---
title: "Who cites Prafulla Dhariwal — page 6"
description: "12,963 papers of the Elamur Research library cite the works of Prafulla Dhariwal, found in their bibliographies · page 6 of 9 · 501–600; the most cited…"
canonical: "https://research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/6/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/6/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Prafulla Dhariwal](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/) / [cited by](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/) / page 6

# Who cites Prafulla Dhariwal

13,378 citations of their works from 12,963 papers of our library (of the 140,884 whose bibliographies we read) · 891 with a page here, the most cited first · page 6 of 9 · 501–600 · [← Prafulla Dhariwal](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/)

[← prev](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/5/) [1](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/) … [5](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/5/) **6** [7](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/7/) [8](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/8/) [9](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/9/) [next →](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/7/)

501. [**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/)
502. [**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/)
503. [**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/)
504. [**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/)
505. [**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/)
506. [**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/)
507. [**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/)
508. [**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/)
509. [**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/)
510. [**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/)
511. [**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/)
512. [**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/)
513. [**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/)
514. [**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/)
515. [**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/)
516. [**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/)
517. [**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/)
518. [**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/)
519. [**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/)
520. [**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/)
521. [**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/)
522. [**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/)
523. [**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/)
524. [**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/)
525. [**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/)
526. [**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/)
527. [**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/)
528. [**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/)
529. [**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/)
530. [**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/)
531. [**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/)
532. [**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/)
533. [**The Lessons of Developing Process Reward Models in Mathematical Reasoning**Zhenru Zhang, Chujie Zheng, Yangzhen Wu, et al.*2025 · 155 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-lessons-developing-process-reward-models/)
534. [**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/)
535. [**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/)
536. [**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/)
537. [**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/)
538. [**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/)
539. [**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/)
540. [**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/)
541. [**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/)
542. [**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/)
543. [**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/)
544. [**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/)
545. [**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/)
546. [**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/)
547. [**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/)
548. [**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/)
549. [**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/)
550. [**SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild**Weihao Zeng, Yuzhen Huang, Qian Liu, et al.*2025 · 148 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2025-simplerl-zoo-investigating-taming-zero/)
551. [**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/)
552. [**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/)
553. [**Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature**Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, et al.*2023 · 146 citations*](https://md.research.elamur.ai/free/en/papers/bao-2023-fast-detectgpt-efficient-zero-shot/)
554. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 145 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
555. [**How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition**Guanting Dong, Hongyi Yuan, Keming Lu, et al.*2024 · 145 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-how-abilities-large-language-models/)
556. [**Context-faithful Prompting for Large Language Models**Wenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-context-faithful-prompting-large-language/)
557. [**Fact-Checking Complex Claims with Program-Guided Reasoning**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/)
558. [**Self-Evaluation Guided Beam Search for Reasoning**Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/xie-2023-self-evaluation-guided-beam-search/)
559. [**The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset**Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-bigscience-roots-corpus-1-6tb/)
560. [**Unified Demonstration Retriever for In-Context Learning**Xiaonan Li, Kai Lv, Hang Yan, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-unified-demonstration-retriever-context-learning/)
561. [**Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework**Ruochen Zhao, Xingxuan Li, Shafiq Joty, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-verify-edit-knowledge-enhanced-chain/)
562. [**In-Context Learning for Few-Shot Dialogue State Tracking**Yushi Hu, Chia-Hsuan Lee, Tianbao Xie, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/hu-2022-context-learning-few-shot-dialogue/)
563. [**Is GPT-3 a Good Data Annotator?**Bosheng Ding, Chengwei Qin, Linlin Liu, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-gpt-3-good-data-annotator/)
564. [**MiniLLM: On-Policy Distillation of Large Language Models**Yuxian Gu, Li Dong, Furu Wei, et al.*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-minillm-policy-distillation-large-language/)
565. [**In-Context Learning Creates Task Vectors**Roee Hendel, Mor Geva, Amir Globerson*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/hendel-2023-context-learning-creates-task-vectors/)
566. [**ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings**Shibo Hao, Tianyang Liu, Zhen Wang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/hao-2023-toolkengpt-augmenting-frozen-language-models/)
567. [**TALM: Tool Augmented Language Models**Aaron Parisi, Yao Zhao, Noah Fiedel*2022 · 142 citations*](https://md.research.elamur.ai/free/en/papers/parisi-2022-talm-tool-augmented-language-models/)
568. [**Rethinking embedding coupling in pre-trained language models**Hyung Won Chung, Thibault Févry, Henry Tsai, et al.*2020 · 142 citations*](https://md.research.elamur.ai/free/en/papers/chung-2020-rethinking-embedding-coupling-pre-trained/)
569. [**JudgeLM: Fine-tuned Large Language Models are Scalable Judges**Lianghui Zhu, Xinggang Wang, Xinlong Wang*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-judgelm-fine-tuned-large-language/)
570. [**ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics**Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, et al.*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-proofnet-autoformalizing-formally-proving-undergraduate/)
571. [**How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model**Michael Hanna, Ollie Liu, Alexandre Variengien*2023 · 140 citations*](https://md.research.elamur.ai/free/en/papers/hanna-2023-gpt-2-compute-greater-than/)
572. [**A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation**Tianyu Liu, Yizhe Zhang, Chris Brockett, et al.*2022 · 140 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-token-level-reference-free-hallucination/)
573. [**A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation**Neeraj Varshney; Wenlin Yao; Hongming Zhang; Jianshu Chen;, Dong Yu*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/varshney-2023-stitch-time-saves-nine-detecting/)
574. [**Diverse Demonstrations Improve In-context Compositional Generalization**Itay Levy, Ben Bogin, Jonathan Berant*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/levy-2023-diverse-demonstrations-improve-context-compositional/)
575. [**Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration**Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, et al.*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-unleashing-emergent-cognitive-synergy-large/)
576. [**Exploring Length Generalization in Large Language Models**Cem Anil, Yuhuai Wu, Anders Andreassen, et al.*2022 · 138 citations*](https://md.research.elamur.ai/free/en/papers/anil-2022-exploring-length-generalization-large-language/)
577. [**Investigating Data Contamination in Modern Benchmarks for Large Language Models**Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/deng-2024-investigating-data-contamination-modern-benchmarks/)
578. [**Efficient Training of Language Models to Fill in the Middle**Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.*2022 · 137 citations*](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/)
579. [**Agent Laboratory: Using LLM Agents as Research Assistants**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 136 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/)
580. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/)
581. [**NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics**Ximing Lu, Sean Welleck, Peter West, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/lu-2022-neurologic-esque-decoding-constrained-text/)
582. [**A Roadmap to Pluralistic Alignment**Taylor Sorensen, Jared Moore, Jillian Fisher, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/sorensen-2024-roadmap-pluralistic-alignment/)
583. [**Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models**Qingyu Lu, Baopu Qiu, Liang Ding, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-error-analysis-prompting-enables-human/)
584. [**RAFT: Adapting Language Model to Domain Specific RAG**Tianjun Zhang, Shishir G. Patil, Naman Jain, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-raft-adapting-language-model-domain/)
585. [**SLiC-HF: Sequence Likelihood Calibration with Human Feedback**Yao Zhao, Rishabh Joshi, Tianqi Liu, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-slic-hf-sequence-likelihood-calibration/)
586. [**Many-Shot In-Context Learning**Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2024-many-shot-context-learning/)
587. [**Few-Shot Self-Rationalization with Natural Language Prompts**Ana Marasovic, Iz Beltagy, Doug Downey, et al.*2022 · 134 citations*](https://md.research.elamur.ai/free/en/papers/marasovic-2022-few-shot-self-rationalization-natural/)
588. [**InFoBench: Evaluating Instruction Following Ability in Large Language Models**Yiwei Qin, Kaiqiang Song, Yebowen Hu, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-infobench-evaluating-instruction-following-ability/)
589. [**Prompting is not a substitute for probability measurements in large language models**Jennifer Hu, Roger Levy*2023 · 133 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-prompting-is-not-substitute-probability/)
590. [**Formal Mathematics Statement Curriculum Learning**Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.*2022 · 132 citations*](https://md.research.elamur.ai/free/en/papers/polu-2022-formal-mathematics-statement-curriculum-learning/)
591. [**Understanding the Effects of RLHF on LLM Generalisation and Diversity**Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/kirk-2023-understanding-effects-rlhf-llm-generalisation/)
592. [**Extracting Latent Steering Vectors from Pretrained Language Models**Nishant Subramani, Nivedita Suresh, Matthew Peters*2022 · 131 citations*](https://md.research.elamur.ai/free/en/papers/subramani-2022-extracting-latent-steering-vectors-pretrained/)
593. [**FLUTE: Figurative Language Understanding through Textual Explanations**Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.*2022 · 131 citations*](https://md.research.elamur.ai/free/en/papers/chakrabarty-2022-flute-figurative-language-understanding-through/)
594. [**FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation**Tu Vu, Mohit Iyyer, Xuezhi Wang, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/vu-2023-freshllms-refreshing-large-language-models/)
595. [**MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems**Jakub Macina, Nico Daheim, Sankalan Chowdhury, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/macina-2023-mathdial-dialogue-tutoring-dataset-rich/)
596. [**Secrets of RLHF in Large Language Models Part I: PPO**Rui Zheng, Shihan Dou, Songyang Gao, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-secrets-rlhf-large-language-models/)
597. [**Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback**Yao Fu, Hao Peng, Tushar Khot, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-improving-language-model-negotiation-self/)
598. [**Retrieval meets Long Context Large Language Models**Peng Xu, Wei Ping, Xianchao Wu, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-retrieval-meets-long-context-large/)
599. [**Deductive Verification of Chain-of-Thought Reasoning**Zhan Ling, Yunhao Fang, Xuanlin Li, et al.*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/ling-2023-deductive-verification-chain-thought-reasoning/)
600. [**Sequence Parallelism: Long Sequence Training from System Perspective**Shenggui Li, Fuzhao Xue, Chaitanya Baranwal, et al.*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-sequence-parallelism-long-sequence-training/)

[← prev](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/5/) [1](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/) … [5](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/5/) **6** [7](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/7/) [8](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/8/) [9](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/9/) [next →](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/cited-by/page/7/)

- [← back to](https://md.research.elamur.ai/free/en/authors/prafulla-dhariwal/) — Prafulla Dhariwal
