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

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

Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Enhancing Linguistic Competence of Language Models through Pre-training with Language Learning Tasks — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
InferenceDynamics: Adaptive LLM Routing through Structured Capability and Knowledge Profiling — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Infinity-MoE: Generalizing Mixture of Experts to Infinite Experts — 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)
Jais 2: A Family of Arabic-Centric Open Large Language Models — 2026 · arXiv:2608.13580
LoopFormer: Elastic-Depth Looped Transformers for Latent Reasoning via Shortcut Modulation — 2026 · arXiv:2602.11451
ModularMoE: Fast LLM Customization with Parameter-Sharing Mixture-of-Experts for Low-Resource Settings — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning — 2026 · arXiv:2604.12374
Offline Preference Optimization via Maximum Marginal Likelihood Estimation — 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
One Token Is Enough: Improving Diffusion Language Models with a Sink Token — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
PHEB: An European Portuguese High School-Level LLM Benchmark — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
Position Encoding with Random Float Sampling Enhances Length Generalization of Transformers — 2026 · Findings of the Association for Computational Linguistics: EACL 2026
RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Suppressing Final Layer Hidden State Jumps in Transformer Pretraining — 2026 · Findings of the Association for Computational Linguistics: EACL 2026
500xCompressor: Generalized Prompt Compression for Large Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
A Systematic Survey of Automatic Prompt Optimization Techniques — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
AQuilt: Weaving Logic and Self-Inspection into Low-Cost, High-Relevance Data Synthesis for Specialist LLMs — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Advancing MoE Efficiency: A Collaboration-Constrained Routing (C2R) Strategy for Better Expert Parallelism Design — 2025 · arXiv:2504.01337
Beyond Text Compression: Evaluating Tokenizers Across Scales — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
BlockPruner: Fine-grained Pruning for Large Language Models — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Condor: Enhance LLM Alignment with Knowledge-Driven Data Synthesis and Refinement — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
DOVE: A Large-Scale Multi-Dimensional Predictions Dataset Towards Meaningful LLM Evaluation — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Data Laundering: Artificially Boosting Benchmark Results through Knowledge Distillation — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Dream 7B: Diffusion Large Language Models — 2025 · arXiv:2508.15487
Efficient Domain Continual pretraining by Mitigating the Stability Gap — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs — 2025 · arXiv:2503.05139
Flexora: Flexible Low-Rank Adaptation for Large Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Front-Loading Reasoning: The Synergy between Pretraining and Post-Training Data — 2025 · arXiv:2510.03264
Generating Plausible Distractors for Multiple-Choice Questions via Student Choice Prediction — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
HICD: Hallucination-Inducing via Attention Dispersion for Contrastive Decoding to Mitigate Hallucinations in Large Language Models — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
ICLEval: Evaluating In-Context Learning Ability of Large Language Models — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
Implicit Reasoning in Large Language Models: A Comprehensive Survey — 2025 · arXiv:2509.02350
InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency — 2025 · arXiv:2508.18265
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models — 2025 · arXiv:2504.10479
LLMs May Perform MCQA by Selecting the Least Incorrect Option — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
Large Language Models Still Exhibit Bias in Long Text — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Locate-then-Merge: Neuron-Level Parameter Fusion for Mitigating Catastrophic Forgetting in Multimodal LLMs — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Math Neurosurgery: Isolating Language Models'' Math Reasoning Abilities Using Only Forward Passes — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Meta-rater: A Multi-dimensional Data Selection Method for Pre-training Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining — 2025 · arXiv:2505.07608
MoSLD: An Extremely Parameter-Efficient Mixture-of-Shared LoRAs for Multi-Task Learning — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
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)
Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts — 2025 · Proceedings of The Third Arabic Natural Language Processing Conference
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)
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
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)
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
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
The Gaps between Fine Tuning and In-context Learning in Bias Evaluation and Debiasing — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
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)
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)
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
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
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
Continual Learning of Large Language Models: A Comprehensive Survey — 2024 · arXiv:2404.16789
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
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
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)

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