---
title: "Who cites Sharan Narang — page 8"
description: "11,493 papers of the Elamur Research library cite the works of Sharan Narang, found in their bibliographies · page 8 of 9 · 701–800; the most cited first."
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---
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# Who cites Sharan Narang

13,067 citations of their works from 11,493 papers of our library (of the 140,884 whose bibliographies we read) · 895 with a page here, the most cited first · page 8 of 9 · 701–800 · [← Sharan Narang](https://md.research.elamur.ai/free/en/authors/sharan-narang/)

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701. [**Arabic Speech Recognition by End-to-End, Modular Systems and Human**Amir Hussein, Shinji Watanabe, Ahmed Ali*2021 · 76 citations*](https://md.research.elamur.ai/free/en/papers/hussein-2021-arabic-speech-recognition-end-end/)
702. [**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/)
703. [**Iterative Translation Refinement with Large Language Models**Pinzhen Chen, Zhicheng Guo, Barry Haddow, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-iterative-translation-refinement-large-language/)
704. [**What Artificial Neural Networks Can Tell Us About Human Language Acquisition**Alex Warstadt, Samuel R. Bowman*2022 · 72 citations*](https://md.research.elamur.ai/free/en/papers/warstadt-2022-artificial-neural-networks-tell-us/)
705. [**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/)
706. [**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/)
707. [**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/)
708. [**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/)
709. [**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/)
710. [**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/)
711. [**Scaling Laws of RoPE-based Extrapolation**Xiaoran Liu, Hang Yan, Shuo Zhang, et al.*2023 · 53 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-scaling-laws-rope-based/)
712. [**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/)
713. [**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/)
714. [**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/)
715. [**Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model**Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban*2023 · 47 citations*](https://md.research.elamur.ai/free/en/papers/weissweiler-2023-chatgpt-wugs-morphology/)
716. [**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/)
717. [**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/)
718. [**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/)
719. [**A Hierarchical Neural Model for Learning Sequences of Dialogue Acts**Quan Hung Tran, Ingrid Zukerman, Gholamreza Haffari*2017 · 44 citations*](https://md.research.elamur.ai/free/en/papers/tran-2017-hierarchical-neural-model-learning-sequences/)
720. [**Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies**Chaofan Tao, Qian Liu, Longxu Dou, et al.*2024 · 42 citations*](https://md.research.elamur.ai/free/en/papers/tao-2024-scaling-laws-vocabulary-larger-models/)
721. [**Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling**Runze Liu, Junqi Gao, Jian Zhao, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-1b-llm-surpass-405b-llm/)
722. [**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/)
723. [**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/)
724. [**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/)
725. [**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/)
726. [**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/)
727. [**Towards Effective Disambiguation for Machine Translation with Large Language Models**Vivek Iyer, Pinzhen Chen, Alexandra Birch*2023 · 38 citations*](https://md.research.elamur.ai/free/en/papers/iyer-2023-effective-disambiguation-machine-translation-large/)
728. [**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/)
729. [**FRMT: A Benchmark for Few-Shot Region-Aware Machine Translation**Parker Riley, Timothy Dozat, Jan A. Botha, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/riley-2023-frmt-benchmark-few-shot-region/)
730. [**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/)
731. [**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/)
732. [**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/)
733. [**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/)
734. [**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/)
735. [**SemEval-2025 Task 1: AdMIRe - Advancing Multimodal Idiomaticity Representation**Thomas Pickard, Aline Villavicencio, Maggie Mi, et al.*2025 · 30 citations*](https://md.research.elamur.ai/free/en/papers/pickard-2025-semeval-2025-task-1-admire/)
736. [**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/)
737. [**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/)
738. [**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/)
739. [**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/)
740. [**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/)
741. [**Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling**Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.*2024 · 26 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2024-smaller-weaker-yet-better-training/)
742. [**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/)
743. [**Taqyim: Evaluating Arabic NLP Tasks Using ChatGPT Models**Zaid Alyafeai, Maged S. Alshaibani, Badr AlKhamissi, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2023-taqyim-evaluating-arabic-nlp-tasks/)
744. [**How Is LLM Reasoning Distracted by Irrelevant Context? An Analysis Using a Controlled Benchmark**Minglai Yang, Ethan Huang, Liang Zhang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-llm-reasoning-distracted-irrelevant-context/)
745. [**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/)
746. [**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/)
747. [**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/)
748. [**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/)
749. [**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/)
750. [**LLM-Assisted Rule Based Machine Translation for Low/No-Resource Languages**Jared Coleman, Bhaskar Krishnamachari, Ruben Rosales, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/coleman-2024-llm-assisted-rule-based-machine/)
751. [**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/)
752. [**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/)
753. [**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/)
754. [**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/)
755. [**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/)
756. [**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/)
757. [**Multi-Dialect Arabic Speech Recognition**Abbas Raza Ali*2020 · 18 citations*](https://md.research.elamur.ai/free/en/papers/ali-2021-multi-dialect-arabic-speech-recognition/)
758. [**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/)
759. [**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/)
760. [**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/)
761. [**Okay, Let's Do This! Modeling Event Coreference with Generated Rationales and Knowledge Distillation**Abhijnan Nath, Shadi Manafi Avari, Avyakta Chelle, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/nath-2024-okay-let-s-do-this/)
762. [**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/)
763. [**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/)
764. [**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/)
765. [**MASRI-HEADSET: A Maltese Corpus for Speech Recognition**Carlos Daniel Hernandez Mena, Albert Gatt, Andrea DeMarco, et al.*2020 · 16 citations*](https://md.research.elamur.ai/free/en/papers/mena-2020-masri-headset-maltese-corpus-speech/)
766. [**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/)
767. [**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/)
768. [**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/)
769. [**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/)
770. [**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/)
771. [**Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes On**Liang Zeng, Liangjun Zhong, Liang Zhao, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-skywork-math-data-scaling-laws/)
772. [**Constituency Parsing using LLMs**Xuefeng Bai, Jialong Wu, Yulong Chen, et al.*2023 · 14 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-constituency-parsing-using-llms/)
773. [**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/)
774. [**When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning**Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/)
775. [**Amharic LLaMA and LLaVA: Multimodal LLMs for Low Resource Languages**Michael Andersland*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/andersland-2024-amharic-llama-llava-multimodal-llms/)
776. [**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/)
777. [**Towards Ontology Construction with Language Models**Maurice Funk, Simon Hosemann, Jean Christoph Jung, et al.*2023 · 12 citations*](https://md.research.elamur.ai/free/en/papers/funk-2023-towards-ontology-construction-language-models/)
778. [**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/)
779. [**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/)
780. [**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/)
781. [**T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation**Anubhav Jangra, Preksha Nema, Aravindan Raghuveer*2022 · 11 citations*](https://md.research.elamur.ai/free/en/papers/jangra-2022-t-star-truthful-style-transfer/)
782. [**How Often Are Errors in Natural Language Reasoning Due to Paraphrastic Variability?**Neha Srikanth, Marine Carpuat, Rachel Rudinger*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/srikanth-2024-how-often-are-errors-natural/)
783. [**Overview of PragTag-2023: Low-Resource Multi-Domain Pragmatic Tagging of Peer Reviews**Nils Dycke, Ilia Kuznetsov, Iryna Gurevych*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/dycke-2023-overview-pragtag-2023-low-resource/)
784. [**TEPrompt: Task Enlightenment Prompt Learning for Implicit Discourse Relation Recognition**Wei Xiang, Chao Liang, Bang Wang*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/xiang-2023-teprompt-task-enlightenment-prompt-learning/)
785. [**Towards Arabic Sentence Simplification via Classification and Generative Approaches**Nouran Khallaf, Serge Sharoff, Rasha Soliman*2022 · 10 citations*](https://md.research.elamur.ai/free/en/papers/khallaf-2022-arabic-sentence-simplification-classification-generative/)
786. [**Multilingual Sequence-to-Sequence Models for Hebrew NLP**Matan Eyal, Hila Noga, Roee Aharoni, et al.*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/eyal-2023-multilingual-sequence-sequence-models-hebrew/)
787. [**TATA: Stance Detection via Topic-Agnostic and Topic-Aware Embeddings**Hans Hanley, Zakir Durumeric*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/hanley-2023-tata-stance-detection-topic-agnostic/)
788. [**When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! Principle**Judith Sieker, Sina Zarrieß*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/sieker-2023-when-your-language-model-cannot/)
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