---
title: "Who cites Sharan Narang — page 6"
description: "11,493 papers of the Elamur Research library cite the works of Sharan Narang, found in their bibliographies · page 6 of 9 · 501–600; 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 6 of 9 · 501–600 · [← Sharan Narang](https://md.research.elamur.ai/free/en/authors/sharan-narang/)

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501. [**LawBench: Benchmarking Legal Knowledge of Large Language Models**Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.*2023 · 184 citations*](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/)
502. [**OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents**Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/)
503. [**Preference Ranking Optimization for Human Alignment**Feifan Song, Bowen Yu, Minghao Li, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/song-2023-preference-ranking-optimization-human-alignment/)
504. [**Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models**Kushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, et al.*2022 · 183 citations*](https://md.research.elamur.ai/free/en/papers/tirumala-2022-memorization-overfitting-analyzing-training-dynamics/)
505. [**Re2G: Retrieve, Rerank, Generate**Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, et al.*2022 · 183 citations*](https://md.research.elamur.ai/free/en/papers/glass-2022-re2g-retrieve-rerank-generate/)
506. [**Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers**Chenglei Si, Diyi Yang, Tatsunori Hashimoto*2024 · 182 citations*](https://md.research.elamur.ai/free/en/papers/si-2024-llms-generate-novel-research/)
507. [**Large Language Models are few(1)-shot Table Reasoners**Wenhu Chen*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-large-language-models-are-few/)
508. [**Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models**Yunfei Chu, Jin Xu, Xiaohuan Zhou, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-qwen-audio-advancing-universal/)
509. [**Pre-training via Paraphrasing**Mike Lewis, Marjan Ghazvininejad, Gargi Ghosh, et al.*2020 · 181 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2020-pre-training-paraphrasing/)
510. [**On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning**Omar Shaikh, Hongxin Zhang, William Held, et al.*2023 · 180 citations*](https://md.research.elamur.ai/free/en/papers/shaikh-2023-second-thought-let-s-not/)
511. [**CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages**Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, et al.*2023 · 179 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2023-culturax-cleaned-enormous-multilingual-dataset/)
512. [**Charformer: Fast Character Transformers via Gradient-based Subword Tokenization**Yi Tay, Vinh Q. Tran, Sebastian Ruder, et al.*2021 · 179 citations*](https://md.research.elamur.ai/free/en/papers/tay-2021-charformer-fast-character-transformers-gradient/)
513. [**The False Promise of Imitating Proprietary LLMs**Arnav Gudibande, Eric Wallace, Charlie Snell, et al.*2023 · 178 citations*](https://md.research.elamur.ai/free/en/papers/gudibande-2023-false-promise-imitating-proprietary-llms/)
514. [**Evaluating Large Language Models: A Comprehensive Survey**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
515. [**On the Risk of Misinformation Pollution with Large Language Models**Yikang Pan, Liangming Pan, Wenhu Chen, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-risk-misinformation-pollution-large-language/)
516. [**ToolQA: A Dataset for LLM Question Answering with External Tools**Yuchen Zhuang, Yue Yu, Kuan Wang, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-toolqa-dataset-llm-question-answering/)
517. [**Findings of the IWSLT 2022 Evaluation Campaign**Antonios Anastasopoulos, Loïc Barrault, Luisa Bentivogli, et al.*2022 · 177 citations*](https://md.research.elamur.ai/free/en/papers/anastasopoulos-2022-findings-iwslt-2022-evaluation-campaign/)
518. [**8-bit Optimizers via Block-wise Quantization**Tim Dettmers, Mike Lewis, Sam Shleifer, et al.*2021 · 177 citations*](https://md.research.elamur.ai/free/en/papers/dettmers-2021-8-bit-optimizers-block-wise/)
519. [**RealTime QA: What's the Answer Right Now?**Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, et al.*2022 · 176 citations*](https://md.research.elamur.ai/free/en/papers/kasai-2022-realtime-qa-s-answer-right/)
520. [**Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs**Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.*2022 · 175 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-draft-sketch-prove-guiding-formal/)
521. [**Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 174 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/)
522. [**SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language Model**Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.*2025 · 171 citations*](https://md.research.elamur.ai/free/en/papers/allal-2025-smollm2-smol-goes-big-data/)
523. [**LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers**Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/olausson-2023-linc-neurosymbolic-approach-logical-reasoning/)
524. [**OpenChat: Advancing Open-source Language Models with Mixed-Quality Data**Guan Wang, Sijie Cheng, Xianyuan Zhan, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-openchat-advancing-open-source-language/)
525. [**ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering**Zhiyu Chen, Shiyang Li, Charese Smiley, et al.*2022 · 171 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-convfinqa-exploring-chain-numerical-reasoning/)
526. [**Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs**Simone Balloccu, Patrícia Schmidtová, Mateusz Lango, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/balloccu-2024-leak-cheat-repeat-data-contamination/)
527. [**AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning**Qingru Zhang, Minshuo Chen, Alexander Bukharin, et al.*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-adalora-adaptive-budget-allocation-parameter/)
528. [**Learning to Compress Prompts with Gist Tokens**Jesse Mu, Xiang Lisa Li, Noah Goodman*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/mu-2023-learning-compress-prompts-gist-tokens/)
529. [**Generating Sequences by Learning to Self-Correct**Sean Welleck, Ximing Lu, Peter West, et al.*2022 · 170 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2022-generating-sequences-learning-self-correct/)
530. [**AudioPaLM: A Large Language Model That Can Speak and Listen**Paul K. Rubenstein, Chulayuth Asawaroengchai, Duc Dung Nguyen, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/rubenstein-2023-audiopalm-large-language-model-that/)
531. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
532. [**WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models**Hongliang He, Wenlin Yao, Kaixin Ma, et al.*2024 · 168 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-webvoyager-building-end-end-web/)
533. [**Aligning Large Multimodal Models with Factually Augmented RLHF**Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-aligning-large-multimodal-models-factually/)
534. [**SqueezeLLM: Dense-and-Sparse Quantization**Sehoon Kim, Coleman Hooper, Amir Gholami, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-squeezellm-dense-sparse-quantization/)
535. [**Promptagator: Few-shot Dense Retrieval From 8 Examples**Zhuyun Dai, Vincent Y. Zhao, Ji Ma, et al.*2022 · 167 citations*](https://md.research.elamur.ai/free/en/papers/dai-2022-promptagator-few-shot-dense-retrieval/)
536. [**Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4**Kent K. Chang, Mackenzie Cramer, Sandeep Soni, et al.*2023 · 166 citations*](https://md.research.elamur.ai/free/en/papers/chang-2023-speak-memory-archaeology-books-known/)
537. [**Deduplicating Training Data Mitigates Privacy Risks in Language Models**Nikhil Kandpal, Eric Wallace, Colin Raffel*2022 · 166 citations*](https://md.research.elamur.ai/free/en/papers/kandpal-2022-deduplicating-training-data-mitigates-privacy/)
538. [**Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization**Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kiante Brantley, et al.*2022 · 166 citations*](https://md.research.elamur.ai/free/en/papers/ramamurthy-2022-reinforcement-learning-natural-language-processing/)
539. [**Generative Representational Instruction Tuning**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
540. [**Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts**Jian Xie, Kai Zhang, Jiangjie Chen, et al.*2023 · 165 citations*](https://md.research.elamur.ai/free/en/papers/xie-2023-adaptive-chameleon-stubborn-sloth-revealing/)
541. [**Binding Language Models in Symbolic Languages**Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.*2022 · 165 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2022-binding-language-models-symbolic-languages/)
542. [**SantaCoder: don't reach for the stars!**Loubna Ben Allal, Raymond Li, Denis Kocetkov, et al.*2023 · 164 citations*](https://md.research.elamur.ai/free/en/papers/allal-2023-santacoder-don-t-reach-stars/)
543. [**Quark: Controllable Text Generation with Reinforced Unlearning**Ximing Lu, Sean Welleck, Jack Hessel, et al.*2022 · 164 citations*](https://md.research.elamur.ai/free/en/papers/lu-2022-quark-controllable-text-generation-reinforced/)
544. [**CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer**Zhuoyi Yang, Jiayan Teng, Wendi Zheng, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-cogvideox-text-video-diffusion/)
545. [**Improve Mathematical Reasoning in Language Models by Automated Process Supervision**Liangchen Luo, Yinxiao Liu, Rosanne Liu, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-improve-mathematical-reasoning-language-models/)
546. [**Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution**Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, et al.*2023 · 163 citations*](https://md.research.elamur.ai/free/en/papers/fernando-2023-promptbreeder-self-referential-self-improvement/)
547. [**The 2020 Bilingual, Bi-Directional WebNLG+ Shared Task: Overview and Evaluation Results (WebNLG+ 2020)**Thiago Castro Ferreira, Claire Gardent, Nikolai Ilinykh, et al.*2020 · 163 citations*](https://md.research.elamur.ai/free/en/papers/ferreira-2020-2020-bilingual-bi-directional-webnlg/)
548. [**Long-form factuality in large language models**Jerry Wei, Chengrun Yang, Xinying Song, et al.*2024 · 162 citations*](https://md.research.elamur.ai/free/en/papers/wei-2024-long-form-factuality-large-language/)
549. [**LooGLE: Can Long-Context Language Models Understand Long Contexts?**Jiaqi Li, Mengmeng Wang, Zilong Zheng, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-loogle-long-context-language-models/)
550. [**Impact of Pretraining Term Frequencies on Few-Shot Numerical Reasoning**Yasaman Razeghi, Robert L Logan IV, Matt Gardner, et al.*2022 · 162 citations*](https://md.research.elamur.ai/free/en/papers/razeghi-2022-impact-pretraining-term-frequencies-few/)
551. [**QuALITY: Question Answering with Long Input Texts, Yes!**Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, et al.*2022 · 161 citations*](https://md.research.elamur.ai/free/en/papers/pang-2022-quality-question-answering-long-input/)
552. [**ChatGPT as a Factual Inconsistency Evaluator for Text Summarization**Zheheng Luo, Qianqian Xie, Sophia Ananiadou*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-chatgpt-factual-inconsistency-evaluator-text/)
553. [**Reasoning with Language Model Prompting: A Survey**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 160 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
554. [**Larger-Scale Transformers for Multilingual Masked Language Modeling**Naman Goyal, Jingfei Du, Myle Ott, et al.*2021 · 160 citations*](https://md.research.elamur.ai/free/en/papers/goyal-2021-larger-scale-transformers-multilingual-masked/)
555. [**MultiEURLEX - A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer**Ilias Chalkidis, Manos Fergadiotis, Ion Androutsopoulos*2021 · 160 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-multieurlex-multi-lingual-multi-label/)
556. [**When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/)
557. [**DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models**Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, et al.*2023 · 159 citations*](https://md.research.elamur.ai/free/en/papers/jacobs-2023-deepspeed-ulysses-system-optimizations-enabling/)
558. [**PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation**Wei Zeng, Xiaozhe Ren, Teng Su, et al.*2021 · 159 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2021-pangu-alpha-large-scale/)
559. [**AgentTuning: Enabling Generalized Agent Abilities for LLMs**Aohan Zeng, Mingdao Liu, Rui Lu, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2023-agenttuning-enabling-generalized-agent/)
560. [**Testing the Predictions of Surprisal Theory in 11 Languages**Ethan G. Wilcox, Tiago Pimentel, Clara Meister, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/wilcox-2023-testing-predictions-surprisal-theory-11/)
561. [**DataComp-LM: In search of the next generation of training sets for language models**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 156 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/)
562. [**VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks**Jing Yu Koh, Robert Lo, Lawrence Jang, et al.*2024 · 156 citations*](https://md.research.elamur.ai/free/en/papers/koh-2024-visualwebarena-evaluating-multimodal-agents-realistic/)
563. [**The Devil Is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation**Patrick Fernandes, Daniel Deutsch, Mara Finkelstein, et al.*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/fernandes-2023-devil-is-errors-leveraging-large/)
564. [**Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation**Jonathan H. Clark, Dan Garrette, Iulia Turc, et al.*2022 · 156 citations*](https://md.research.elamur.ai/free/en/papers/clark-2022-canine-pre-training-efficient-tokenization/)
565. [**HunyuanVideo: A Systematic Framework For Large Video Generative Models**Weijie Kong, Qi Tian, Zijian Zhang, et al.*2024 · 155 citations*](https://md.research.elamur.ai/free/en/papers/kong-2024-hunyuanvideo-systematic-framework-large/)
566. [**LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding**Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, et al.*2024 · 155 citations*](https://md.research.elamur.ai/free/en/papers/elhoushi-2024-layerskip-enabling-early-exit-inference/)
567. [**Lawyer LLaMA Technical Report**Quzhe Huang, Mingxu Tao, Chen Zhang, et al.*2023 · 155 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-lawyer-llama-technical-report/)
568. [**GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval**Kexin Wang, Nandan Thakur, Nils Reimers, et al.*2022 · 155 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-gpl-generative-pseudo-labeling-unsupervised/)
569. [**Moshi: a speech-text foundation model for real-time dialogue**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 154 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
570. [**ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs**Justin Chen, Swarnadeep Saha, Mohit Bansal*2024 · 154 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-reconcile-round-table-conference-improves/)
571. [**Large Language Models with Controllable Working Memory**Daliang Li, Ankit Singh Rawat, Manzil Zaheer, et al.*2023 · 154 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-large-language-models-controllable-working/)
572. [**TheoremQA: A Theorem-driven Question Answering Dataset**Wenhu Chen, Ming Yin, Max Ku, et al.*2023 · 154 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-theoremqa-theorem-driven-question-answering/)
573. [**Leveraging Large Language Models for Multiple Choice Question Answering**Joshua Robinson, Christopher Michael Rytting, David Wingate*2022 · 154 citations*](https://md.research.elamur.ai/free/en/papers/robinson-2022-leveraging-large-language-models-multiple/)
574. [**Towards a Cleaner Document-Oriented Multilingual Crawled Corpus**Julien Abadji, Pedro Ortiz Suarez, Laurent Romary, et al.*2022 · 154 citations*](https://md.research.elamur.ai/free/en/papers/abadji-2022-towards-cleaner-document-oriented-multilingual/)
575. [**DART: Open-Domain Structured Data Record to Text Generation**Linyong Nan, Dragomir Radev, Rui Zhang, et al.*2020 · 154 citations*](https://md.research.elamur.ai/free/en/papers/nan-2020-dart-open-domain-structured-data/)
576. [**Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models**Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.*2025 · 153 citations*](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)
577. [**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/)
578. [**Locally Typical Sampling**Clara Meister, Tiago Pimentel, Gian Wiher, et al.*2023 · 152 citations*](https://md.research.elamur.ai/free/en/papers/meister-2023-locally-typical-sampling/)
579. [**REFINER: Reasoning Feedback on Intermediate Representations**Debjit Paul, Mete Ismayilzada, Maxime Peyrard, et al.*2023 · 152 citations*](https://md.research.elamur.ai/free/en/papers/paul-2023-refiner-reasoning-feedback-intermediate-representations/)
580. [**Training Language Models to Self-Correct via Reinforcement Learning**Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.*2024 · 151 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2024-training-language-models-self-correct/)
581. [**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/)
582. [**Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation**Niels Mundler, Jingxuan He, Slobodan Jenko, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/mundler-2023-self-contradictory-hallucinations-large-language/)
583. [**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/)
584. [**ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning**Olga Golovneva, Moya Chen, Spencer Poff, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/golovneva-2022-roscoe-suite-metrics-scoring-step/)
585. [**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/)
586. [**SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models**Xiaoxuan Wang, Ziniu Hu, Pan Lu, et al.*2023 · 148 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-scibench-evaluating-college-level-scientific/)
587. [**Measuring short-form factuality in large language models**Jason Wei, Nguyen Karina, Hyung Won Chung, et al.*2024 · 147 citations*](https://md.research.elamur.ai/free/en/papers/wei-2024-measuring-short-form-factuality-large/)
588. [**rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking**Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.*2025 · 146 citations*](https://md.research.elamur.ai/free/en/papers/guan-2025-rstar-math-small-llms-can/)
589. [**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/)
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