Submission to the MRL 2024 Shared Task: Ensembling Enhances Effectiveness of Multilingual Small LMs — 2024 · Proceedings of the Fourth Workshop on Multilingual Representation Learning (MRL 2024)
Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance — 2024 · arXiv:2403.09085