---
title: "Who cites Kensen Shi — page 4 — 2,760 papers of our library"
description: "2,760 papers of the Elamur Research library cite the works of Kensen Shi, found in their bibliographies · page 4 of 8 · 301–400; the most cited first."
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---
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# Who cites Kensen Shi

2,769 citations of their works from 2,760 papers of our library (of the 149,439 whose bibliographies we read) · 731 with a page here, the most cited first · page 4 of 8 · 301–400 · [← Kensen Shi](https://md.research.elamur.ai/free/en/authors/kensen-shi/)

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301. **[Investigating Data Contamination in Modern Benchmarks for Large Language Models](https://md.research.elamur.ai/free/en/papers/deng-2024-investigating-data-contamination-modern-benchmarks/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.*2024 · 137 citations*
302. [**Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V arXiv:2310.11441**Jianwei Yang, Hao Zhang, Feng Li, et al.*2023 · 137 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-set-mark-prompting-unleashes-extraordinary/)
303. **[InFoBench: Evaluating Instruction Following Ability in Large Language Models](https://md.research.elamur.ai/free/en/papers/qin-2024-infobench-evaluating-instruction-following-ability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiwei Qin, Kaiqiang Song, Yebowen Hu, et al.*2024 · 136 citations*
304. [**A fine-grained comparison of pragmatic language understanding in humans and language models**Jennifer Hu, Sammy Floyd, Olessia Jouravlev, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-fine-grained-comparison-pragmatic-language/)
305. [**Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions arXiv:2309.07875**Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/bianchi-2023-safety-tuned-llamas-lessons-improving/)
306. **[Self-Knowledge Guided Retrieval Augmentation for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-self-knowledge-guided-retrieval-augmentation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yile Wang, Peng Li, Maosong Sun, et al.*2023 · 135 citations*
307. [**Analyzing and Mitigating Object Hallucination in Large Vision-Language Models arXiv:2310.00754**Yiyang Zhou, Chenhang Cui, Jaehong Yoon, et al.*2023 · 134 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-analyzing-mitigating-object-hallucination-large/)
308. [**FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation arXiv:2310.03214**Tu Vu, Mohit Iyyer, Xuezhi Wang, et al.*2023 · 134 citations*](https://md.research.elamur.ai/free/en/papers/vu-2023-freshllms-refreshing-large-language-models/)
309. [**Simple synthetic data reduces sycophancy in large language models arXiv:2308.03958**Jerry Wei, Da Huang, Yifeng Lu, et al.*2023 · 134 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-simple-synthetic-data-reduces-sycophancy/)
310. **[The Impact of Positional Encoding on Length Generalization in Transformers](https://md.research.elamur.ai/free/en/papers/kazemnejad-2023-impact-positional-encoding-length-generalization/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, et al.*2023 · 134 citations*
311. **[Few-Shot Self-Rationalization with Natural Language Prompts](https://md.research.elamur.ai/free/en/papers/marasovic-2022-few-shot-self-rationalization-natural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ana Marasovic, Iz Beltagy, Doug Downey, et al.*2022 · 134 citations*
312. [**Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback arXiv:2305.10142**Yao Fu, Hao Peng, Tushar Khot, et al.*2023 · 132 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-improving-language-model-negotiation-self/)
313. [**OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text arXiv:2310.06786**Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, et al.*2023 · 132 citations*](https://md.research.elamur.ai/free/en/papers/paster-2023-openwebmath-open-dataset-high-quality/)
314. [**Progressive-Hint Prompting Improves Reasoning in Large Language Models arXiv:2304.09797**Chuanyang Zheng, Zhengying Liu, Enze Xie, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-progressive-hint-prompting-improves-reasoning/)
315. **[Deductive Verification of Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/ling-2023-deductive-verification-chain-thought-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhan Ling, Yunhao Fang, Xuanlin Li, et al.*2023 · 130 citations*
316. **[OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement](https://md.research.elamur.ai/free/en/papers/zheng-2024-opencodeinterpreter-integrating-code-generation-execution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyu Zheng, Ge Zhang, Tianhao Shen, et al.*2024 · 129 citations*
317. **[Evaluating the Moral Beliefs Encoded in LLMs](https://md.research.elamur.ai/free/en/papers/scherrer-2023-evaluating-moral-beliefs-encoded-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nino Scherrer, Claudia Shi, Amir Feder, et al.*2023 · 129 citations*
318. [**Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning arXiv:2303.15647**Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/lialin-2023-scaling-down-scale-up-guide/)
319. **[Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data](https://md.research.elamur.ai/free/en/papers/shum-2023-automatic-prompt-augmentation-selection-chain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kashun Shum, Shizhe Diao, Tong Zhang*2023 · 128 citations*
320. **[Code4Struct: Code Generation for Few-Shot Event Structure Prediction](https://md.research.elamur.ai/free/en/papers/wang-2023-code4struct-code-generation-few-shot/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingyao Wang, Sha Li, Heng Ji*2023 · 128 citations*
321. [**Emergent autonomous scientific research capabilities of large language models arXiv:2304.05332 · published as "Autonomous chemical research with large language models", Nature (2023), doi:10.1038/s41586-023-06792-0**Daniil A. Boiko, Robert MacKnight, Gabe Gomes*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/boiko-2023-emergent-autonomous-scientific-research/)
322. [**Time Travel in LLMs: Tracing Data Contamination in Large Language Models arXiv:2308.08493**Shahriar Golchin, Mihai Surdeanu*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/golchin-2023-time-travel-llms-tracing-data/)
323. **[Scaling Sentence Embeddings with Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-scaling-sentence-embeddings-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ting Jiang, Shaohan Huang, Zhongzhi Luan, et al.*2024 · 127 citations*
324. [**LEVER: Learning to Verify Language-to-Code Generation with Execution arXiv:2302.08468**Ansong Ni, Srini Iyer, Dragomir Radev, et al.*2023 · 126 citations*](https://md.research.elamur.ai/free/en/papers/ni-2023-lever-learning-verify-language-code/)
325. [**Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models arXiv:2310.06117**Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, et al.*2023 · 126 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-take-step-back-evoking-reasoning/)
326. [**PEER: A Collaborative Language Model arXiv:2208.11663**Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, et al.*2022 · 126 citations*](https://md.research.elamur.ai/free/en/papers/schick-2022-peer-collaborative-language-model/)
327. [**Generative Judge for Evaluating Alignment arXiv:2310.05470**Junlong Li, Shichao Sun, Weizhe Yuan, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-generative-judge-evaluating-alignment/)
328. [**H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models arXiv:2306.14048**Zhenyu Zhang, Ying Sheng, Tianyi Zhou, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-h-2-o-heavy-hitter/)
329. [**Large Language Model Alignment: A Survey arXiv:2309.15025**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
330. **[Machine Learning for Ancient Languages: A Survey](https://md.research.elamur.ai/free/en/papers/sommerschield-2023-machine-learning-ancient-languages-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Thea Sommerschield, Yannis Assael, John Pavlopoulos, et al.*2023 · 124 citations*
331. **[Unlearn What You Want to Forget: Efficient Unlearning for LLMs](https://md.research.elamur.ai/free/en/papers/chen-2023-unlearn-what-you-want-forget/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiaao Chen, Diyi Yang*2023 · 124 citations*
332. **[Emergent and Predictable Memorization in Large Language Models](https://md.research.elamur.ai/free/en/papers/biderman-2023-emergent-predictable-memorization-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Stella Biderman, USVSN Sai Prashanth, Lintang Sutawika, et al.*2023 · 123 citations*
333. [**Finding Neurons in a Haystack: Case Studies with Sparse Probing arXiv:2305.01610**Wes Gurnee, Neel Nanda, Matthew Pauly, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/gurnee-2023-finding-neurons-haystack-case-studies/)
334. [**Large Language Models as Tool Makers arXiv:2305.17126**Tianle Cai, Xuezhi Wang, Tengyu Ma, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/cai-2023-large-language-models-tool-makers/)
335. **[LEXTREME: A Multi-Lingual and Multi-Task Benchmark for the Legal Domain](https://md.research.elamur.ai/free/en/papers/niklaus-2023-lextreme-multi-lingual-multi-task/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joel Niklaus, Veton Matoshi, Pooja Rani, et al.*2023 · 123 citations*
336. [**LongNet: Scaling Transformers to 1,000,000,000 Tokens arXiv:2307.02486**Jiayu Ding, Shuming Ma, Li Dong, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/ding-2023-longnet-scaling-transformers-1-000/)
337. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
338. [**Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models arXiv:2408.00724**Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-inference-scaling-laws-empirical-analysis/)
339. **[Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across Languages](https://md.research.elamur.ai/free/en/papers/qin-2023-cross-lingual-prompting-improving-zero/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Libo Qin, Qiguang Chen, Fuxuan Wei, et al.*2023 · 122 citations*
340. **[DePlot: One-shot visual language reasoning by plot-to-table translation](https://md.research.elamur.ai/free/en/papers/liu-2023-deplot-one-shot-visual-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fangyu Liu, Julian Eisenschlos, Francesco Piccinno, et al.*2023 · 122 citations*
341. [**RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems arXiv:2306.03091**Tianyang Liu, Canwen Xu, Julian McAuley*2023 · 122 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-repobench-benchmarking-repository-level-code/)
342. [**The Alignment Problem from a Deep Learning Perspective arXiv:2209.00626**Richard Ngo, Lawrence Chan, Soren Mindermann*2022 · 121 citations*](https://md.research.elamur.ai/free/en/papers/ngo-2022-alignment-problem-deep-learning-perspective/)
343. [**Hallucination of Multimodal Large Language Models: A Survey arXiv:2404.18930**Zechen Bai, Pichao Wang, Tianjun Xiao, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-hallucination-multimodal-large-language-models/)
344. [**Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text arXiv:2401.12070**Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/hans-2024-spotting-llms-binoculars-zero-shot/)
345. [**A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis arXiv:2307.12856**Izzeddin Gur, Hiroki Furuta, Austin Huang, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/gur-2023-real-world-webagent-planning-long/)
346. [**Explanations from Large Language Models Make Small Reasoners Better arXiv:2210.06726**Shiyang Li, Jianshu Chen, Yelong Shen, et al.*2022 · 120 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-explanations-large-language-models-make/)
347. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering arXiv:2306.04136**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/)
348. [**RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation arXiv:2303.12570**Fengji Zhang, Bei Chen, Yue Zhang, et al.*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-repocoder-repository-level-code-completion/)
349. **[MapCoder: Multi-Agent Code Generation for Competitive Problem Solving](https://md.research.elamur.ai/free/en/papers/islam-2024-mapcoder-multi-agent-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Md. Ashraful Islam, Mohammed Eunus Ali, Md Rizwan Parvez*2024 · 118 citations*
350. **[A Length-Extrapolatable Transformer](https://md.research.elamur.ai/free/en/papers/sun-2023-length-extrapolatable-transformer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yutao Sun, Li Dong, Barun Patra, et al.*2023 · 118 citations*
351. **[Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors](https://md.research.elamur.ai/free/en/papers/zhang-2023-aligning-instruction-tasks-unlocks-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Zhang, Bernal Jimenez Gutierrez, Yu Su*2023 · 118 citations*
352. [**Platypus: Quick, Cheap, and Powerful Refinement of LLMs arXiv:2308.07317**Ariel N. Lee, Cole J. Hunter, Nataniel Ruiz*2023 · 117 citations*](https://md.research.elamur.ai/free/en/papers/lee-2023-platypus-quick-cheap-powerful-refinement/)
353. [**Mixture-of-Agents Enhances Large Language Model Capabilities arXiv:2406.04692**Junlin Wang, Jue Wang, Ben Athiwaratkun, et al.*2024 · 116 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-mixture-agents-enhances-large/)
354. [**GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction arXiv:2310.03668**Oscar Sainz, Iker Garcia-Ferrero, Rodrigo Agerri, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/sainz-2023-gollie-annotation-guidelines-improve-zero/)
355. **[Ground-Truth Labels Matter: A Deeper Look into Input-Label Demonstrations](https://md.research.elamur.ai/free/en/papers/yoo-2022-ground-truth-labels-matter-deeper/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al.*2022 · 114 citations*
356. [**ALLaM: Large Language Models for Arabic and English arXiv:2407.15390**M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/bari-2024-allam-large-language-models-arabic/)
357. **[Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical Study](https://md.research.elamur.ai/free/en/papers/chen-2023-exploring-use-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yi Chen, Rui Wang, Haiyun Jiang, et al.*2023 · 113 citations*
358. **[AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehension](https://md.research.elamur.ai/free/en/papers/yang-2024-air-bench-benchmarking-large-audio/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qian Yang, Jin Xu, Wenrui Liu, et al.*2024 · 112 citations*
359. [**Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources arXiv:2305.13269**Xingxuan Li, Ruochen Zhao, Yew Ken Chia, et al.*2023 · 112 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-chain-knowledge-grounding-large-language/)
360. **[Do Androids Laugh at Electric Sheep? Humor “Understanding” Benchmarks from The New Yorker Caption Contest](https://md.research.elamur.ai/free/en/papers/hessel-2023-do-androids-laugh-electric-sheep/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jack Hessel, Ana Marasovic, Jena D. Hwang, et al.*2023 · 112 citations*
361. **[Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?](https://md.research.elamur.ai/free/en/papers/chen-2023-can-pre-trained-vision-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yang Chen, Hexiang Hu, Yi Luan, et al.*2023 · 111 citations*
362. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
363. **[GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP](https://md.research.elamur.ai/free/en/papers/khondaker-2023-gptaraeval-comprehensive-evaluation-chatgpt-arabic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tawkat Islam Khondaker, Abdul Waheed, El Moatez Billah Nagoudi, et al.*2023 · 110 citations*
364. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
365. [**Better Zero-Shot Reasoning with Role-Play Prompting arXiv:2308.07702**Aobo Kong, Shiwan Zhao, Hao Chen, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/kong-2023-better-zero-shot-reasoning-role/)
366. **[CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors](https://md.research.elamur.ai/free/en/papers/li-2023-codeie-large-code-generation-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peng Li, Tianxiang Sun, Qiong Tang, et al.*2023 · 109 citations*
367. [**PaperQA: Retrieval-Augmented Generative Agent for Scientific Research arXiv:2312.07559**Jakub Lála, Odhran O'Donoghue, Aleksandar Shtedritski, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/lala-2023-paperqa-retrieval-augmented-generative/)
368. **[Leveraging GPT-4 for Automatic Translation Post-Editing](https://md.research.elamur.ai/free/en/papers/raunak-2023-leveraging-gpt-4-automatic-translation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Vikas Raunak, Amr Sharaf, Yiren Wang, et al.*2023 · 108 citations*
369. [**Nemotron-4 340B Technical Report arXiv:2406.11704**Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/adler-2024-nemotron-4-340b-technical-report/)
370. **[Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?](https://md.research.elamur.ai/free/en/papers/wang-2024-rethinking-bounds-llm-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qineng Wang, Zihao Wang, Ying Su, et al.*2024 · 107 citations*
371. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 citations*
372. **[Benchmarking Foundation Models with Language-Model-as-an-Examiner](https://md.research.elamur.ai/free/en/papers/bai-2023-benchmarking-foundation-models-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yushi Bai, Jiahao Ying, Yixin Cao, et al.*2023 · 106 citations*
373. **[Complementary Explanations for Effective In-Context Learning](https://md.research.elamur.ai/free/en/papers/ye-2023-complementary-explanations-effective-context-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xi Ye, Srinivasan Iyer, Asli Celikyilmaz, et al.*2023 · 106 citations*
374. **[TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models](https://md.research.elamur.ai/free/en/papers/gekhman-2023-trueteacher-learning-factual-consistency-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zorik Gekhman, Jonathan Herzig, Roee Aharoni, et al.*2023 · 106 citations*
375. [**Inverse Scaling: When Bigger Isn't Better arXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQF**Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.*2023 · 105 citations*](https://md.research.elamur.ai/free/en/papers/mckenzie-2023-inverse-scaling-bigger-isn-t/)
376. [**LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions arXiv:2304.14402**Minghao Wu, Abdul Waheed, Chiyu Zhang, et al.*2023 · 105 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-lamini-lm-diverse-herd-distilled/)
377. **[Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence](https://md.research.elamur.ai/free/en/papers/chen-2022-rich-knowledge-sources-bring-complex/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hung-Ting Chen, Michael Zhang, Eunsol Choi*2022 · 105 citations*
378. [**A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity arXiv:2305.13169**Shayne Longpre, Gregory Yauney, Emily Reif, et al.*2023 · 104 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-pretrainer-s-guide-training-data/)
379. [**PolyLM: An Open Source Polyglot Large Language Model arXiv:2307.06018**Xiangpeng Wei, Haoran Wei, Huan Lin, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-polylm-open-source-polyglot-large/)
380. **[LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models](https://md.research.elamur.ai/free/en/papers/park-2022-lut-gemm-quantized-matrix-multiplication/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Gunho Park, Baeseong Park, Minsub Kim, et al.*2022 · 103 citations*
381. [**FireAct: Toward Language Agent Fine-tuning arXiv:2310.05915**Baian Chen, Chang Shu, Ehsan Shareghi, et al.*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-fireact-toward-language-agent-fine/)
382. [**SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning arXiv:2308.00436**Ning Miao, Yee Whye Teh, Tom Rainforth*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/miao-2023-selfcheck-using-llms-zero-shot/)
383. [**Rationale-Augmented Ensembles in Language Models arXiv:2207.00747**Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.*2022 · 101 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-rationale-augmented-ensembles-language-models/)
384. **[Unsupervised Real-Time Hallucination Detection based on the Internal States of Large Language Models](https://md.research.elamur.ai/free/en/papers/su-2024-unsupervised-real-time-hallucination-detection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weihang Su, Changyue Wang, Qingyao Ai, et al.*2024 · 99 citations*
385. **[Answering Questions by Meta-Reasoning over Multiple Chains of Thought](https://md.research.elamur.ai/free/en/papers/yoran-2023-answering-questions-meta-reasoning-over/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ori Yoran, Tomer Wolfson, Ben Bogin, et al.*2023 · 99 citations*
386. **[FELM: Benchmarking Factuality Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2023-felm-benchmarking-factuality-evaluation-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shiqi Chen, Yiran Zhao, Jinghan Zhang, et al.*2023 · 99 citations*
387. [**Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints arXiv:2212.05055**Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, et al.*2022 · 98 citations*](https://md.research.elamur.ai/free/en/papers/komatsuzaki-2022-sparse-upcycling-training-mixture-experts/)
388. [**Bactrian-X: Multilingual Replicable Instruction-Following Models with Low-Rank Adaptation arXiv:2305.15011**Haonan Li, Fajri Koto, Minghao Wu, et al.*2023 · 96 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-bactrian-x-multilingual-replicable-instruction/)
389. [**Teaching Algorithmic Reasoning via In-context Learning arXiv:2211.09066**Hattie Zhou, Azade Nova, Hugo Larochelle, et al.*2022 · 96 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2022-teaching-algorithmic-reasoning-context-learning/)
390. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
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392. **[WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences](https://md.research.elamur.ai/free/en/papers/liu-2023-webglm-efficient-web-enhanced/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Xiao Liu, Hanyu Lai, Hao Yu, et al.*2023 · 95 citations*
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394. **[Boosting Language Models Reasoning with Chain-of-Knowledge Prompting](https://md.research.elamur.ai/free/en/papers/wang-2024-boosting-language-models-reasoning-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianing Wang, Qiushi Sun, Xiang Li, et al.*2024 · 94 citations*
395. [**InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model arXiv:2401.16420**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 94 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-mastering-free/)
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397. [**Auto-GPT for Online Decision Making: Benchmarks and Additional Opinions arXiv:2306.02224**Hui Yang, Sifu Yue, Yunzhong He*2023 · 94 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-auto-gpt-online-decision-making/)
398. **[LLMs Are Few-Shot In-Context Low-Resource Language Learners](https://md.research.elamur.ai/free/en/papers/cahyawijaya-2024-llms-are-few-shot-context/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Samuel Cahyawijaya, Holy Lovenia, Pascale Fung*2024 · 93 citations*
399. [**Proving Test Set Contamination in Black Box Language Models arXiv:2310.17623**Yonatan Oren, Nicole Meister, Niladri Chatterji, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/oren-2023-proving-test-set-contamination-black/)
400. [**Universal Self-Consistency for Large Language Model Generation arXiv:2311.17311**Xinyun Chen, Renat Aksitov, Uri Alon, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-universal-self-consistency-large-language/)

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