---
title: "Who cites Pranav Shyam — page 6"
description: "13,326 papers of the Elamur Research library cite the works of Pranav Shyam, found in their bibliographies · page 6 of 10 · 501–600; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/pranav-shyam/cited-by/page/6/"
---
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# Who cites Pranav Shyam

14,304 citations of their works from 13,326 papers of our library (of the 140,884 whose bibliographies we read) · 932 with a page here, the most cited first · page 6 of 10 · 501–600 · [← Pranav Shyam](https://md.research.elamur.ai/free/en/authors/pranav-shyam/)

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501. [**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/)
502. [**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/)
503. [**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/)
504. [**Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier**John Dang, Shivalika Singh, Daniel D'souza, et al.*2024 · 180 citations*](https://md.research.elamur.ai/free/en/papers/dang-2024-aya-expanse-combining-research-breakthroughs/)
505. [**GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models**Archiki Prasad, Peter Hase, Xiang Zhou, et al.*2023 · 180 citations*](https://md.research.elamur.ai/free/en/papers/prasad-2023-grips-gradient-free-edit-based/)
506. [**Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning**Fuxiao Liu, Kevin Lin, Linjie Li, et al.*2023 · 180 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-mitigating-hallucination-large-multi-modal/)
507. [**Knowledge Conflicts for LLMs: A Survey**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 179 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/)
508. [**Adapting Language Models to Compress Contexts**Alexis Chevalier, Alexander Wettig, Anirudh Ajith, et al.*2023 · 179 citations*](https://md.research.elamur.ai/free/en/papers/chevalier-2023-adapting-language-models-compress-contexts/)
509. [**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/)
510. [**Eliciting Latent Predictions from Transformers with the Tuned Lens**Nora Belrose, Igor Ostrovsky, Lev McKinney, et al.*2023 · 179 citations*](https://md.research.elamur.ai/free/en/papers/belrose-2023-eliciting-latent-predictions-transformers-tuned/)
511. [**Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/)
512. [**Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization**Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/tseng-2024-two-tales-persona-llms-survey/)
513. [**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/)
514. [**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/)
515. [**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/)
516. [**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/)
517. [**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/)
518. [**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/)
519. [**Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models**Nora Kassner, Philipp Dufter, Hinrich Schütze*2021 · 175 citations*](https://md.research.elamur.ai/free/en/papers/kassner-2021-multilingual-lama-investigating-knowledge-multilingual/)
520. [**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/)
521. [**DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text**Jinyan Su, Terry Zhuo, Di Wang, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/su-2023-detectllm-leveraging-log-rank-information/)
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. [**Aya 23: Open Weight Releases to Further Multilingual Progress**Viraat Aryabumi, John Dang, Dwarak Talupuru, et al.*2024 · 171 citations*](https://md.research.elamur.ai/free/en/papers/aryabumi-2024-aya-23-open-weight-releases/)
524. [**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/)
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. [**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/)
537. [**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/)
538. [**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/)
539. [**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/)
540. [**On Generative Spoken Language Modeling from Raw Audio**Kushal Lakhotia, Eugene Kharitonov, Wei-Ning Hsu, et al.*2021 · 165 citations*](https://md.research.elamur.ai/free/en/papers/lakhotia-2021-generative-spoken-language-modeling-raw/)
541. [**Sustainable Modular Debiasing of Language Models**Anne Lauscher, Tobias Lueken, Goran Glavaš*2021 · 165 citations*](https://md.research.elamur.ai/free/en/papers/lauscher-2021-sustainable-modular-debiasing-language-models/)
542. [**Large Language Diffusion Models**Shen Nie, Fengqi Zhu, Zebin You, et al.*2025 · 164 citations*](https://md.research.elamur.ai/free/en/papers/nie-2025-large-language-diffusion-models/)
543. [**Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models**Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.*2023 · 164 citations*](https://md.research.elamur.ai/free/en/papers/ahia-2023-do-all-languages-cost-same/)
544. [**PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts**Stephen H. Bach, Victor Sanh, Zheng-Xin Yong, et al.*2022 · 164 citations*](https://md.research.elamur.ai/free/en/papers/bach-2022-promptsource-integrated-development-environment-repository/)
545. [**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/)
546. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/)
547. [**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/)
548. [**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/)
549. [**Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision**Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.*2023 · 163 citations*](https://md.research.elamur.ai/free/en/papers/burns-2023-weak-strong-generalization-eliciting-strong/)
550. [**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/)
551. [**Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation**Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-catastrophic-jailbreak-open-source-llms/)
552. [**GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts**Jiahao Yu, Xingwei Lin, Zheng Yu, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-gptfuzzer-red-teaming-large-language/)
553. [**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/)
554. [**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/)
555. [**SCROLLS: Standardized CompaRison Over Long Language Sequences**Uri Shaham, Elad Segal, Maor Ivgi, et al.*2022 · 162 citations*](https://md.research.elamur.ai/free/en/papers/shaham-2022-scrolls-standardized-comparison-over-long/)
556. [**Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents**Zihao Wang, Shaofei Cai, Guanzhou Chen, et al.*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-describe-explain-plan-select-interactive/)
557. [**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/)
558. [**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/)
559. [**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/)
560. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 159 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
561. [**MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents**Liyan Tang, Philippe Laban, Greg Durrett*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-minicheck-efficient-fact-checking-llms/)
562. [**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/)
563. [**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/)
564. [**GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models**Aohan Zeng, Xin Lv, Qinkai Zheng, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-4-glm-4-5-agentic/)
565. [**From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning**Ming Li, Yong Zhang, Zhitao Li, et al.*2023 · 157 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-quantity-quality-boosting-llm-performance/)
566. [**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/)
567. [**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/)
568. [**Large Language Models Effectively Leverage Document-level Context for Literary Translation, but Critical Errors Persist**Marzena Karpinska, Mohit Iyyer*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/karpinska-2023-large-language-models-effectively-leverage/)
569. [**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/)
570. [**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/)
571. [**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/)
572. [**WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs**Seungju Han, Kavel Rao, Allyson Ettinger, et al.*2024 · 155 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-wildguard-open-one-stop-moderation/)
573. [**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/)
574. [**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/)
575. [**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/)
576. [**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/)
577. [**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/)
578. [**Can GPT-3 Perform Statutory Reasoning?**Andrew Blair-Stanek, Nils Holzenberger, Benjamin Van Durme*2023 · 153 citations*](https://md.research.elamur.ai/free/en/papers/blair-stanek-2023-gpt-3-perform-statutory-reasoning/)
579. [**Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning**Lean Wang, Lei Li, Damai Dai, et al.*2023 · 153 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-label-words-anchors-information-flow/)
580. [**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/)
581. [**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/)
582. [**ChatGPT MT: Competitive for High- (but Not Low-) Resource Languages**Nathaniel Robinson, Perez Ogayo, David R. Mortensen, et al.*2023 · 151 citations*](https://md.research.elamur.ai/free/en/papers/robinson-2023-chatgpt-mt-competitive-high-but/)
583. [**The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models**Junyi Li, Jie Chen, Ruiyang Ren, et al.*2024 · 150 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-dawn-after-dark-empirical-study/)
584. [**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/)
585. [**Generation-Augmented Retrieval for Open-domain Question Answering**Yuning Mao, Pengcheng He, Xiaodong Liu, et al.*2020 · 150 citations*](https://md.research.elamur.ai/free/en/papers/mao-2020-generation-augmented-retrieval-open-domain/)
586. [**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/)
587. [**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/)
588. [**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/)
589. [**BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages**Junho Myung, Nayeon Lee, Yi Zhou, et al.*2024 · 147 citations*](https://md.research.elamur.ai/free/en/papers/myung-2024-blend-benchmark-llms-everyday-knowledge/)
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