---
title: "Who cites Gaurav Mishra — page 6 — 7,760 papers of our library"
description: "7,760 papers of the Elamur Research library cite the works of Gaurav Mishra, found in their bibliographies · page 6 of 19 · 501–600; the most…"
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---
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# Who cites Gaurav Mishra

9,492 citations of their works from 7,760 papers of our library (of the 149,439 whose bibliographies we read) · 1,843 with a page here, the most cited first · page 6 of 19 · 501–600 · [← Gaurav Mishra](https://md.research.elamur.ai/free/en/authors/gaurav-mishra/)

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501. [**Long-context LLMs Struggle with Long In-context Learning arXiv:2404.02060**Tianle Li, Ge Zhang, Quy Duc Do, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-long-context-llms-struggle-long/)
502. [**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/)
503. **[Theory of Mind for Multi-Agent Collaboration via Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-theory-mind-multi-agent-collaboration/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Huao Li, Yu Chong, Simon Stepputtis, et al.*2023 · 138 citations*
504. [**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/)
505. **[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*
506. **[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*
507. [**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/)
508. **[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*
509. **[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*
510. [**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/)
511. [**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/)
512. **[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*
513. **[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*
514. [**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/)
515. [**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/)
516. [**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/)
517. **[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*
518. **[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*
519. **[Humans or LLMs as the Judge? A Study on Judgement Bias](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-or-llms-as-judge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 133 citations*
520. **[The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/kirk-2024-prism-alignment-dataset-participatory-representative/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hannah Rose Kirk, Alexander Whitefield, Paul Rottger, et al.*2024 · 133 citations*
521. **[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*
522. **[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*
523. [**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/)
524. [**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/)
525. **[Task-aware Retrieval with Instructions](https://md.research.elamur.ai/free/en/papers/asai-2023-task-aware-retrieval-instructions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Akari Asai, Timo Schick, Patrick Lewis, et al.*2023 · 132 citations*
526. **[ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding](https://md.research.elamur.ai/free/en/papers/shaham-2023-zeroscrolls-zero-shot-benchmark-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Uri Shaham, Maor Ivgi, Avia Efrat, et al.*2023 · 132 citations*
527. **[MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems](https://md.research.elamur.ai/free/en/papers/macina-2023-mathdial-dialogue-tutoring-dataset-rich/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jakub Macina, Nico Daheim, Sankalan Chowdhury, et al.*2023 · 131 citations*
528. [**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/)
529. **[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*
530. **[Natural Language Reasoning, A Survey](https://md.research.elamur.ai/free/en/papers/yu-2023-natural-language-reasoning-survey/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Fei Yu, Hongbo Zhang, Prayag Tiwari, et al.*2023 · 130 citations*
531. **[Faithful Logical Reasoning via Symbolic Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/xu-2024-faithful-logical-reasoning-symbolic-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jundong Xu, Hao Fei, Liangming Pan, et al.*2024 · 129 citations*
532. **[MAGE: Machine-generated Text Detection in the Wild](https://md.research.elamur.ai/free/en/papers/li-2024-mage-machine-generated-text-detection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yafu Li, Qintong Li, Leyang Cui, et al.*2024 · 129 citations*
533. **[Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-multimodal-arxiv-dataset-improving-scientific/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Li, Yuqi Wang, Runxin Xu, et al.*2024 · 129 citations*
534. **[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*
535. **[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*
536. [**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/)
537. **[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*
538. **[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*
539. [**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/)
540. [**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/)
541. [**LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models arXiv:2407.07895**Feng Li, Renrui Zhang, Hao Zhang, et al.*2024 · 127 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-next-interleave-tackling-multi/)
542. **[SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding](https://md.research.elamur.ai/free/en/papers/xu-2024-safedecoding-defending-against-jailbreak-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 127 citations*
543. **[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*
544. [**Fine-tuning Language Models for Factuality arXiv:2311.08401**Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/tian-2023-fine-tuning-language-models-factuality/)
545. [**Chain of Hindsight Aligns Language Models with Feedback arXiv:2302.02676**Hao Liu, Carmelo Sferrazza, Pieter Abbeel*2023 · 126 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-chain-hindsight-aligns-language-models/)
546. [**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/)
547. [**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/)
548. [**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/)
549. [**TravelPlanner: A Benchmark for Real-World Planning with Language Agents arXiv:2402.01622**Jian Xie, Kai Zhang, Jiangjie Chen, et al.*2024 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-travelplanner-benchmark-real-world-planning/)
550. [**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/)
551. [**Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future arXiv:2309.15402**Zheng Chu, Jingchang Chen, Qianglong Chen, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-navigate-through-enigmatic-labyrinth-survey/)
552. **[Can Language Models Solve Graph Problems in Natural Language?](https://md.research.elamur.ai/free/en/papers/wang-2023-language-models-solve-graph-problems/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Heng Wang, Shangbin Feng, Tianxing He, et al.*2023 · 124 citations*
553. [**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/)
554. [**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/)
555. **[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*
556. **[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*
557. **[Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-mini-gemini-mining-potential-multi/) [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-pattern-analysis-and-machine-intelligence/)**Yanwei Li, Yuechen Zhang, Chengyao Wang, et al.*2024 · 123 citations*
558. [**MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark arXiv:2409.02813**Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-mmmu-pro-more-robust-multi/)
559. **[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*
560. [**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/)
561. [**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/)
562. **[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*
563. [**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/)
564. [**OpenThoughts: Data Recipes for Reasoning Models arXiv:2506.04178**Etash Guha, Ryan Marten, Sedrick Keh, et al.*2025 · 122 citations*](https://md.research.elamur.ai/free/en/papers/guha-2025-openthoughts-data-recipes-reasoning-models/)
565. [**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/)
566. [**Quiet-STaR: Language models can teach themselves to think before speaking***2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/al-2024-quiet-star-language-models-teach/)
567. **[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*
568. **[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*
569. [**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/)
570. **[UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning](https://md.research.elamur.ai/free/en/papers/masry-2023-unichart-universal-vision-language-pretrained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ahmed Masry, Parsa Kavehzadeh, Xuan Long Do, et al.*2023 · 121 citations*
571. [**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/)
572. [**Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models arXiv:2501.09686**Fengli Xu, Qianyue Hao, Zefang Zong, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-towards-large-reasoning-models-survey/)
573. **[AlphaMath Almost Zero: Process Supervision without Process](https://md.research.elamur.ai/free/en/papers/chen-2024-alphamath-almost-zero-process-supervision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guoxin Chen, Minpeng Liao, Chengxi Li, et al.*2024 · 120 citations*
574. [**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/)
575. [**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/)
576. [**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/)
577. [**UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition arXiv:2308.03279**Wenxuan Zhou, Sheng Zhang, Yu Gu, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-universalner-targeted-distillation-large-language/)
578. [**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/)
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580. **[CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/wang-2024-charxiv-charting-gaps-realistic-chart/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zirui Wang, Mengzhou Xia, Luxi He, et al.*2024 · 119 citations*
581. [**LLaVA-Video: Video Instruction Tuning With Synthetic Data arXiv:2410.02713**Yuanhan Zhang, Jinming Wu, Wei Li, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-llava-video-video-instruction-tuning/)
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583. [**SaulLM-7B: A pioneering Large Language Model for Law arXiv:2403.03883**Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/colombo-2024-saullm-7b-pioneering-large-language/)
584. [**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/)
585. [**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/)
586. [**Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks arXiv:2404.02151**Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion*2024 · 118 citations*](https://md.research.elamur.ai/free/en/papers/andriushchenko-2024-jailbreaking-leading-safety-aligned-llms/)
587. **[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*
588. [**VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs arXiv:2406.07476**Zesen Cheng, Sicong Leng, Hang Zhang, et al.*2024 · 118 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-videollama-2-advancing-spatial-temporal/)
589. **[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*
590. **[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*
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592. **[The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning](https://md.research.elamur.ai/free/en/papers/kim-2023-cot-collection-improving-zero-shot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Seungone Kim, Se Joo, Doyoung Kim, et al.*2023 · 118 citations*
593. **[Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/shao-2024-visual-cot-advancing-multi-modal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hao Shao, Shengju Qian, Han Xiao, et al.*2024 · 117 citations*
594. [**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/)
595. [**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/)
596. [**Large Language Models Understand and Can be Enhanced by Emotional Stimuli arXiv:2307.11760**Cheng Li, Jindong Wang, Yixuan Zhang, et al.*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-large-language-models-understand-enhanced/)
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598. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 115 citations*
599. [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
600. [**Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2 arXiv:2408.05147**Tom Lieberum, Senthooran Rajamanoharan, Arthur Conmy, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/lieberum-2024-gemma-scope-open-sparse-autoencoders/)

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