---
title: "Who cites Exploring the Limits of Transfer Learning with a…"
description: "7,433 papers of the Elamur Research library cite «Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer», found in their…"
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---
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# Who cites «Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer»

7,433 papers of our library cite it (of the 140,884 whose bibliographies we read) · 592 with a page here, the most cited first · page 5 of 6 · 401–500 · [← the paper](https://md.research.elamur.ai/free/en/papers/raffel-2019-exploring-limits-transfer-learning-unified/)

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401. [**Graph Pre-training for AMR Parsing and Generation**Xuefeng Bai, Yulong Chen, Yue Zhang*2022 · 153 citations*](https://md.research.elamur.ai/free/en/papers/bai-2022-graph-pre-training-amr-parsing/)
402. [**AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators**Xingwei He, Zhenghao Lin, Yeyun Gong, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-annollm-making-large-language-models/)
403. [**ProsocialDialog: A Prosocial Backbone for Conversational Agents**Hyunwoo Kim, Youngjae Yu, Liwei Jiang, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/kim-2022-prosocialdialog-prosocial-backbone-conversational-agents/)
404. [**Investigating Pretrained Language Models for Graph-to-Text Generation**Leonardo F. R. Ribeiro, Martin Schmitt, Hinrich Schütze, et al.*2021 · 149 citations*](https://md.research.elamur.ai/free/en/papers/ribeiro-2021-investigating-pretrained-language-models-graph/)
405. [**Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding**Jun Zhang, Jue Wang, Huan Li, et al.*2024 · 146 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-draft-verify-lossless-large-language/)
406. [**SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and Arabic**Ibrahim Abu Farha, Silviu Vlad Oprea, Steven Wilson, et al.*2022 · 146 citations*](https://md.research.elamur.ai/free/en/papers/farha-2022-semeval-2022-task-6-isarcasmeval/)
407. [**Fact-Checking Complex Claims with Program-Guided Reasoning**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/)
408. [**RA-DIT: Retrieval-Augmented Dual Instruction Tuning**Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-ra-dit-retrieval-augmented-dual/)
409. [**SCOTT: Self-Consistent Chain-of-Thought Distillation**Peifeng Wang, Zhengyang Wang, Zheng Li, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-scott-self-consistent-chain-thought/)
410. [**The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset**Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-bigscience-roots-corpus-1-6tb/)
411. [**Is GPT-3 a Good Data Annotator?**Bosheng Ding, Chengwei Qin, Linlin Liu, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-gpt-3-good-data-annotator/)
412. [**GLUCOSE: GeneraLized and COntextualized Story Explanations**Nasrin Mostafazadeh, Aditya Kalyanpur, Lori Moon, et al.*2020 · 144 citations*](https://md.research.elamur.ai/free/en/papers/mostafazadeh-2020-glucose-generalized-contextualized-story-explanations/)
413. [**AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages**Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele, et al.*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/muhammad-2023-afrisenti-twitter-sentiment-analysis-benchmark/)
414. [**TALM: Tool Augmented Language Models**Aaron Parisi, Yao Zhao, Noah Fiedel*2022 · 142 citations*](https://md.research.elamur.ai/free/en/papers/parisi-2022-talm-tool-augmented-language-models/)
415. [**Rethinking embedding coupling in pre-trained language models**Hyung Won Chung, Thibault Févry, Henry Tsai, et al.*2020 · 142 citations*](https://md.research.elamur.ai/free/en/papers/chung-2020-rethinking-embedding-coupling-pre-trained/)
416. [**JudgeLM: Fine-tuned Large Language Models are Scalable Judges**Lianghui Zhu, Xinggang Wang, Xinlong Wang*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-judgelm-fine-tuned-large-language/)
417. [**Diverse Demonstrations Improve In-context Compositional Generalization**Itay Levy, Ben Bogin, Jonathan Berant*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/levy-2023-diverse-demonstrations-improve-context-compositional/)
418. [**Exploring Length Generalization in Large Language Models**Cem Anil, Yuhuai Wu, Anders Andreassen, et al.*2022 · 138 citations*](https://md.research.elamur.ai/free/en/papers/anil-2022-exploring-length-generalization-large-language/)
419. [**Investigating Data Contamination in Modern Benchmarks for Large Language Models**Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/deng-2024-investigating-data-contamination-modern-benchmarks/)
420. [**Efficient Training of Language Models to Fill in the Middle**Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.*2022 · 137 citations*](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/)
421. [**A fine-grained comparison of pragmatic language understanding in humans and language models**Jennifer Hu, Sammy Floyd, Olessia Jouravlev, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-fine-grained-comparison-pragmatic-language/)
422. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/)
423. [**Byte Pair Encoding is Suboptimal for Language Model Pretraining**Kaj Bostrom, Greg Durrett*2020 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bostrom-2020-byte-pair-encoding-is-suboptimal/)
424. [**SLiC-HF: Sequence Likelihood Calibration with Human Feedback**Yao Zhao, Rishabh Joshi, Tianqi Liu, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-slic-hf-sequence-likelihood-calibration/)
425. [**Simple and Effective Masked Diffusion Language Models**Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/sahoo-2024-simple-effective-masked-diffusion-language/)
426. [**Few-Shot Self-Rationalization with Natural Language Prompts**Ana Marasovic, Iz Beltagy, Doug Downey, et al.*2022 · 134 citations*](https://md.research.elamur.ai/free/en/papers/marasovic-2022-few-shot-self-rationalization-natural/)
427. [**FLUTE: Figurative Language Understanding through Textual Explanations**Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.*2022 · 131 citations*](https://md.research.elamur.ai/free/en/papers/chakrabarty-2022-flute-figurative-language-understanding-through/)
428. [**FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation**Tu Vu, Mohit Iyyer, Xuezhi Wang, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/vu-2023-freshllms-refreshing-large-language-models/)
429. [**MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems**Jakub Macina, Nico Daheim, Sankalan Chowdhury, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/macina-2023-mathdial-dialogue-tutoring-dataset-rich/)
430. [**Learning Compact Metrics for MT**Amy Pu, Hyung Won Chung, Ankur Parikh, et al.*2021 · 130 citations*](https://md.research.elamur.ai/free/en/papers/pu-2021-learning-compact-metrics-mt/)
431. [**Analyzing Transformers in Embedding Space**Guy Dar, Mor Geva, Ankit Gupta, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/dar-2023-analyzing-transformers-embedding-space/)
432. [**Sequence Parallelism: Long Sequence Training from System Perspective**Shenggui Li, Fuzhao Xue, Chaitanya Baranwal, et al.*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-sequence-parallelism-long-sequence-training/)
433. [**ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding**Uri Shaham, Maor Ivgi, Avia Efrat, et al.*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/shaham-2023-zeroscrolls-zero-shot-benchmark-long/)
434. [**Fanar: An Arabic-Centric Multimodal Generative AI Platform**Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.*2025 · 127 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2025-fanar-arabic-centric-multimodal-generative/)
435. [**Understanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error Detectors**Liyan Tang, Tanya Goyal, Alex Fabbri, et al.*2023 · 126 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-understanding-factual-errors-summarization-errors/)
436. [**InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory**Chaojun Xiao, Pengle Zhang, Xu Han, et al.*2024 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2024-infllm-training-free-long-context/)
437. [**OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text**Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/paster-2023-openwebmath-open-dataset-high-quality/)
438. [**Nomic Embed: Training a Reproducible Long Context Text Embedder**Zach Nussbaum, John X. Morris, Brandon Duderstadt, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/nussbaum-2024-nomic-embed-training-reproducible-long/)
439. [**Large Language Model Alignment: A Survey**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
440. [**LEVER: Learning to Verify Language-to-Code Generation with Execution**Ansong Ni, Srini Iyer, Dragomir Radev, et al.*2023 · 122 citations*](https://md.research.elamur.ai/free/en/papers/ni-2023-lever-learning-verify-language-code/)
441. [**Transformer-Patcher: One Mistake worth One Neuron**Zeyu Huang, Yikang Shen, Xiaofeng Zhang, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-transformer-patcher-one-mistake-worth/)
442. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/)
443. [**Findings of the AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas**Manuel Mager, Arturo Oncevay, Abteen Ebrahimi, et al.*2021 · 118 citations*](https://md.research.elamur.ai/free/en/papers/mager-2021-findings-americasnlp-2021-shared-task/)
444. [**I-BERT: Integer-only BERT Quantization**Sehoon Kim, Amir Gholami, Zhewei Yao, et al.*2021 · 118 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-i-bert-integer-only-bert/)
445. [**MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases**Louis Martin, Angela Fan, Éric de la Clergerie, et al.*2022 · 117 citations*](https://md.research.elamur.ai/free/en/papers/martin-2022-muss-multilingual-unsupervised-sentence-simplification/)
446. [**GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction**Oscar Sainz, Iker Garcia-Ferrero, Rodrigo Agerri, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/sainz-2023-gollie-annotation-guidelines-improve-zero/)
447. [**RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation**Fangyuan Xu, Weijia Shi, Eunsol Choi*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-recomp-improving-retrieval-augmented-lms/)
448. [**ALLaM: Large Language Models for Arabic and English**M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/bari-2024-allam-large-language-models-arabic/)
449. [**Quiet-STaR: Language models can teach themselves to think before speaking***2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/al-2024-quiet-star-language-models-teach/)
450. [**DistiLLM: Towards Streamlined Distillation for Large Language Models**Jongwoo Ko, Sungnyun Kim, Tianyi Chen, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/ko-2024-distillm-towards-streamlined-distillation-large/)
451. [**Language ID in the Wild: Unexpected Challenges on the Path to a Thousand-Language Web Text Corpus**Isaac Caswell, Theresa Breiner, Daan van Esch, et al.*2020 · 111 citations*](https://md.research.elamur.ai/free/en/papers/caswell-2020-language-id-wild-unexpected/)
452. [**Data Engineering for Scaling Language Models to 128K Context**Yao Fu, Rameswar Panda, Xinyao Niu, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-data-engineering-scaling-language-models/)
453. [**LENS: A Learnable Evaluation Metric for Text Simplification**Mounica Maddela, Yao Dou, David Heineman, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/maddela-2023-lens-learnable-evaluation-metric-text/)
454. [**Nemotron-4 340B Technical Report**Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.*2024 · 102 citations*](https://md.research.elamur.ai/free/en/papers/adler-2024-nemotron-4-340b-technical-report/)
455. [**Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words**Valentin, Hofmann*2021 · 101 citations*](https://md.research.elamur.ai/free/en/papers/hofmann-2021-superbizarre-derivational/)
456. [**SemDeDup: Data-efficient learning at web-scale through semantic deduplication**Amro Abbas, Kushal Tirumala, Dániel Simig, et al.*2023 · 94 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2023-semdedup-data-efficient-learning-web/)
457. [**InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 92 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-mastering-free/)
458. [**AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Models**Harish Tayyar Madabushi, Edward Gow-Smith, Carolina Scarton, et al.*2021 · 86 citations*](https://md.research.elamur.ai/free/en/papers/madabushi-2021-astitchinlanguagemodels-dataset-methods-exploration-idiomaticity/)
459. [**NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation**Kaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.*2023 · 84 citations*](https://md.research.elamur.ai/free/en/papers/dhole-2023-nl-augmenter-framework-task-sensitive/)
460. [**D4: Improving LLM Pretraining via Document De-Duplication and Diversification**Kushal Tirumala, Daniel Simig, Armen Aghajanyan, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/tirumala-2023-d4-improving-llm-pretraining-document/)
461. [**Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/tay-2023-scaling-laws-vs-model-architectures/)
462. [**Coreference Resolution through a seq2seq Transition-Based System**Bernd Bohnet, Chris Alberti, Michael Collins*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2023-coreference-resolution-through-seq2seq-transition/)
463. [**SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented Parser**Yue Zhang, Bo Zhang, Zhenghua Li, et al.*2022 · 76 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2022-syngec-syntax-enhanced-grammatical-error/)
464. [**PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities**Settaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/sravanthi-2024-pub-pragmatics-understanding-benchmark-assessing/)
465. [**POLITICS: Pretraining with Same-story Article Comparison for Ideology Prediction and Stance Detection**Yujian Liu, Xinliang Frederick Zhang, David Wegsman, et al.*2022 · 70 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-politics-pretraining-same-story-article/)
466. [**CREPE: Open-Domain Question Answering with False Presuppositions**Xinyan Yu, Sewon Min, Luke Zettlemoyer, et al.*2023 · 67 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-crepe-open-domain-question-answering/)
467. [**Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks**Akari Asai, Matt Gardner, Hannaneh Hajishirzi*2022 · 60 citations*](https://md.research.elamur.ai/free/en/papers/asai-2022-evidentiality-guided-generation-knowledge-intensive/)
468. [**AlephBERT: Language Model Pre-training and Evaluation from Sub-Word to Sentence Level**Amit Seker, Elron Bandel, Dan Bareket, et al.*2022 · 57 citations*](https://md.research.elamur.ai/free/en/papers/seker-2022-alephbert-language-model-pre-training/)
469. [**Learning to Evaluate Translation Beyond English: BLEURT Submissions to the WMT Metrics 2020 Shared Task**Thibault Sellam, Amy Pu, Hyung Won Chung, et al.*2020 · 55 citations*](https://md.research.elamur.ai/free/en/papers/sellam-2020-learning-evaluate-translation-beyond-english/)
470. [**TellMeWhy: A Dataset for Answering Why-Questions in Narratives**Yash Kumar Lal, Nathanael Chambers, Raymond Mooney, et al.*2021 · 53 citations*](https://md.research.elamur.ai/free/en/papers/lal-2021-tellmewhy-dataset-answering-why-questions/)
471. [**XCodeEval: An Execution-based Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/khan-2024-xcodeeval-execution-based-large-scale/)
472. [**Weisfeiler-Leman in the Bamboo: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity**Juri Opitz, Angel Daza, Anette Frank*2021 · 47 citations*](https://md.research.elamur.ai/free/en/papers/opitz-2021-weisfeiler-leman-bamboo-novel-amr/)
473. [**Bridging the Preference Gap between Retrievers and LLMs**Zixuan Ke, Weize Kong, Cheng Li, et al.*2024 · 45 citations*](https://md.research.elamur.ai/free/en/papers/ke-2024-bridging-preference-gap-between-retrievers/)
474. [**DiscoPrompt: Path Prediction Prompt Tuning for Implicit Discourse Relation Recognition**Chunkit Chan, Xin Liu, Jiayang Cheng, et al.*2023 · 45 citations*](https://md.research.elamur.ai/free/en/papers/chan-2023-discoprompt-path-prediction-prompt-tuning/)
475. [**Interpretable Word Sense Representations via Definition Generation: The Case of Semantic Change Analysis**Mario Giulianelli, Iris Luden, Raquel Fernandez, et al.*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/giulianelli-2023-definition-generation-senses/)
476. [**Transcending Scaling Laws with 0.1% Extra Compute**Yi Tay, Jason Wei, Hyung Won Chung, et al.*2022 · 40 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-transcending-scaling-laws-0-1/)
477. [**xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/khan-2023-xcodeeval-large-scale-multilingual-multitask/)
478. [**A Multimodal Corpus for Emotion Recognition in Sarcasm**Anupama Ray, Shubham Mishra, Apoorva Nunna, et al.*2022 · 35 citations*](https://md.research.elamur.ai/free/en/papers/ray-2022-multimodal-corpus-emotion-recognition-sarcasm/)
479. [**Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing**Jaehun Jung, Peter West, Liwei Jiang, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/jung-2023-impossible-distillation-low-quality-model/)
480. [**Seq2seq is All You Need for Coreference Resolution**Wenzheng Zhang, Sam Wiseman, Karl Stratos*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-seq2seq-is-all-you-need/)
481. [**RST Discourse Parsing with Second-Stage EDU-Level Pre-training**Nan Yu, Meishan Zhang, Guohong Fu, et al.*2022 · 32 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-rst-discourse-parsing-second-stage/)
482. [**Chinese Idiom Paraphrasing**Jipeng Qiang, Yang Li, Chaowei Zhang, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/qiang-2023-chinese-idiom-paraphrasing/)
483. [**Probing Contextual Language Models for Common Ground with Visual Representations**Gabriel Ilharco, Rowan Zellers, Ali Farhadi, et al.*2021 · 31 citations*](https://md.research.elamur.ai/free/en/papers/ilharco-2021-probing-contextual-language-models-common/)
484. [**Not Just Classification: Recognizing Implicit Discourse Relation on Joint Modeling of Classification and Generation**Feng Jiang, Yaxin Fan, Xiaomin Chu, et al.*2021 · 30 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2021-not-just-classification-recognizing-implicit/)
485. [**Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All**Eylon Gueta, Avi Shmidman, Shaltiel Shmidman, et al.*2022 · 28 citations*](https://md.research.elamur.ai/free/en/papers/gueta-2022-large-pre-trained-models-extra/)
486. [**Exploring the Relationship between LLM Hallucinations and Prompt Linguistic Nuances: Readability, Formality, and Concreteness**Vipula Rawte, Prachi Priya, S.M Towhidul Islam Tonmoy, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/rawte-2023-exploring-relationship-between-llm-hallucinations/)
487. [**IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions**Wenhao Yu, Meng Jiang, Peter Clark, et al.*2023 · 26 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-ifqa-dataset-open-domain-question/)
488. [**Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations**Alexander Hägele, Elie Bakouch, Atli Kosson, et al.*2024 · 24 citations*](https://md.research.elamur.ai/free/en/papers/hagele-2024-scaling-laws-compute-optimal-training/)
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