Who cites «RACE: Large-scale ReAding Comprehension Dataset From Examinations» · page 4

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

SharPT: Shared Latent Space Prompt Tuning — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
Shepherd: A Critic for Language Model Generation — 2023 · arXiv:2308.04592
SkillQG: Learning to Generate Question for Reading Comprehension Assessment — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
Skywork: A More Open Bilingual Foundation Model — 2023 · arXiv:2310.19341
Sparse Neural Retrieval Model for Efficient Cross-Domain Retrieval-Based Question Answering — 2023 · Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation
Specialist or Generalist? Instruction Tuning for Specific NLP Tasks — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Statistically Profiling Biases in Natural Language Reasoning Datasets and Models — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
Symbolic Discovery of Optimization Algorithms — 2023 · arXiv:2302.06675
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants — 2023 · arXiv:2308.16884 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics 749-775 2024
The Falcon Series of Open Language Models — 2023 · arXiv:2311.16867
The Generative AI Paradox: "What It Can Create, It May Not Understand — 2023 · arXiv:2311.00059
The Impacts of Unanswerable Questions on the Robustness of Machine Reading Comprehension Models — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
Toward Unified Controllable Text Generation via Regular Expression Instruction — 2023 · Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Training NLI Models Through Universal Adversarial Attack — 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics
Tunable Soft Prompts are Messengers in Federated Learning — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
UltraFeedback: Boosting Language Models with Scaled AI Feedback — 2023 · arXiv:2310.01377
Universal Self-Adaptive Prompting — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Using contradictions improves question answering systems — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
WYWEB: A NLP Evaluation Benchmark For Classical Chinese — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
Weakly-Supervised Questions for Zero-Shot Relation Extraction — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
What's the Meaning of Superhuman Performance in Today's NLU? — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Won''t Get Fooled Again: Answering Questions with False Premises — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
``World Knowledge'''' in Multiple Choice Reading Comprehension — 2023 · Proceedings of the Sixth Fact Extraction and VERification Workshop (FEVER)
An MRC Framework for Semantic Role Labeling — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
Analyzing Multi-Task Learning for Abstractive Text Summarization — 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
Answer Uncertainty and Unanswerability in Multiple-Choice Machine Reading Comprehension — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
Atlas: Few-shot Learning with Retrieval Augmented Language Models — 2022 · arXiv:2208.03299
BBQ: A hand-built bias benchmark for question answering — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
BanglaRQA: A Benchmark Dataset for Under-resourced Bangla Language Reading Comprehension-based Question Answering with Diverse Question-Answer Types — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models — 2022 · arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Can We Guide a Multi-Hop Reasoning Language Model to Incrementally Learn at Each Single-Hop? — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
Cascading Biases: Investigating the Effect of Heuristic Annotation Strategies on Data and Models — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Case-Based Abductive Natural Language Inference — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
Compliance Checking with NLI: Privacy Policies vs. Regulations — 2022 · arXiv:2204.01845
ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Data Augmentation for Biomedical Factoid Question Answering — 2022 · Proceedings of the 21st Workshop on Biomedical Language Processing
DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale — 2022 · arXiv:2201.05596
Different Tunes Played with Equal Skill: Exploring a Unified Optimization Subspace for Parameter-Efficient Tuning — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Discovering Language Model Behaviors with Model-Written Evaluations — 2022 · arXiv:2212.09251
Document-level Event Factuality Identification via Machine Reading Comprehension Frameworks with Transfer Learning — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
Editing Models with Task Arithmetic — 2022 · arXiv:2212.04089
Eliciting and Understanding Cross-task Skills with Task-level Mixture-of-Experts — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
ElitePLM: An Empirical Study on General Language Ability Evaluation of Pretrained Language Models — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Evaluating the Knowledge Dependency of Questions — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Exploring The Landscape of Distributional Robustness for Question Answering Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
FQuAD2.0: French Question Answering and Learning When You Don''t Know — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension — our card · 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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)
Fine- and Coarse-Granularity Hybrid Self-Attention for Efficient BERT — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
How Long Is Enough? Exploring the Optimal Intervals of Long-Range Clinical Note Language Modeling — 2022 · Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis (LOUHI)
Hyperdecoders: Instance-specific decoders for multi-task NLP — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
JBNU-CCLab at SemEval-2022 Task 7: DeBERTa for Identifying Plausible Clarifications in Instructional Texts — 2022 · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Learning Invariant Representation Improves Robustness for MRC Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Leveraging Large Language Models for Multiple Choice Question Answering — 2022 · arXiv:2210.12353
Life after BERT: What do Other Muppets Understand about Language? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Lite Unified Modeling for Discriminative Reading Comprehension — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
LogiTorch: A PyTorch-based library for logical reasoning on natural language — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Logic Traps in Evaluating Attribution Scores — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
MoEfication: Transformer Feed-forward Layers are Mixtures of Experts — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
Modeling Hierarchical Reasoning Chains by Linking Discourse Units and Key Phrases for Reading Comprehension — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
Not to Overfit or Underfit the Source Domains? An Empirical Study of Domain Generalization in Question Answering — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
OPERA: Operation-Pivoted Discrete Reasoning over Text — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
PILE: Pairwise Iterative Logits Ensemble for Multi-Teacher Labeled Distillation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track
PPT: Pre-trained Prompt Tuning for Few-shot Learning — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
PaLM: Scaling Language Modeling with Pathways — 2022 · arXiv:2204.02311
Perturbation Augmentation for Fairer NLP — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Possible Stories: Evaluating Situated Commonsense Reasoning under Multiple Possible Scenarios — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
ProQA: Structural Prompt-based Pre-training for Unified Question Answering — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
QAConv: Question Answering on Informative Conversations — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
QuALITY: Question Answering with Long Input Texts, Yes! — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Question Answering Infused Pre-training of General-Purpose Contextualized Representations — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
RealTime QA: What''s the Answer Right Now? — 2022 · arXiv:2207.13332
Retrieval Augmentation for Commonsense Reasoning: A Unified Approach — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Scaling Laws Under the Microscope: Predicting Transformer Performance from Small Scale Experiments — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Self-critiquing models for assisting human evaluators — 2022 · arXiv:2206.05802
Synthetic Data Generation for Multilingual Domain-Adaptable Question Answering Systems — 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
TIE: Topological Information Enhanced Structural Reading Comprehension on Web Pages — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
To Answer or Not To Answer? Improving Machine Reading Comprehension Model with Span-based Contrastive Learning — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
Training Compute-Optimal Large Language Models — 2022 · arXiv:2203.15556
UKP-SQUARE: An Online Platform for Question Answering Research — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
UL2: Unifying Language Learning Paradigms — 2022 · arXiv:2205.05131
Unsupervised Domain Adaptation for Question Generation with DomainData Selection and Self-training — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model — 2022 · arXiv:2201.11990
Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization? — 2022 · arXiv:2204.05832
What Language Model to Train if You Have One Million GPU Hours? — 2022 · arXiv:2210.15424
What Makes Reading Comprehension Questions Difficult? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers — 2022 · arXiv:2206.01861
`Am I the Bad One''? Predicting the Moral Judgement of the Crowd Using Pre–trained Language Models — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
基于相似度进行句子选择的机器阅读理解数据增强(Machine reading comprehension data Augmentation for sentence selection based on similarity) — 2022 · Proceedings of the 21st Chinese National Conference on Computational Linguistics
A Chinese Machine Reading Comprehension Dataset Automatic Generated Based on Knowledge Graph — 2021 · Proceedings of the 20th Chinese National Conference on Computational Linguistics
A Robustly Optimized BERT Pre-training Approach with Post-training — 2021 · Proceedings of the 20th Chinese National Conference on Computational Linguistics
Answering Chinese Elementary School Social Studies Multiple Choice Questions — 2021
Arabic Offensive Language on Twitter: Analysis and Experiments — 2021 · Proceedings of the Sixth Arabic Natural Language Processing Workshop