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Who cites «Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences» · page 2

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

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  1. 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
  2. ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems — 2023 · arXiv:2311.09476
  3. Adapting Language Models to Compress Contexts — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  4. Adapting Large Language Models to Domains via Reading Comprehension — 2023 · arXiv:2309.09530
  5. 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
  6. Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  7. Benchmarks for Automated Commonsense Reasoning: A Survey — 2023 · arXiv:2302.04752
  8. BloombergGPT: A Large Language Model for Finance — 2023 · arXiv:2303.17564
  9. Catwalk: A Unified Language Model Evaluation Framework for Many Datasets — 2023 · arXiv:2312.10253
  10. 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)
  11. DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI — 2023 · arXiv:2307.10172
  12. 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
  13. Efficiently Adapting Pretrained Language Models To New Languages — 2023 · arXiv:2311.05741
  14. Emergent Modularity in Pre-trained Transformers — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  15. Entity Tracking via Effective Use of Multi-Task Learning Model and Mention-guided Decoding — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  16. Evaluating Large Language Models: A Comprehensive Survey — 2023 · arXiv:2310.19736
  17. Few-shot Adaptation Works with UnpredicTable Data — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  18. 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)
  19. Fine-Tuning Language Models with Just Forward Passes — 2023 · arXiv:2305.17333
  20. GlobalBench: A Benchmark for Global Progress in Natural Language Processing — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  21. Hop, Union, Generate: Explainable Multi-hop Reasoning without Rationale Supervision — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  22. Incorporating Attribution Importance for Improving Faithfulness Metrics — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  23. Knowledge is a Region in Weight Space for Fine-tuned Language Models — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  24. KoRC: Knowledge Oriented Reading Comprehension Benchmark for Deep Text Understanding — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  25. 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)
  26. Learning Easily Updated General Purpose Text Representations with Adaptable Task-Specific Prefix — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  27. Learning to Ignore Adversarial Attacks — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  28. 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)
  29. Learning to Predict Task Transferability via Soft Prompt — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  30. 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)
  31. Make Your Decision Convincing! A Unified Two-Stage Framework: Self-Attribution and Decision-Making — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  32. 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
  33. 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)
  34. 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
  35. 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
  36. Parameter Efficient Multi-task Fine-tuning by Learning to Transfer Token-wise Prompts — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  37. Parameter-efficient Tuning for Large Language Model without Calculating Its Gradients — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  38. Prompting with Pseudo-Code Instructions — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  39. 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)
  40. RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Question — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  41. Residual Prompt Tuning: improving prompt tuning with residual reparameterization — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  42. 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)
  43. SharPT: Shared Latent Space Prompt Tuning — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
  44. Symbolic Discovery of Optimization Algorithms — 2023 · arXiv:2302.06675
  45. 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
  46. TimelineQA: A Benchmark for Question Answering over Timelines — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  47. Trained on 100 million words and still in shape: BERT meets British National Corpus — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
  48. Two Examples are Better than One: Context Regularization for Gradient-based Prompt Tuning — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  49. UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  50. UltraFeedback: Boosting Language Models with Scaled AI Feedback — 2023 · arXiv:2310.01377
  51. Understanding the Role of Input Token Characters in Language Models: How Does Information Loss Affect Performance? — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  52. Unsupervised Selective Rationalization with Noise Injection — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  53. Vote''n''Rank: Revision of Benchmarking with Social Choice Theory — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  54. Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision — 2023 · arXiv:2312.09390
  55. 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)
  56. When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! Principle — our card · 2023 · Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP
  57. Where to start? Analyzing the potential value of intermediate models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  58. kNN-CM: A Non-parametric Inference-Phase Adaptation of Parametric Text Classifiers — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  59. ACES: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics — our card · 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)
  60. ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  61. AdapLeR: Speeding up Inference by Adaptive Length Reduction — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  62. An Investigation of the (In)effectiveness of Counterfactually Augmented Data — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  63. Analyzing Multi-Task Learning for Abstractive Text Summarization — 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
  64. Ask Me Anything: A simple strategy for prompting language models — 2022 · arXiv:2210.02441
  65. Automatic Label Sequence Generation for Prompting Sequence-to-sequence Models — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  66. 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
  67. Can Edge Probing Tests Reveal Linguistic Knowledge in QA Models? — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  68. Can Rationalization Improve Robustness? — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  69. Coarse-to-Fine: Hierarchical Multi-task Learning for Natural Language Understanding — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  70. Cross-Task Generalization via Natural Language Crowdsourcing Instructions — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  71. Design Challenges for a Multi-Perspective Search Engine — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  72. Double Trouble: How to not Explain a Text Classifier''s Decisions Using Counterfactuals Synthesized by Masked Language Models? — 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
  73. Down and Across: Introducing Crossword-Solving as a New NLP Benchmark — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  74. Eliciting and Understanding Cross-task Skills with Task-level Mixture-of-Experts — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  75. FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  76. FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  77. Hey AI, Can You Solve Complex Tasks by Talking to Agents? — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  78. Human-Centered Evaluation of Explanations — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorial Abstracts
  79. Improving In-Context Few-Shot Learning via Self-Supervised Training — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  80. Is a Question Decomposition Unit All We Need? — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  81. Learning to Perform Complex Tasks through Compositional Fine-Tuning of Language Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  82. Lite Unified Modeling for Discriminative Reading Comprehension — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  83. Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  84. On the Diversity and Limits of Human Explanations — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  85. Reframing Instructional Prompts to GPTk's Language — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  86. 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)
  87. Towards a Unified Multi-Dimensional Evaluator for Text Generation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  88. Transferring Confluent Knowledge to Argument Mining — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  89. UKP-SQUARE: An Online Platform for Question Answering Research — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
  90. UNIREX: A Unified Learning Framework for Language Model Rationale Extraction — 2022 · Proceedings of BigScience Episode \#5 – Workshop on Challenges & Perspectives in Creating Large Language Models
  91. Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  92. What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization? — 2022 · arXiv:2204.05832
  93. What Language Model to Train if You Have One Million GPU Hours? — 2022 · arXiv:2210.15424
  94. What Makes Reading Comprehension Questions Difficult? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  95. What to Learn, and How: Toward Effective Learning from Rationales — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  96. Word Order Does Matter and Shuffled Language Models Know It — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  97. XPrompt: Exploring the Extreme of Prompt Tuning — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  98. 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
  99. An Investigation of Language Model Interpretability via Sentence Editing — 2021 · Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
  100. Benchmarking Machine Reading Comprehension: A Psychological Perspective — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

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