---
title: "Who cites Igor Babuschkin — page 9 — 11,836 citing papers"
description: "11,836 papers of the Elamur Research library cite the works of Igor Babuschkin, found in their bibliographies · page 9 of 27 · 801–900; the…"
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---
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# Who cites Igor Babuschkin

12,380 citations of their works from 11,836 papers of our library (of the 149,439 whose bibliographies we read) · 2,628 with a page here, the most cited first · page 9 of 27 · 801–900 · [← Igor Babuschkin](https://md.research.elamur.ai/free/en/authors/igor-babuschkin/)

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801. [**Better & Faster Large Language Models via Multi-token Prediction arXiv:2404.19737**Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Roziere, et al.*2024 · 90 citations*](https://md.research.elamur.ai/free/en/papers/gloeckle-2024-better-faster-large-language-models/)
802. **[CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark](https://md.research.elamur.ai/free/en/papers/romero-2024-cvqa-culturally-diverse-multilingual-visual/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo, et al.*2024 · 90 citations*
803. [**InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning arXiv:2402.06332**Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.*2024 · 90 citations*](https://md.research.elamur.ai/free/en/papers/ying-2024-internlm-math-open-math-large/)
804. **[Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling](https://md.research.elamur.ai/free/en/papers/maini-2024-rephrasing-web-recipe-compute-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pratyush Maini, Skyler Seto, Richard Bai, et al.*2024 · 90 citations*
805. [**RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation arXiv:2404.00610**Chi-Min Chan, Chunpu Xu, Ruibin Yuan, et al.*2024 · 90 citations*](https://md.research.elamur.ai/free/en/papers/chan-2024-rq-rag-learning-refine-queries/)
806. [**AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation arXiv:2312.13010**Dong Huang, Jie M.Zhang, Michael Luck, et al.*2023 · 90 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-agentcoder-multi-agent-based/)
807. **[Alignment for Honesty](https://md.research.elamur.ai/free/en/papers/yang-2023-alignment-honesty/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuqing Yang, Ethan Chern, Xipeng Qiu, et al.*2023 · 90 citations*
808. [**AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models arXiv:2310.15140**Sicheng Zhu, Ruiyi Zhang, Bang An, et al.*2023 · 90 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-autodan-interpretable-gradient-based-adversarial/)
809. **[Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey](https://md.research.elamur.ai/free/en/papers/kumar-2023-language-generation-models-can-cause/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.*2023 · 90 citations*
810. [**Planning with Large Language Models for Code Generation arXiv:2303.05510**Shun Zhang, Zhenfang Chen, Yikang Shen, et al.*2023 · 90 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-planning-large-language-models-code/)
811. **[Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards](https://md.research.elamur.ai/free/en/papers/rame-2023-rewarded-soups-towards-pareto-optimal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alexandre Rame, Guillaume Couairon, Mustafa Shukor, et al.*2023 · 90 citations*
812. [**Deep Reinforcement Learning at the Edge of the Statistical Precipice arXiv:2108.13264**Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, et al.*2021 · 90 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2021-deep-reinforcement-learning-edge-statistical/)
813. [**Dream 7B: Diffusion Large Language Models arXiv:2508.15487**Jiacheng Ye; Zhihui Xie; Lin Zheng; Jiahui Gao; Zirui Wu; Xin Jiang; Zhenguo Li;, Lingpeng Kong*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-dream-7b-diffusion-large-language/)
814. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
815. [**SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines arXiv:2502.14739**M-A-P Team, Xinrun Du, Yifan Yao, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-supergpqa-scaling-llm-evaluation-across/)
816. **[ADaPT: As-Needed Decomposition and Planning with Language Models](https://md.research.elamur.ai/free/en/papers/prasad-2024-adapt-as-needed-decomposition-planning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Archiki Prasad, Alexander Koller, Mareike Hartmann, et al.*2024 · 89 citations*
817. [**Automated Design of Agentic Systems arXiv:2408.08435**Shengran Hu, Cong Lu, Jeff Clune*2024 · 89 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-automated-design-agentic-systems/)
818. **[LVBench: An Extreme Long Video Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wang-2024-lvbench-extreme-long-video-understanding/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Weihan Wang, Zehai He, Wenyi Hong, et al.*2024 · 89 citations*
819. [**Automatically Auditing Large Language Models via Discrete Optimization arXiv:2303.04381**Erik Jones, Anca Dragan, Aditi Raghunathan, et al.*2023 · 89 citations*](https://md.research.elamur.ai/free/en/papers/jones-2023-automatically-auditing-large-language-models/)
820. **[Evaluation Metrics in the Era of GPT-4: Reliably Evaluating Large Language Models on Sequence to Sequence Tasks](https://md.research.elamur.ai/free/en/papers/sottana-2023-evaluation-metrics-era-gpt-4/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Andrea Sottana, Bin Liang, Kai Zou, et al.*2023 · 89 citations*
821. **[LAMBADA: Backward Chaining for Automated Reasoning in Natural Language](https://md.research.elamur.ai/free/en/papers/kazemi-2023-lambada-backward-chaining-automated-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mehran Kazemi, Najoung Kim, Deepti Bhatia, et al.*2023 · 89 citations*
822. [**Safety Assessment of Chinese Large Language Models arXiv:2304.10436**Hao Sun, Zhexin Zhang, Jiawen Deng, et al.*2023 · 89 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-safety-assessment-chinese-large-language/)
823. **[BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack](https://md.research.elamur.ai/free/en/papers/kuratov-2024-babilong-testing-limits-llms-long/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.*2024 · 88 citations*
824. **[EmoBench: Evaluating the Emotional Intelligence of Large Language Models](https://md.research.elamur.ai/free/en/papers/sabour-2024-emobench-evaluating-emotional-intelligence-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sahand Sabour, Siyang Liu, Zheyuan Zhang, et al.*2024 · 88 citations*
825. [**LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks arXiv:2402.01817 · Proceedings of the 41 st International Conference on Machine Learning, Vienna, Austria. PMLR 235, 2024**Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, et al.*2024 · 88 citations*](https://md.research.elamur.ai/free/en/papers/kambhampati-2024-llms-t-plan-but-help/)
826. [**Massive Activations in Large Language Models arXiv:2402.17762**Mingjie Sun, Xinlei Chen, J. Zico Kolter, et al.*2024 · 88 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-massive-activations-large-language-models/)
827. **[Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2024-not-all-experts-are-equal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xudong Lu, Qi Liu, Yuhui Xu, et al.*2024 · 88 citations*
828. **[Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement](https://md.research.elamur.ai/free/en/papers/xu-2024-pride-prejudice-llm-amplifies-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenda Xu, Guanglei Zhu, Xuandong Zhao, et al.*2024 · 88 citations*
829. **[The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual Contexts](https://md.research.elamur.ai/free/en/papers/shen-2024-language-barrier-dissecting-safety-challenges/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingfeng Shen, Weiting Tan, Sihao Chen, et al.*2024 · 88 citations*
830. [**Landmark Attention: Random-Access Infinite Context Length for Transformers arXiv:2305.16300**Amirkeivan Mohtashami, Martin Jaggi*2023 · 88 citations*](https://md.research.elamur.ai/free/en/papers/mohtashami-2023-landmark-attention-random-access-infinite/)
831. [**MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation arXiv:2208.08227**Federico Cassano, John Gouwar, Daniel Nguyen, et al.*2022 · 88 citations*](https://md.research.elamur.ai/free/en/papers/cassano-2022-multipl-e-scalable-extensible-approach/)
832. **[Reinforcement Learning for Reasoning in Large Language Models with One Training Example](https://md.research.elamur.ai/free/en/papers/wang-2025-reinforcement-learning-reasoning-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yiping Wang, Qing Yang, Zhiyuan Zeng, et al.*2025 · 87 citations*
833. [**Do Membership Inference Attacks Work on Large Language Models? arXiv:2402.07841**Michael Duan, Anshuman Suri, Niloofar Mireshghallah, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/duan-2024-membership-inference-attacks-work-large/)
834. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
835. [**HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs arXiv:2412.18925**Junying Chen, Zhenyang Cai, Ke Ji, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-huatuogpt-o1-towards-medical-complex/)
836. [**Rethinking Interpretability in the Era of Large Language Models arXiv:2402.01761**Chandan Singh, Jeevana Priya Inala, Michel Galley, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-rethinking-interpretability-era-large-language/)
837. **[Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-self-checker-plug-play-modules/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Miaoran Li, Baolin Peng, Michel Galley, et al.*2024 · 87 citations*
838. [**SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal arXiv:2406.14598**Tinghao Xie, Xiangyu Qi, Yi Zeng, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-sorry-bench-systematically-evaluating-large/)
839. **[When Is Multilinguality a Curse? Language Modeling for 250 High- and Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/chang-2024-when-is-multilinguality-curse-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tyler A. Chang, Catherine Arnett, Zhuowen Tu, et al.*2024 · 87 citations*
840. [**A Survey of Large Language Models in Medicine: Progress, Application, and Challenge arXiv:2311.05112**Hongjian Zhou, Fenglin Liu, Boyang Gu, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-survey-large-language-models-medicine/)
841. [**InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition arXiv:2309.15112**Pan Zhang, Xiaoyi Dong, Bin Wang, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-internlm-xcomposer-vision-language/)
842. **[AgentReview: Exploring Peer Review Dynamics with LLM Agents](https://md.research.elamur.ai/free/en/papers/jin-2024-agentreview-exploring-peer-review/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yiqiao Jin, Qinlin Zhao, Yiyang Wang, et al.*2024 · 86 citations*
843. **[Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations](https://md.research.elamur.ai/free/en/papers/chen-2024-breaking-language-barriers-multilingual-mathematical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nuo Chen, Zinan Zheng, Ning Wu, et al.*2024 · 86 citations*
844. **[FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-followbench-multi-level-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxin Jiang, Yufei Wang, Xingshan Zeng, et al.*2024 · 86 citations*
845. **[MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning](https://md.research.elamur.ai/free/en/papers/liu-2024-mmc-advancing-multimodal-chart-understanding/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Fuxiao Liu, Xiaoyang Wang, Wenlin Yao, et al.*2024 · 86 citations*
846. **[Retrieval-Augmented Generation for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/wu-2024-retrieval-augmented-generation-natural-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Shangyu Wu, Ying Xiong, Yufei Cui, et al.*2024 · 86 citations*
847. [**PromptNER: Prompting For Named Entity Recognition arXiv:2305.15444**Dhananjay Ashok, Zachary C. Lipton*2023 · 86 citations*](https://md.research.elamur.ai/free/en/papers/ashok-2023-promptner-prompting-named-entity-recognition/)
848. **[Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?](https://md.research.elamur.ai/free/en/papers/tay-2023-scaling-laws-vs-model-architectures/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2023 · 86 citations*
849. [**Multi-lingual Evaluation of Code Generation Models arXiv:2210.14868**Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, et al.*2022 · 86 citations*](https://md.research.elamur.ai/free/en/papers/athiwaratkun-2022-multi-lingual-evaluation-code-generation/)
850. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
851. **[Evaluating Mathematical Reasoning Beyond Accuracy](https://md.research.elamur.ai/free/en/papers/xia-2024-evaluating-mathematical-reasoning-accuracy/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Shijie Xia, Xuefeng Li, Yixin Liu, et al.*2024 · 85 citations*
852. [**On Prompt-Driven Safeguarding for Large Language Models arXiv:2401.18018**Chujie Zheng, Fan Yin, Hao Zhou, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-prompt-driven-safeguarding-large-language/)
853. [**OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data arXiv:2410.01560**Shubham Toshniwal, Wei Du, Ivan Moshkov, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/toshniwal-2024-openmathinstruct-2-accelerating-ai-math/)
854. **[SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2024-seaeval-multilingual-foundation-models-cross/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Zhengyuan Liu, Xin Huang, et al.*2024 · 85 citations*
855. [**A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily arXiv:2311.08268**Peng Ding, Jun Kuang, Dan Ma, et al.*2023 · 85 citations*](https://md.research.elamur.ai/free/en/papers/ding-2023-wolf-sheep-s-clothing-generalized/)
856. [**BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language Models arXiv:2306.10968**Shaolei Zhang, Qingkai Fang, Zhuocheng Zhang, et al.*2023 · 85 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-bayling-bridging-cross-lingual-alignment/)
857. [**Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving arXiv:2502.07640**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 84 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-frontier-model-open/)
858. **[Simulating Classroom Education with LLM-Empowered Agents](https://md.research.elamur.ai/free/en/papers/zhang-2025-simulating-classroom-education-llm-empowered/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zheyuan Zhang, Daniel Zhang-Li, Jifan Yu, et al.*2025 · 84 citations*
859. **[Detoxifying Large Language Models via Knowledge Editing](https://md.research.elamur.ai/free/en/papers/wang-2024-detoxifying-large-language-models-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengru Wang, Ningyu Zhang, Ziwen Xu, et al.*2024 · 84 citations*
860. **[Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*
861. [**Formalizing and Benchmarking Prompt Injection Attacks and Defenses arXiv:2310.12815**Yupei Liu, Yuqi Jia, Runpeng Geng, et al.*2023 · 84 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-formalizing-benchmarking-prompt-injection-attacks/)
862. [**ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing arXiv:2306.00622**Ryan Liu, Nihar B. Shah*2023 · 84 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-reviewergpt-exploratory-study-using/)
863. [**AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model arXiv:2208.01448**Saleh Soltan, Shankar Ananthakrishnan, Jack FitzGerald, et al.*2022 · 84 citations*](https://md.research.elamur.ai/free/en/papers/soltan-2022-alexatm-20b-few-shot-learning/)
864. **[PKU-SafeRLHF: Towards Multi-Level Safety Alignment for LLMs with Human Preference](https://md.research.elamur.ai/free/en/papers/ji-2025-pku-saferlhf-multi-level-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaming Ji, Donghai Hong, Borong Zhang, et al.*2025 · 83 citations*
865. **[Improving Alignment and Robustness with Circuit Breakers](https://md.research.elamur.ai/free/en/papers/zou-2024-improving-alignment-robustness-circuit-breakers/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Andy Zou, Long Phan, Justin Wang, et al.*2024 · 83 citations*
866. **[Large Language Model Instruction Following: A Survey of Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/lou-2024-large-language-model-instruction-following/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Renze Lou, Kai Zhang, Wenpeng Yin*2024 · 83 citations*
867. [**The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions arXiv:2404.13208**Eric Wallace, Kai Xiao, Reimar Leike, et al.*2024 · 83 citations*](https://md.research.elamur.ai/free/en/papers/wallace-2024-instruction-hierarchy-training-llms-prioritize/)
868. [**Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model arXiv:2408.11039**Chunting Zhou, Lili Yu, Arun Babu, et al.*2024 · 83 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-transfusion-predict-next-token-diffuse/)
869. [**PRD: Peer Rank and Discussion Improve Large Language Model based Evaluations arXiv:2307.02762**Ruosen Li, Teerth Patel, Xinya Du*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-prd-peer-rank-discussion-improve/)
870. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
871. **[HalluLens: LLM Hallucination Benchmark](https://md.research.elamur.ai/free/en/papers/bang-2025-hallulens-llm-hallucination-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yejin Bang, Ziwei Ji, Alan Schelten, et al.*2025 · 82 citations*
872. [**AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents arXiv:2405.14573**Christopher Rawles, Sarah Clinckemaillie, Yifan Chang, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/rawles-2024-androidworld-dynamic-benchmarking-environment-autonomous/)
873. [**HelpSteer2: Open-source dataset for training top-performing reward models arXiv:2406.08673**Zhilin Wang, Yi Dong, Olivier Delalleau, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-helpsteer2-open-source-dataset-training/)
874. [**Is Self-Repair a Silver Bullet for Code Generation? arXiv:2306.09896**Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/olausson-2024-self-repair-silver-bullet-code/)
875. **[MART: Improving LLM Safety with Multi-round Automatic Red-Teaming](https://md.research.elamur.ai/free/en/papers/ge-2024-mart-improving-llm-safety-multi/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Suyu Ge, Chunting Zhou, Rui Hou, et al.*2024 · 82 citations*
876. [**Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive arXiv:2402.13228**Arka Pal, Deep Karkhanis, Samuel Dooley, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/pal-2024-smaug-fixing-failure-modes-preference/)
877. [**Does Writing with Language Models Reduce Content Diversity? arXiv:2309.05196**Vishakh Padmakumar, He He*2023 · 82 citations*](https://md.research.elamur.ai/free/en/papers/padmakumar-2023-writing-language-models-reduce-content/)
878. **[Style Over Substance: Evaluation Biases for Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2025-style-over-substance-evaluation-biases/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Minghao Wu, Alham Fikri Aji*2025 · 81 citations*
879. [**DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving arXiv:2407.13690**Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.*2024 · 81 citations*](https://md.research.elamur.ai/free/en/papers/tong-2024-dart-math-difficulty-aware-rejection/)
880. **[You Only Look at Screens: Multimodal Chain-of-Action Agents](https://md.research.elamur.ai/free/en/papers/zhang-2024-you-only-look-screens-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuosheng Zhang, Aston Zhang*2024 · 81 citations*
881. [**Analyzing the Performance of GPT-3.5 and GPT-4 in Grammatical Error Correction arXiv:2303.14342**Steven Coyne, Keisuke Sakaguchi, Diana Galvan-Sosa, et al.*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/coyne-2023-analyzing-performance-gpt-3-5/)
882. [**Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models arXiv:2307.14539**Erfan Shayegani, Yue Dong, Nael Abu-Ghazaleh*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-jailbreak-pieces-compositional-adversarial-attacks/)
883. **[Large Language Models Meet Harry Potter: A Dataset for Aligning Dialogue Agents with Characters](https://md.research.elamur.ai/free/en/papers/chen-2023-large-language-models-meet-harry/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nuo Chen, Yan Wang, Haiyun Jiang, et al.*2023 · 81 citations*
884. [**MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use arXiv:2310.03128**Yue Huang, Jiawen Shi, Yuan Li, et al.*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-metatool-benchmark-large-language-models/)
885. **[AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning](https://md.research.elamur.ai/free/en/papers/fu-2025-areal-large-scale-asynchronous-reinforcement/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wei Fu, Jiaxuan Gao, Xujie Shen, et al.*2025 · 80 citations*
886. **[AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents](https://md.research.elamur.ai/free/en/papers/trivedi-2024-appworld-controllable-world-apps-people/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Harsh Trivedi, Tushar Khot, Mareike Hartmann, et al.*2024 · 80 citations*
887. **[Lean Workbook: A large-scale Lean problem set formalized from natural language math problems](https://md.research.elamur.ai/free/en/papers/ying-2024-lean-workbook-large-scale-lean/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Huaiyuan Ying, Zijian Wu, Yihan Geng, et al.*2024 · 80 citations*
888. **[Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing](https://md.research.elamur.ai/free/en/papers/tian-2024-toward-self-improvement-llms-imagination/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ye Tian, Baolin Peng, Linfeng Song, et al.*2024 · 80 citations*
889. [**S-LoRA: Serving Thousands of Concurrent LoRA Adapters MLSys 2024**Ying Sheng, Shiyi Cao, Dacheng Li, et al.*2023 · 80 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2023-s-lora-serving-thousands-concurrent/)
890. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/)
891. **[AutoRE: Document-Level Relation Extraction with Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2024-autore-document-level-relation-extraction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lilong Xue, Dan Zhang, Yuxiao Dong, et al.*2024 · 79 citations*
892. [**Common 7B Language Models Already Possess Strong Math Capabilities arXiv:2403.04706**Chen Li, Weiqi Wang, Jingcheng Hu, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-common-7b-language-models-already/)
893. **[Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/paul-2024-making-reasoning-matter-measuring-improving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Debjit Paul, Robert West, Antoine Bosselut, et al.*2024 · 79 citations*
894. [**Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities arXiv:2408.07666**Enneng Yang, Li Shen, Guibing Guo, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-model-merging-llms-mllms-methods/)
895. [**Tuning Language Models by Proxy arXiv:2401.08565**Alisa Liu, Xiaochuang Han, Yizhong Wang, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-tuning-language-models-proxy/)
896. [**LEGO-Prover: Neural Theorem Proving with Growing Libraries arXiv:2310.00656**Haiming Wang, Huajian Xin, Chuanyang Zheng, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-lego-prover-neural-theorem-proving/)
897. [**Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers arXiv:2205.10893**Albert Q. Jiang, Wenda Li, Szymon Tworkowski, et al.*2022 · 79 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-thor-wielding-hammers-integrate-language/)
898. **[Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps](https://md.research.elamur.ai/free/en/papers/chuang-2024-lookback-lens-detecting-mitigating-contextual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yung-Sung Chuang, Linlu Qiu, Cheng-Yu Hsieh, et al.*2024 · 78 citations*
899. [**Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs arXiv:2308.13387**Yuxia Wang, Haonan Li, Xudong Han, et al.*2023 · 78 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-answer-dataset-evaluating-safeguards-llms/)
900. **[AudioBench: A Universal Benchmark for Audio Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-audiobench-universal-benchmark-audio-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Xunlong Zou, Geyu Lin, et al.*2025 · 77 citations*

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