---
title: "Who cites Yanqi Zhou — page 6"
description: "8,127 papers of the Elamur Research library cite the works of Yanqi Zhou, found in their bibliographies · page 6 of 7 · 501–600; the most cited first."
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---
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# Who cites Yanqi Zhou

8,538 citations of their works from 8,127 papers of our library (of the 140,884 whose bibliographies we read) · 669 with a page here, the most cited first · page 6 of 7 · 501–600 · [← Yanqi Zhou](https://md.research.elamur.ai/free/en/authors/yanqi-zhou/)

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501. [**The case for 4-bit precision: k-bit Inference Scaling Laws**Tim Dettmers, Luke Zettlemoyer*2022 · 119 citations*](https://md.research.elamur.ai/free/en/papers/dettmers-2022-case-4-bit-precision-k/)
502. [**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/)
503. [**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/)
504. [**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/)
505. [**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/)
506. [**Scaling Laws for Autoregressive Generative Modeling**Tom Henighan, Jared Kaplan, Mor Katz, et al.*2020 · 115 citations*](https://md.research.elamur.ai/free/en/papers/henighan-2020-scaling-laws-autoregressive-generative-modeling/)
507. [**From Persona to Personalization: A Survey on Role-Playing Language Agents**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
508. [**Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models**Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-inference-scaling-laws-empirical-analysis/)
509. [**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/)
510. [**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/)
511. [**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/)
512. [**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/)
513. [**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/)
514. [**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/)
515. [**ExpertQA: Expert-Curated Questions and Attributed Answers**Chaitanya Malaviya, Subin Lee, Sihao Chen, et al.*2024 · 109 citations*](https://md.research.elamur.ai/free/en/papers/malaviya-2024-expertqa-expert-curated-questions-attributed/)
516. [**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/)
517. [**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/)
518. [**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/)
519. [**Scaling Laws for Transfer**Danny Hernandez, Jared Kaplan, Tom Henighan, et al.*2021 · 102 citations*](https://md.research.elamur.ai/free/en/papers/hernandez-2021-scaling-laws-transfer/)
520. [**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/)
521. [**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/)
522. [**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/)
523. [**The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs**Laura Ruis, Akbir Khan, Stella Biderman, et al.*2022 · 86 citations*](https://md.research.elamur.ai/free/en/papers/ruis-2022-goldilocks-pragmatic-understanding-fine-tuning/)
524. [**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/)
525. [**Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/)
526. [**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/)
527. [**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/)
528. [**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/)
529. [**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/)
530. [**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/)
531. [**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/)
532. [**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/)
533. [**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/)
534. [**Scaling Laws and Interpretability of Learning from Repeated Data**Danny Hernandez, Tom Brown, Tom Conerly, et al.*2022 · 62 citations*](https://md.research.elamur.ai/free/en/papers/hernandez-2022-scaling-laws-interpretability-learning-repeated/)
535. [**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/)
536. [**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/)
537. [**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/)
538. [**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/)
539. [**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/)
540. [**Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws**Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.*2024 · 47 citations*](https://md.research.elamur.ai/free/en/papers/sardana-2024-chinchilla-optimal-accounting-inference-language/)
541. [**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/)
542. [**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/)
543. [**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/)
544. [**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/)
545. [**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/)
546. [**Scaling Laws for Generative Mixed-Modal Language Models**Armen Aghajanyan, Lili Yu, Alexis Conneau, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/aghajanyan-2023-scaling-laws-generative-mixed-modal/)
547. [**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/)
548. [**Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data**Mubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.*2023 · 38 citations*](https://md.research.elamur.ai/free/en/papers/akhtar-2023-exploring-numerical-reasoning-capabilities-language/)
549. [**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/)
550. [**Reflect, Not Reflex: Inference-Based Common Ground Improves Dialogue Response Quality**Pei Zhou, Hyundong Cho, Pegah Jandaghi, et al.*2022 · 34 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2022-reflect-not-reflex-inference-based/)
551. [**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/)
552. [**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/)
553. [**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/)
554. [**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/)
555. [**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/)
556. [**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/)
557. [**Observational Scaling Laws and the Predictability of Language Model Performance**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
558. [**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/)
559. [**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/)
560. [**The Quantization Model of Neural Scaling**Eric J. Michaud, Ziming Liu, Uzay Girit, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/michaud-2023-quantization-model-neural-scaling/)
561. [**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/)
562. [**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/)
563. [**An Expanded Massive Multilingual Dataset for High-Performance Language Technologies (HPLT)**Laurie Burchell, Ona de Gibert, Nikolay Arefyev, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/burchell-2025-expanded-massive-multilingual-dataset-high/)
564. [**Distillation Scaling Laws**Dan Busbridge, Amitis Shidani, Floris Weers, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/busbridge-2025-distillation-scaling-laws/)
565. [**Modeling Cross-Cultural Pragmatic Inference with Codenames Duet**Omar Shaikh, Caleb Ziems, William Held, et al.*2023 · 23 citations*](https://md.research.elamur.ai/free/en/papers/shaikh-2023-modeling-cross-cultural-pragmatic-inference/)
566. [**CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models**Zixin Chen, Hongzhan Lin, Ziyang Luo, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-cofipara-coarse-fine-paradigm-multimodal/)
567. [**Semantics of Multiword Expressions in Transformer-Based Models: A Survey**Filip Miletić, Sabine Schulte im Walde*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/miletic-2024-semantics-multiword-expressions-transformer-based/)
568. [**Few-Shot Anaphora Resolution in Scientific Protocols via Mixtures of In-Context Experts**Nghia T. Le, Fan Bai, Alan Ritter*2022 · 20 citations*](https://md.research.elamur.ai/free/en/papers/le-2022-few-shot-anaphora-resolution-scientific/)
569. [**Can we obtain significant success in RST discourse parsing by using Large Language Models?**Aru Maekawa, Tsutomu Hirao, Hidetaka Kamigaito, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/maekawa-2024-can-we-obtain-significant-success/)
570. [**Topic-Guided Sampling For Data-Efficient Multi-Domain Stance Detection**Erik Arakelyan, Arnav Arora, Isabelle Augenstein*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/arakelyan-2023-topic-guided-sampling-data-efficient/)
571. [**BLiMP: The Benchmark of Linguistic Minimal Pairs for English**Alex Warstadt, Alicia Parrish, Haokun Liu, et al.*2020 · 19 citations*](https://md.research.elamur.ai/free/en/papers/warstadt-2020-blimp-benchmark-linguistic-minimal-pairs/)
572. [**The Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm Generation**Tyler Loakman, Aaron Maladry, Chenghua Lin*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/loakman-2023-iron-ic-melting-pot-reviewing/)
573. [**MultiPragEval: Multilingual Pragmatic Evaluation of Large Language Models**Dojun Park, Jiwoo Lee, Seohyun Park, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/park-2024-multiprageval-multilingual-pragmatic-evaluation-large/)
574. [**Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys**Yong Cao, Min Chen, Daniel Hershcovich*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/cao-2024-bridging-cultural-nuances-dialogue-agents/)
575. [**Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better**Shengchao Liu, Xiaoming Liu, Yichen Wang, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-does-detectgpt-fully-utilize-perturbation/)
576. [**StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements**Jillian Fisher, Skyler Hallinan, Ximing Lu, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/fisher-2024-styleremix-interpretable-authorship-obfuscation-distillation/)
577. [**Cross-Document Event Coreference Resolution on Discourse Structure**Xinyu Chen, Sheng Xu, Peifeng Li, et al.*2023 · 16 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-cross-document-event-coreference-resolution/)
578. [**JABER and SABER: Junior and Senior Arabic BERt**Abbas Ghaddar, Yimeng Wu, Ahmad Rashid, et al.*2021 · 16 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2021-jaber-saber-junior-senior-arabic/)
579. [**Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary and Instruction Capabilities**Shaltiel Shmidman, Avi Shmidman, Amir DN Cohen, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2024-adapting-llms-hebrew-unveiling-dictalm/)
580. [**Evaluating Large Language Models for Health-related Queries with Presuppositions**Navreet Kaur, Monojit Choudhury, Danish Pruthi*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/kaur-2024-evaluating-large-language-models-health/)
581. [**When Truth Matters - Addressing Pragmatic Categories in Natural Language Inference (NLI) by Large Language Models (LLMs)**Reto Gubelmann, Aikaterini-lida Kalouli, Christina Niklaus, et al.*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/gubelmann-2023-when-truth-matters-addressing-pragmatic/)
582. [**Alignment at Pre-training! Towards Native Alignment for Arabic LLMs**Juhao Liang, Zhenyang Cai, Jianqing Zhu, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/liang-2024-alignment-pre-training-towards-native/)
583. [**Resolving Discrepancies in Compute-Optimal Scaling of Language Models**Tomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/porian-2024-resolving-discrepancies-compute-optimal-scaling/)
584. [**Introducing BEREL: BERT Embeddings for Rabbinic-Encoded Language**Avi Shmidman, Joshua Guedalia, Shaltiel Shmidman, et al.*2022 · 13 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2022-introducing-berel-bert-embeddings-rabbinic/)
585. [**A Multi-Task Dataset for Assessing Discourse Coherence in Chinese Essays: Structure, Theme, and Logic Analysis**Hongyi Wu, Xinshu Shen, Man Lan, et al.*2023 · 12 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-multi-task-dataset-assessing-discourse/)
586. [**Dialogue Discourse Parsing as Generation: A Sequence-to-Sequence LLM-based Approach**Chuyuan Li, Yuwei Yin, Giuseppe Carenini*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-dialogue-discourse-parsing-as-generation/)
587. [**Are Frequent Phrases Directly Retrieved like Idioms? An Investigation with Self-Paced Reading and Language Models**Giulia Rambelli, Emmanuele Chersoni, Marco S. G. Senaldi, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/rambelli-2023-are-frequent-phrases-directly-retrieved/)
588. [**IEKG: A Commonsense Knowledge Graph for Idiomatic Expressions**Ziheng Zeng, Kellen Tan Cheng, Srihari Venkat Nanniyur, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2023-iekg-commonsense-knowledge-graph-idiomatic/)
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