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Who cites «Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences»

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

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  1. A Survey on Evaluation of LLM-based Agents — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  2. Charting the European LLM Benchmarking Landscape: A New Taxonomy and Registry — 2026 · Proceedings of Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities (LLMs4SSH) @ LREC 2026
  3. Decompose-and-Refine: Structured Legal Question Answering with Parametric Retrieval — 2026 · arXiv:2605.24454
  4. High-Throughput and Memory-Efficient Zeroth-Order Fine-tuning LLMs with Distributed Parallel Computing — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  5. Serbian SuperGLUE: Towards an Evaluation Benchmark for South Slavic Language Models — 2026 · Proceedings of the Second Workshop on Language Models for Low-Resource Languages (LoResLM 2026)
  6. Ultra-Low-Dimensional Prompt Tuning via Random Projection — 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  7. Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  8. ltzGLUE: Luxembourgish General Language Understanding Evaluation — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  9. BiLD: Bi-directional Logits Difference Loss for Large Language Model Distillation — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
  10. CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation Backdoor — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  11. CausalEval: Towards Better Causal Reasoning in 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)
  12. Efficient and Effective Prompt Tuning via Prompt Decomposition and Compressed Outer Product — 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)
  13. EverTracer: Hunting Stolen Large Language Models via Stealthy and Robust Probabilistic Fingerprint — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  14. FPEdit: Robust LLM Fingerprinting through Localized Parameter Editing — 2025 · arXiv:2508.02092
  15. Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning — 2025 · arXiv:2502.03304
  16. Investigating Critical Period Effects in Language Acquisition through Neural Language Models — 2025 · Transactions of the Association for Computational Linguistics
  17. MEraser: An Effective Fingerprint Erasure Approach for Large Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  18. Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets — 2025 · Computational Linguistics
  19. Once Upon a Time: Interactive Learning for Storytelling with Small Language Models — 2025 · Proceedings of the First BabyLM Workshop
  20. Piecing It All Together: Verifying Multi-Hop Multimodal Claims — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
  21. RecombiText: Compositional Data Augmentation for Enhancing LLM Pre-Training Datasets in Low-Resource Scenarios — 2025 · Proceedings of the First BabyLM Workshop
  22. Self-Adjust Softmax — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  23. Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translation — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  24. Single layer tiny Co4 outpaces GPT-2 and GPT-BERT — 2025 · Proceedings of the First BabyLM Workshop
  25. ZO2: Scalable Zeroth-Order Fine-Tuning for Extremely Large Language Models with Limited GPU Memory — 2025 · arXiv:2503.12668
  26. A Multi-Task Embedder For Retrieval Augmented LLMs — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  27. ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  28. Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models — 2024 · arXiv:2410.06441
  29. Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model — 2024 · arXiv:2402.07827
  30. Calibration-Tuning: Teaching Large Language Models to Know What They Don''t Know — 2024 · Proceedings of the 1st Workshop on Uncertainty-Aware NLP (UncertaiNLP 2024)
  31. Continual Learning of Large Language Models: A Comprehensive Survey — 2024 · arXiv:2404.16789
  32. Contrastive Instruction Tuning — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  33. Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  34. Full Parameter Fine-tuning for Large Language Models with Limited Resources — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  35. GPT or BERT: why not both? — 2024 · The 2nd BabyLM Challenge at the 28th Conference on Computational Natural Language Learning
  36. In-context Learning with Retrieved Demonstrations for Language Models: A Survey — 2024 · arXiv:2401.11624
  37. Instruction Pre-Training: Language Models are Supervised Multitask Learners — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  38. Instructional Fingerprinting of 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)
  39. Large Language Models Must Be Taught to Know What They Don't Know — 2024 · arXiv:2406.08391
  40. Large Language Models: A Survey — 2024 · arXiv:2402.06196
  41. Learning to Compress Prompt in Natural Language Formats — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  42. Learning to Retrieve In-Context Examples for Large Language Models — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  43. Light-PEFT: Lightening Parameter-Efficient Fine-Tuning via Early Pruning — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  44. 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)
  45. Multi-Task Inference: Can Large Language Models Follow Multiple Instructions at Once? — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  46. Multi-Task Learning with Adapters for Plausibility Prediction: Bridging the Gap or Falling into the Trenches? — 2024 · Proceedings of the Fifth Workshop on Insights from Negative Results in NLP
  47. MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries — 2024 · arXiv:2401.15391
  48. On Evaluating Explanation Utility for Human-AI Decision Making in NLP — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  49. PEMT: Multi-Task Correlation Guided Mixture-of-Experts Enables Parameter-Efficient Transfer Learning — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  50. PORTULAN ExtraGLUE Datasets and Models: Kick-starting a Benchmark for the Neural Processing of Portuguese — 2024 · Proceedings of the 17th Workshop on Building and Using Comparable Corpora (BUCC) @ LREC-COLING 2024
  51. Paraphrasing in Affirmative Terms Improves Negation Understanding — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
  52. Plausible Extractive Rationalization through Semi-Supervised Entailment Signal — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  53. Synthetic Multimodal Question Generation — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  54. Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  55. Whispers of Doubt Amidst Echoes of Triumph in NLP Robustness — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  56. tasksource: A Large Collection of NLP tasks with a Structured Dataset Preprocessing Framework — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  57. Étude des facteurs de complexité des modèles de langage dans une tâche de compréhension de lecture à l'aide d'une expérience contrôlée sémantiquement — 2024 · Actes de la 31ème Conférence sur le Traitement Automatique des Langues Naturelles, volume 1 : articles longs et prises de position
  58. A Comprehensive Overview of Large Language Models — 2023 · arXiv:2307.06435
  59. A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  60. ACES: Translation Accuracy Challenge Sets at WMT 2023 — 2023 · Proceedings of the Eighth Conference on Machine Translation
  61. AD-KD: Attribution-Driven Knowledge Distillation for Language Model Compression — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  62. APrompt: Attention Prompt Tuning for Efficient Adaptation of Pre-trained Language Models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  63. ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems — 2023 · arXiv:2311.09476
  64. Adapting Language Models to Compress Contexts — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  65. Adapting Large Language Models to Domains via Reading Comprehension — 2023 · arXiv:2309.09530
  66. Baby''s CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
  67. Benchmarks for Automated Commonsense Reasoning: A Survey — 2023 · arXiv:2302.04752
  68. BloombergGPT: A Large Language Model for Finance — 2023 · arXiv:2303.17564
  69. ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  70. DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI — 2023 · arXiv:2307.10172
  71. Don''t Blame the Annotator: Bias Already Starts in the Annotation Instructions — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  72. Efficiently Adapting Pretrained Language Models To New Languages — 2023 · arXiv:2311.05741
  73. Emergent Modularity in Pre-trained Transformers — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  74. Evaluating Large Language Models: A Comprehensive Survey — 2023 · arXiv:2310.19736
  75. Few-shot Adaptation Works with UnpredicTable Data — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  76. FiD-ICL: A Fusion-in-Decoder Approach for Efficient In-Context Learning — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  77. Fine-Tuning Language Models with Just Forward Passes — 2023 · arXiv:2305.17333
  78. GlobalBench: A Benchmark for Global Progress in Natural Language Processing — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  79. Hop, Union, Generate: Explainable Multi-hop Reasoning without Rationale Supervision — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  80. Incorporating Attribution Importance for Improving Faithfulness Metrics — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  81. Knowledge is a Region in Weight Space for Fine-tuned Language Models — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  82. KoRC: Knowledge Oriented Reading Comprehension Benchmark for Deep Text Understanding — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  83. LAIT: Efficient Multi-Segment Encoding in Transformers with Layer-Adjustable Interaction — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  84. Learning to Initialize: Can Meta Learning Improve Cross-task Generalization in Prompt Tuning? — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  85. Long-Tailed Question Answering in an Open World — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  86. Mean BERTs make erratic language teachers: the effectiveness of latent bootstrapping in low-resource settings — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
  87. Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  88. Not all layers are equally as important: Every Layer Counts BERT — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
  89. PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  90. Parameter Efficient Multi-task Fine-tuning by Learning to Transfer Token-wise Prompts — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  91. Parameter-efficient Tuning for Large Language Model without Calculating Its Gradients — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  92. Prompting with Pseudo-Code Instructions — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  93. QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  94. RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Question — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  95. Residual Prompt Tuning: improving prompt tuning with residual reparameterization — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  96. Revisiting Token Dropping Strategy in Efficient BERT Pretraining — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  97. Symbolic Discovery of Optimization Algorithms — 2023 · arXiv:2302.06675
  98. 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
  99. TimelineQA: A Benchmark for Question Answering over Timelines — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  100. Trained on 100 million words and still in shape: BERT meets British National Corpus — 2023 · Findings of the Association for Computational Linguistics: EACL 2023

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