---
title: "Who cites Mark I-Cheng Chen — page 9 — 16,629 citing papers"
description: "16,629 papers of the Elamur Research library cite the works of Mark I-Cheng Chen, found in their bibliographies · page 9 of 33 · 801–900; the…"
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---
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# Who cites Mark I-Cheng Chen

20,687 citations of their works from 16,629 papers of our library (of the 149,439 whose bibliographies we read) · 3,273 with a page here, the most cited first · page 9 of 33 · 801–900 · [← Mark I-Cheng Chen](https://md.research.elamur.ai/free/en/authors/mark-i-cheng-chen/)

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801. **[From Slow Bidirectional to Fast Autoregressive Video Diffusion Models](https://md.research.elamur.ai/free/en/papers/yin-2024-slow-bidirectional-fast-autoregressive-video/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Tianwei Yin, Qiang Zhang, Richard Zhang, et al.*2024 · 148 citations*
802. [**Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge arXiv:2410.02736**Jiayi Ye, Yanbo Wang, Yue Huang, et al.*2024 · 148 citations*](https://md.research.elamur.ai/free/en/papers/ye-2024-justice-prejudice-quantifying-biases-llm/)
803. **[Language Model Behavior: A Comprehensive Survey](https://md.research.elamur.ai/free/en/papers/chang-2024-language-model-behavior-comprehensive-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Tyler A. Chang, Benjamin K. Bergen*2024 · 148 citations*
804. [**Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing arXiv:2406.08464**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 148 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-magpie-alignment-data-synthesis-scratch/)
805. **[Context-faithful Prompting for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2023-context-faithful-prompting-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.*2023 · 148 citations*
806. [**Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature arXiv:2310.05130**Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, et al.*2023 · 148 citations*](https://md.research.elamur.ai/free/en/papers/bao-2023-fast-detectgpt-efficient-zero-shot/)
807. **[Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation](https://md.research.elamur.ai/free/en/papers/mosbach-2023-few-shot-fine-tuning-vs/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Marius Mosbach, Tiago Pimentel, Shauli Ravfogel, et al.*2023 · 148 citations*
808. [**AudioLDM: Text-to-Audio Generation with Latent Diffusion Models arXiv:2301.12503**Haohe Liu, Zehua Chen, Yi Yuan, et al.*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-audioldm-text-audio-generation-latent/)
809. [**Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models arXiv:2312.06585**Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/singh-2023-human-data-scaling-self-training/)
810. **[GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction](https://md.research.elamur.ai/free/en/papers/yang-2023-gpt4tools-teaching-large-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rui Yang, Lin Song, Yanwei Li, et al.*2023 · 147 citations*
811. **[ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings](https://md.research.elamur.ai/free/en/papers/hao-2023-toolkengpt-augmenting-frozen-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shibo Hao, Tianyang Liu, Zhen Wang, et al.*2023 · 147 citations*
812. [**Is GPT-3 a Good Data Annotator? arXiv:2212.10450**Bosheng Ding, Chengwei Qin, Linlin Liu, et al.*2022 · 147 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-gpt-3-good-data-annotator/)
813. [**rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking arXiv:2501.04519**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/)
814. **[Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion](https://md.research.elamur.ai/free/en/papers/huang-2025-self-forcing-bridging-train-test/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xun Huang, Zhengqi Li, Guande He, et al.*2025 · 146 citations*
815. **[Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding](https://md.research.elamur.ai/free/en/papers/xia-2024-unlocking-efficiency-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Heming Xia, Zhe Yang, Qingxiu Dong, et al.*2024 · 146 citations*
816. **[Fact-Checking Complex Claims with Program-Guided Reasoning](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 146 citations*
817. **[SCOTT: Self-Consistent Chain-of-Thought Distillation](https://md.research.elamur.ai/free/en/papers/wang-2023-scott-self-consistent-chain-thought/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peifeng Wang, Zhengyang Wang, Zheng Li, et al.*2023 · 146 citations*
818. **[Unified Demonstration Retriever for In-Context Learning](https://md.research.elamur.ai/free/en/papers/li-2023-unified-demonstration-retriever-context-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaonan Li, Kai Lv, Hang Yan, et al.*2023 · 146 citations*
819. **[How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition](https://md.research.elamur.ai/free/en/papers/dong-2024-how-abilities-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanting Dong, Hongyi Yuan, Keming Lu, et al.*2024 · 145 citations*
820. **[Efficient Methods for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.*2023 · 145 citations*
821. [**Is ChatGPT a Highly Fluent Grammatical Error Correction System? A Comprehensive Evaluation arXiv:2304.01746**Tao Fang, Shu Yang, Kaixin Lan, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/fang-2023-chatgpt-highly-fluent-grammatical-error/)
822. [**JudgeLM: Fine-tuned Large Language Models are Scalable Judges arXiv:2310.17631**Lianghui Zhu, Xinggang Wang, Xinlong Wang*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-judgelm-fine-tuned-large-language/)
823. **[SpotServe: Serving Generative Large Language Models on Preemptible Instances](https://md.research.elamur.ai/free/en/papers/miao-2023-spotserve-serving-generative-large-language/) [ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-architectural-support-for-programming-languages/)**Xupeng Miao, Chunan Shi, Jiangfei Duan, et al.*2023 · 145 citations*
824. **[Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework](https://md.research.elamur.ai/free/en/papers/zhao-2023-verify-edit-knowledge-enhanced-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruochen Zhao, Xingxuan Li, Shafiq Joty, et al.*2023 · 145 citations*
825. **[Dynamic Prefix-Tuning for Generative Template-based Event Extraction](https://md.research.elamur.ai/free/en/papers/liu-2022-dynamic-prefix-tuning-generative-template/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiao Liu, Heyan Huang, Ge Shi, et al.*2022 · 145 citations*
826. **[TopiOCQA: Open-domain Conversational Question Answering with Topic Switching](https://md.research.elamur.ai/free/en/papers/adlakha-2022-topiocqa-open-domain-conversational-question/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vaibhav Adlakha, Shehzaad Dhuliawala, Kaheer Suleman, et al.*2022 · 145 citations*
827. **[Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions](https://md.research.elamur.ai/free/en/papers/chung-2023-increasing-diversity-while-maintaining-accuracy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**John Chung, Ece Kamar, Saleema Amershi*2023 · 144 citations*
828. [**MiniLLM: On-Policy Distillation of Large Language Models arXiv:2306.08543**Yuxian Gu, Li Dong, Furu Wei, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-minillm-policy-distillation-large-language/)
829. [**SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills arXiv 2023**Amey Agrawal, Ashish Panwar, Jayashree Mohan, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2023-sarathi-efficient-llm-inference-piggybacking/)
830. [**Efficient Training of Language Models to Fill in the Middle arXiv:2207.14255**Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/)
831. **[In-Context Learning for Few-Shot Dialogue State Tracking](https://md.research.elamur.ai/free/en/papers/hu-2022-context-learning-few-shot-dialogue/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yushi Hu, Chia-Hsuan Lee, Tianbao Xie, et al.*2022 · 144 citations*
832. [**InternVideo: General Video Foundation Models via Generative and Discriminative Learning arXiv:2212.03191**Yi Wang, Kunchang Li, Yizhuo Li, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-internvideo-general-video-foundation/)
833. **[Iteratively Prompt Pre-trained Language Models for Chain of Thought](https://md.research.elamur.ai/free/en/papers/wang-2022-iteratively-prompt-pre-trained-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Boshi Wang, Xiang Deng, Huan Sun*2022 · 144 citations*
834. [**A Roadmap to Pluralistic Alignment arXiv:2402.05070**Taylor Sorensen, Jared Moore, Jillian Fisher, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/sorensen-2024-roadmap-pluralistic-alignment/)
835. [**A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation arXiv:2307.03987**Neeraj Varshney; Wenlin Yao; Hongming Zhang; Jianshu Chen;, Dong Yu*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/varshney-2023-stitch-time-saves-nine-detecting/)
836. [**Rethinking with Retrieval: Faithful Large Language Model Inference arXiv:2301.00303**Hangfeng He, Hongming Zhang, Dan Roth*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-rethinking-retrieval-faithful-large-language/)
837. [**Understanding the Effects of RLHF on LLM Generalisation and Diversity arXiv:2310.06452**Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/kirk-2023-understanding-effects-rlhf-llm-generalisation/)
838. [**Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention arXiv:2502.11089**Jingyang Yuan, Huazuo Gao, Damai Dai, et al.*2025 · 142 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2025-native-sparse-attention-hardware/)
839. **[Many-Shot In-Context Learning](https://md.research.elamur.ai/free/en/papers/agarwal-2024-many-shot-context-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.*2024 · 142 citations*
840. [**Eureka: Human-Level Reward Design via Coding Large Language Models arXiv:2310.12931**Yecheng Jason Ma, William Liang, Guanzhi Wang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-eureka-human-level-reward-design/)
841. [**Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness arXiv:2304.11633**Bo Li, Gexiang Fang, Yang Yang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-chatgpt-s-information-extraction/)
842. [**ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics arXiv:2302.12433**Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-proofnet-autoformalizing-formally-proving-undergraduate/)
843. **[A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation](https://md.research.elamur.ai/free/en/papers/liu-2022-token-level-reference-free-hallucination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Liu, Yizhe Zhang, Chris Brockett, et al.*2022 · 142 citations*
844. [**Rethinking embedding coupling in pre-trained language models arXiv:2010.12821**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/)
845. [**R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning arXiv:2503.05592**Huatong Song, Jinhao Jiang, Yingqian Min, et al.*2025 · 141 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-r1-searcher-incentivizing-search/)
846. [**LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks arXiv:2406.18403**Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, et al.*2024 · 141 citations*](https://md.research.elamur.ai/free/en/papers/bavaresco-2024-llms-instead-human-judges-large/)
847. **[Diverse Demonstrations Improve In-context Compositional Generalization](https://md.research.elamur.ai/free/en/papers/levy-2023-diverse-demonstrations-improve-context-compositional/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Itay Levy, Ben Bogin, Jonathan Berant*2023 · 141 citations*
848. [**Exploring the Limits of ChatGPT for Query or Aspect-based Text Summarization arXiv:2302.08081**Xianjun Yang, Yan Li, Xinlu Zhang, et al.*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-exploring-limits-chatgpt-query-aspect/)
849. **[Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery](https://md.research.elamur.ai/free/en/papers/wen-2023-hard-prompts-made-easy-gradient/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxin Wen, Neel Jain, John Kirchenbauer, et al.*2023 · 141 citations*
850. [**MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback arXiv:2309.10691**Xingyao Wang, Zihan Wang, Jiateng Liu, et al.*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mint-evaluating-llms-multi-turn/)
851. **[Retrieval-based Language Models and Applications](https://md.research.elamur.ai/free/en/papers/asai-2023-retrieval-based-language-models-applications/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Akari Asai, Sewon Min, Zexuan Zhong, et al.*2023 · 141 citations*
852. [**SLiC-HF: Sequence Likelihood Calibration with Human Feedback arXiv:2305.10425**Yao Zhao, Rishabh Joshi, Tianqi Liu, et al.*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-slic-hf-sequence-likelihood-calibration/)
853. [**CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks arXiv:2105.12655**Ruchir Puri, David S. Kung, Geert Janssen, et al.*2021 · 141 citations*](https://md.research.elamur.ai/free/en/papers/puri-2021-codenet-large-scale-ai-code/)
854. **[Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge Bases](https://md.research.elamur.ai/free/en/papers/cao-2021-knowledgeable-or-educated-guess-revisiting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2021 · 141 citations*
855. **[Do LLMs Exhibit Human-like Response Biases? A Case Study in Survey Design](https://md.research.elamur.ai/free/en/papers/tjuatja-2024-do-llms-exhibit-human-like/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Lindia Tjuatja, Valerie Chen, Tongshuang Wu, et al.*2024 · 140 citations*
856. [**MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering arXiv:2410.07095**Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, et al.*2024 · 140 citations*](https://md.research.elamur.ai/free/en/papers/chan-2024-mle-bench-evaluating-machine/)
857. **[MLVU: Benchmarking Multi-task Long Video Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2024-mlvu-benchmarking-multi-task-long/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Junjie Zhou, Yan Shu, Bo Zhao, et al.*2024 · 140 citations*
858. [**OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework arXiv:2405.11143**Jian Hu, Xibin Wu, Wei Shen, et al.*2024 · 140 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-openrlhf-easy-use-scalable/)
859. [**Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration arXiv:2307.05300**Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, et al.*2023 · 140 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-unleashing-emergent-cognitive-synergy-large/)
860. **[NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics](https://md.research.elamur.ai/free/en/papers/lu-2022-neurologic-esque-decoding-constrained-text/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ximing Lu, Sean Welleck, Peter West, et al.*2022 · 140 citations*
861. **[TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation](https://md.research.elamur.ai/free/en/papers/uchendu-2021-turingbench-benchmark-environment-turing-test/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adaku Uchendu, Zeyu Ma, Thai Le, et al.*2021 · 140 citations*
862. [**Agent Laboratory: Using LLM Agents as Research Assistants arXiv:2501.04227**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 139 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/)
863. [**Exploring Length Generalization in Large Language Models arXiv:2207.04901**Cem Anil, Yuhuai Wu, Anders Andreassen, et al.*2022 · 139 citations*](https://md.research.elamur.ai/free/en/papers/anil-2022-exploring-length-generalization-large-language/)
864. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
865. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models arXiv:2212.08037**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 138 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/)
866. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding arXiv:2412.10302**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)
867. **[DRAGIN: Dynamic Retrieval Augmented Generation based on the Real-time Information Needs of Large Language Models](https://md.research.elamur.ai/free/en/papers/su-2024-dragin-dynamic-retrieval-augmented-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weihang Su, Yichen Tang, Qingyao Ai, et al.*2024 · 137 citations*
868. **[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*
869. [**RAFT: Adapting Language Model to Domain Specific RAG arXiv:2403.10131**Tianjun Zhang, Shishir G. Patil, Naman Jain, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-raft-adapting-language-model-domain/)
870. [**τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains arXiv:2406.12045**Shunyu Yao, Noah Shinn, Pedram Razavi, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-tau-bench-benchmark-tool/)
871. [**Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference arXiv:2310.04378**Simian Luo, Yiqin Tan, Longbo Huang, et al.*2023 · 137 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-latent-consistency-models-synthesizing-high/)
872. [**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/)
873. **[Extracting Latent Steering Vectors from Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/subramani-2022-extracting-latent-steering-vectors-pretrained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nishant Subramani, Nivedita Suresh, Matthew Peters*2022 · 137 citations*
874. **[Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2024-error-analysis-prompting-enables-human/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qingyu Lu, Baopu Qiu, Liang Ding, et al.*2024 · 136 citations*
875. **[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*
876. [**Token-Budget-Aware LLM Reasoning arXiv:2412.18547**Tingxu Han, Zhenting Wang, Chunrong Fang, et al.*2024 · 136 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-token-budget-aware-llm-reasoning/)
877. **[DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models](https://md.research.elamur.ai/free/en/papers/he-2023-diffusionbert-improving-generative-masked-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengfu He, Tianxiang Sun, Qiong Tang, et al.*2023 · 136 citations*
878. [**Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasets arXiv:2106.10328**Irene Solaiman, Christy Dennison OpenAI)*2021 · 136 citations*](https://md.research.elamur.ai/free/en/papers/solaiman-2021-process-adapting-language-models-society/)
879. [**Secrets of RLHF in Large Language Models Part I: PPO arXiv:2307.04964**Rui Zheng, Shihan Dou, Songyang Gao, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-secrets-rlhf-large-language-models/)
880. **[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*
881. **[AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning](https://md.research.elamur.ai/free/en/papers/wang-2022-adamix-mixture-adaptations-parameter-efficient/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee, et al.*2022 · 135 citations*
882. **[UnNatural Language Inference](https://md.research.elamur.ai/free/en/papers/sinha-2021-unnatural-language-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, et al.*2021 · 135 citations*
883. **[Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View](https://md.research.elamur.ai/free/en/papers/zhang-2024-exploring-collaboration-mechanisms-llm-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jintian Zhang, Xin Xu, Ningyu Zhang, et al.*2024 · 134 citations*
884. **[ReFT: Reasoning with Reinforced Fine-Tuning](https://md.research.elamur.ai/free/en/papers/trung-2024-reft-reasoning-reinforced-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luong Trung, Xinbo Zhang, Zhanming Jie, et al.*2024 · 134 citations*
885. [**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/)
886. [**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/)
887. **[RADAR: Robust AI-Text Detection via Adversarial Learning](https://md.research.elamur.ai/free/en/papers/hu-2023-radar-robust-ai-text-detection/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaomeng Hu, Pin-Yu Chen, Tsung-Yi Ho*2023 · 134 citations*
888. [**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/)
889. **[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*
890. **[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*
891. **[EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-2-faster-inference-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 133 citations*
892. [**EuroLLM: Multilingual Language Models for Europe arXiv:2409.16235**Pedro Henrique Martins, Patrick Fernandes, Joao Alves, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/martins-2024-eurollm-multilingual-language-models-europe/)
893. **[Prompting is not a substitute for probability measurements in large language models](https://md.research.elamur.ai/free/en/papers/hu-2023-prompting-is-not-substitute-probability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jennifer Hu, Roger Levy*2023 · 133 citations*
894. **[FLUTE: Figurative Language Understanding through Textual Explanations](https://md.research.elamur.ai/free/en/papers/chakrabarty-2022-flute-figurative-language-understanding-through/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.*2022 · 133 citations*
895. [**Formal Mathematics Statement Curriculum Learning arXiv:2202.01344**Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.*2022 · 133 citations*](https://md.research.elamur.ai/free/en/papers/polu-2022-formal-mathematics-statement-curriculum-learning/)
896. [**Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast arXiv:2211.02556**Kaifeng Bi, Lingxi Xie, Hengheng Zhang, et al.*2022 · 133 citations*](https://md.research.elamur.ai/free/en/papers/bi-2022-pangu-weather-3d-high/)
897. **[Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset](https://md.research.elamur.ai/free/en/papers/henderson-2022-pile-law-learning-responsible-data/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Peter Henderson, Mark S. Krass, Lucia Zheng, et al.*2022 · 133 citations*
898. [**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/)
899. [**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/)
900. **[Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion](https://md.research.elamur.ai/free/en/papers/shuster-2022-language-models-that-seek-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kurt Shuster, Mojtaba Komeili, Leonard Adolphs, et al.*2022 · 132 citations*

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