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# Who cites «The NarrativeQA Reading Comprehension Challenge»

435 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/kocisky-2018-narrativeqa-reading-comprehension-challenge/)

Pages: **1** · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/kocisky-2018-narrativeqa-reading-comprehension-challenge-2/) · [3](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/kocisky-2018-narrativeqa-reading-comprehension-challenge-3/) · [4](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/kocisky-2018-narrativeqa-reading-comprehension-challenge-4/) · [5](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/kocisky-2018-narrativeqa-reading-comprehension-challenge-5/)

1. [A Survey on Evaluation of LLM-based Agents](https://aclanthology.org/2026.findings-acl.1330/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
2. [ARK: Answer-Centric Retriever Tuning via KG-augmented Curriculum Learning](https://aclanthology.org/2026.acl-long.371/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling](https://aclanthology.org/2026.acl-long.1779/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
4. [EduBench: A Portuguese Benchmark for Open-Ended Discursive Question Answering](https://aclanthology.org/2026.lrec-1.360/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
5. [GMSA: Enhancing Context Compression via Group Merging and Layer Semantic Alignment](https://aclanthology.org/2026.acl-long.1324/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
6. [HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs](https://aclanthology.org/2026.findings-acl.1880/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
7. [HiChunk: Evaluating and Enhancing Retrieval Augmented Generation with Hierarchical Chunking](https://aclanthology.org/2026.acl-long.1372/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
8. [LiveLongBench: Tackling Long-Context Understanding for Spoken Texts from Live Streams](https://aclanthology.org/2026.findings-acl.1485/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
9. [Mask Tokens as Prophet: Fine-Grained Cache Eviction for Efficient dLLM Inference](https://aclanthology.org/2026.findings-acl.170/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
10. [MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search](https://aclanthology.org/2026.acl-long.41/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
11. [More Than Efficiency: Embedding Compression Improves Domain Adaptation in Dense Retrieval](https://aclanthology.org/2026.surgellm-1.24/) *— 2026 · Proceedings of the First Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era (SURGeLLM 2026)*
12. [ReFreeKV: Towards Threshold-Free KV Cache Compression](https://aclanthology.org/2026.findings-acl.1541/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
13. [Read As Human: Compressing Context via Parallelizable Close Reading and Skimming](https://aclanthology.org/2026.acl-long.1309/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
14. [Situated Embedding Models for Context-Aware Dense Retrieval](https://aclanthology.org/2026.acl-short.5/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
15. [TopoRAG: Graph-based RAG via Topology-aware Approximate Nearest Neighbor Search](https://aclanthology.org/2026.findings-acl.1703/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
16. [A Comprehensive Survey on Long Context Language Modeling](https://arxiv.org/abs/2503.17407) *— 2025 · arXiv:2503.17407*
17. [Brevity is the soul of sustainability: Characterizing LLM response lengths](https://aclanthology.org/2025.findings-acl.1125/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
18. [CURIE: Evaluating LLMs On Multitask Scientific Long Context Understanding and Reasoning](https://arxiv.org/abs/2503.13517) *— 2025 · arXiv:2503.13517*
19. [Characterizing LLM Inference Energy-Performance Tradeoffs across Workloads and GPU Scaling](https://arxiv.org/abs/2501.08219) *— 2025 · arXiv:2501.08219*
20. [ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference](https://arxiv.org/abs/2502.00299) *— 2025 · arXiv:2502.00299*
21. [ClusterAttn: KV Cache Compression under Intrinsic Attention Clustering](https://aclanthology.org/2025.acl-long.703/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
22. [Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings](https://aclanthology.org/2025.emnlp-main.1150/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
23. [Culturally-Nuanced Story Generation for Reasoning in Low-Resource Languages: The Case of Javanese and Sundanese](https://arxiv.org/abs/2502.12932) *— 2025 · arXiv:2502.12932*
24. [DTCRS: Dynamic Tree Construction for Recursive Summarization](https://aclanthology.org/2025.acl-long.536/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
25. [Demystify Verbosity Compensation Behavior of Large Language Models](https://aclanthology.org/2025.uncertainlp-main.14/) *— 2025 · Proceedings of the 2nd Workshop on Uncertainty-Aware NLP (UncertaiNLP 2025)*
26. [Distance between Relevant Information Pieces Causes Bias in Long-Context LLMs](https://aclanthology.org/2025.findings-acl.28/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
27. [DocBench: A Benchmark for Evaluating LLM-based Document Reading Systems](https://aclanthology.org/2025.knowledgenlp-1.29/) *— 2025 · Proceedings of the 4th International Workshop on Knowledge-Augmented Methods for Natural Language Processing*
28. [DynamicKV: Task-Aware Adaptive KV Cache Compression for Long Context LLMs](https://aclanthology.org/2025.findings-emnlp.426/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
29. [E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning](https://aclanthology.org/2025.emnlp-main.970/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
30. [ELITR-Bench: A Meeting Assistant Benchmark for Long-Context Language Models](https://aclanthology.org/2025.coling-main.28/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
31. [ETHIC: Evaluating Large Language Models on Long-Context Tasks with High Information Coverage](https://aclanthology.org/2025.naacl-long.283/) *— 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)*
32. [EvolKV: Evolutionary KV Cache Compression for LLM Inference](https://aclanthology.org/2025.findings-emnlp.88/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
33. [Flaw or Artifact? Rethinking Prompt Sensitivity in Evaluating LLMs](https://aclanthology.org/2025.emnlp-main.1006/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
34. [Guess What I am Thinking: A Benchmark for Inner Thought Reasoning of Role-Playing Language Agents](https://aclanthology.org/2025.findings-emnlp.819/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
35. [How to Train Long-Context Language Models (Effectively)](https://aclanthology.org/2025.acl-long.366/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
36. [Implicit Reasoning in Large Language Models: A Comprehensive Survey](https://arxiv.org/abs/2509.02350) *— 2025 · arXiv:2509.02350*
37. [Instella: Fully Open Language Models with Stellar Performance](https://arxiv.org/abs/2511.10628) *— 2025 · arXiv:2511.10628*
38. [Judge as A Judge: Improving the Evaluation of Retrieval-Augmented Generation through the Judge-Consistency of Large Language Models](https://aclanthology.org/2025.findings-acl.301/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
39. [LADM: Long-context Training Data Selection with Attention-based Dependency Measurement for LLMs](https://aclanthology.org/2025.acl-long.154/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
40. [LLMs can be easily Confused by Instructional Distractions](https://aclanthology.org/2025.acl-long.957/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
41. [Large Language Models are good multi-lingual learners : When LLMs meet cross-lingual prompts](https://aclanthology.org/2025.coling-main.300/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
42. [M-LongDoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework](https://aclanthology.org/2025.emnlp-main.469/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
43. [MDCure: A Scalable Pipeline for Multi-Document Instruction-Following](https://aclanthology.org/2025.acl-long.1418/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
44. [More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives](https://aclanthology.org/2025.acl-long.1475/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
45. [NarratEX Dataset: Explaining the Dominant Narratives in News Texts](https://aclanthology.org/2025.findings-emnlp.1112/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
46. [OpeNLGauge: An Explainable Metric for NLG Evaluation with Open-Weights LLMs](https://aclanthology.org/2025.inlg-main.19/) *— 2025 · Proceedings of the 18th International Natural Language Generation Conference*
47. [ParallelComp: Parallel Long-Context Compressor for Length Extrapolation](https://arxiv.org/abs/2502.14317) *— 2025 · arXiv:2502.14317*
48. [PeerQA: A Scientific Question Answering Dataset from Peer Reviews](https://aclanthology.org/2025.naacl-long.22/) *— 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)*
49. [QwenLong-L1.5: Post-Training Recipe for Long-Context Reasoning and Memory Management](https://arxiv.org/abs/2512.12967) *— 2025 · arXiv:2512.12967*
50. [QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning](https://arxiv.org/abs/2505.17667) *— 2025 · arXiv:2505.17667*
51. [R$^3$Mem: Bridging Memory Retention and Retrieval via Reversible Compression](https://aclanthology.org/2025.findings-acl.235/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
52. [RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions](https://aclanthology.org/2025.emnlp-main.192/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
53. [SemEval 2025 Task 10: Multilingual Characterization and Extraction of Narratives from Online News](https://aclanthology.org/2025.semeval-1.331/) *— 2025 · Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)*
54. [SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains](https://aclanthology.org/2025.naacl-long.575/) *— 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)*
55. [SparseServe: Unlocking Parallelism for Dynamic Sparse Attention in Long-Context LLM Serving](https://arxiv.org/abs/2509.24626) *— 2025 · arXiv:2509.24626*
56. [The Essence of Contextual Understanding in Theory of Mind: A Study on Question Answering with Story Characters](https://aclanthology.org/2025.acl-long.1103/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
57. [Unlocking Speech Instruction Data Potential with Query Rewriting](https://aclanthology.org/2025.findings-acl.534/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
58. [VisDoM: Multi-Document QA with Visually Rich Elements Using Multimodal Retrieval-Augmented Generation](https://aclanthology.org/2025.naacl-long.310/) *— 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)*
59. [$\infty$Bench: Extending Long Context Evaluation Beyond 100K Tokens](https://aclanthology.org/2024.acl-long.814/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
60. [A + B: A General Generator-Reader Framework for Optimizing LLMs to Unleash Synergy Potential](https://aclanthology.org/2024.findings-acl.219/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
61. [A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts](https://arxiv.org/abs/2402.09727) *— 2024 · arXiv:2402.09727*
62. [A Simple and Effective $L_2$ Norm-Based Strategy for KV Cache Compression](https://aclanthology.org/2024.emnlp-main.1027/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
63. [A Survey on Detection of LLMs-Generated Content](https://aclanthology.org/2024.findings-emnlp.572/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
64. [An Empirical Study of Mamba-based Language Models](https://arxiv.org/abs/2406.07887) *— 2024 · arXiv:2406.07887*
65. [Beyond Natural Language: LLMs Leveraging Alternative Formats for Enhanced Reasoning and Communication](https://aclanthology.org/2024.findings-emnlp.623/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
66. [CLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models](https://aclanthology.org/2024.findings-emnlp.230/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
67. [CORM: Cache Optimization with Recent Message for Large Language Model Inference](https://arxiv.org/abs/2404.15949) *— 2024 · arXiv:2404.15949*
68. [Chain of Agents: Large Language Models Collaborating on Long-Context Tasks](https://arxiv.org/abs/2406.02818) *— 2024 · arXiv:2406.02818*
69. [Chunk, Align, Select: A Simple Long-sequence Processing Method for Transformers](https://aclanthology.org/2024.acl-long.729/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
70. [ContraDoc: Understanding Self-Contradictions in Documents with Large Language Models](https://aclanthology.org/2024.naacl-long.362/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
71. [Do Large Language Models Understand Conversational Implicature- A case study with a Chinese sitcom](https://aclanthology.org/2024.ccl-1.98/) *— 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)*
72. [DocFinQA: A Long-Context Financial Reasoning Dataset](https://aclanthology.org/2024.acl-short.42/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
73. [Evaluating Character Understanding of Large Language Models via Character Profiling from Fictional Works](https://aclanthology.org/2024.emnlp-main.456/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
74. [Exploring Scientific Hypothesis Generation with Mamba](https://aclanthology.org/2024.nlp4science-1.17/) *— 2024 · Proceedings of the 1st Workshop on NLP for Science (NLP4Science)*
75. [Extending Context Window of Large Language Models via Semantic Compression](https://aclanthology.org/2024.findings-acl.306/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
76. [Fine-Grained Modeling of Narrative Context: A Coherence Perspective via Retrospective Questions](https://aclanthology.org/2024.acl-long.317/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
77. [FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research](https://arxiv.org/abs/2405.13576) *— 2024 · arXiv:2405.13576*
78. [FragRel: Exploiting Fragment-level Relations in the External Memory of Large Language Models](https://aclanthology.org/2024.findings-acl.968/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
79. [Gated Delta Networks: Improving Mamba2 with Delta Rule](https://arxiv.org/abs/2412.06464) *— 2024 · arXiv:2412.06464*
80. [GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models](https://aclanthology.org/2024.findings-emnlp.746/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
81. [Grounding Language Model with Chunking-Free In-Context Retrieval](https://aclanthology.org/2024.acl-long.71/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
82. [HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly](https://arxiv.org/abs/2410.02694) *— 2024 · arXiv:2410.02694*
83. [HumBEL: A Human-in-the-Loop Approach for Evaluating Demographic Factors of Language Models in Human-Machine Conversations](https://aclanthology.org/2024.eacl-long.68/) *— 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
84. [Instruction Pre-Training: Language Models are Supervised Multitask Learners](https://aclanthology.org/2024.emnlp-main.148/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
85. [Is It Really Long Context if All You Need Is Retrieval? Towards Genuinely Difficult Long Context NLP](https://aclanthology.org/2024.emnlp-main.924/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
86. [Jamba: A Hybrid Transformer-Mamba Language Model](https://arxiv.org/abs/2403.19887) *— 2024 · arXiv:2403.19887*
87. [Knowledge Conflicts for LLMs: A Survey](https://aclanthology.org/2024.emnlp-main.486/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
88. [L-Eval: Instituting Standardized Evaluation for Long Context Language Models](https://aclanthology.org/2024.acl-long.776/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
89. [LFED: A Literary Fiction Evaluation Dataset for Large Language Models](https://aclanthology.org/2024.lrec-main.915/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
90. [LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators](https://arxiv.org/abs/2411.00136) *— 2024 · arXiv:2411.00136*
91. [LLM-as-a-Coauthor: Can Mixed Human-Written and Machine-Generated Text Be Detected?](https://aclanthology.org/2024.findings-naacl.29/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
92. [Label-Efficient Model Selection for Text Generation](https://aclanthology.org/2024.acl-long.456/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
93. [Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models](https://aclanthology.org/2024.acl-long.180/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
94. [Large Language Models as Foundations for Next-Gen Dense Retrieval: A Comprehensive Empirical Assessment](https://aclanthology.org/2024.emnlp-main.80/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
95. [Linearizing Large Language Models](https://arxiv.org/abs/2405.06640) *— 2024 · arXiv:2405.06640*
96. [Long-Context Language Modeling with Parallel Context Encoding](https://aclanthology.org/2024.acl-long.142/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
97. [LongAlign: A Recipe for Long Context Alignment of Large Language Models](https://arxiv.org/abs/2401.18058) *— 2024 · arXiv:2401.18058*
98. [LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks](https://arxiv.org/abs/2412.15204) *— 2024 · arXiv:2412.15204*
99. [LongEmbed: Extending Embedding Models for Long Context Retrieval](https://aclanthology.org/2024.emnlp-main.47/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
100. [LumberChunker: Long-Form Narrative Document Segmentation](https://aclanthology.org/2024.findings-emnlp.377/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*

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