---
title: "Who cites Alan Schelten — page 7 — 13,386 citing papers"
description: "13,386 papers of the Elamur Research library cite the works of Alan Schelten, found in their bibliographies · page 7 of 29 · 601–700; the most…"
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---
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# Who cites Alan Schelten

14,809 citations of their works from 13,386 papers of our library (of the 149,439 whose bibliographies we read) · 2,850 with a page here, the most cited first · page 7 of 29 · 601–700 · [← Alan Schelten](https://md.research.elamur.ai/free/en/authors/alan-schelten/)

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601. **[Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions](https://md.research.elamur.ai/free/en/papers/chen-2025-benchmarking-large-language-models-answering/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hanjie Chen, Zhouxiang Fang, Yash Singla, et al.*2025 · 75 citations*
602. **[MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation](https://md.research.elamur.ai/free/en/papers/xuan-2025-mmlu-prox-multilingual-benchmark-advanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Xuan, Rui Yang, Heli Qi, et al.*2025 · 75 citations*
603. **[Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training](https://md.research.elamur.ai/free/en/papers/fang-2024-enhancing-noise-robustness-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feiteng Fang, Yuelin Bai, Shiwen Ni, et al.*2024 · 75 citations*
604. [**Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers arXiv:2404.04925**Libo Qin, Qiguang Chen, Yuhang Zhou, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-multilingual-large-language-model-survey/)
605. [**PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities**Settaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/sravanthi-2024-pub-pragmatics-understanding-benchmark-assessing/)
606. **[Self-Contrast: Better Reflection Through Inconsistent Solving Perspectives](https://md.research.elamur.ai/free/en/papers/zhang-2024-self-contrast-better-reflection-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqi Zhang, Yongliang Shen, Linjuan Wu, et al.*2024 · 75 citations*
607. **[Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions](https://md.research.elamur.ai/free/en/papers/masoud-2025-cultural-alignment-large-language-models/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Reem I. Masoud, Ziquan Liu, Martin Ferianc, et al.*2025 · 74 citations*
608. [**INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge arXiv:2411.19799**Angelika Romanou, Negar Foroutan, Anna Sotnikova, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/romanou-2024-include-evaluating-multilingual-language-understanding/)
609. **[MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-mediq-question-asking-llms-benchmark/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, et al.*2024 · 74 citations*
610. [**QuRating: Selecting High-Quality Data for Training Language Models arXiv:2402.09739**Alexander Wettig, Aatmik Gupta, Saumya Malik, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/wettig-2024-qurating-selecting-high-quality-data/)
611. **[ReFT: Representation Finetuning for Language Models](https://md.research.elamur.ai/free/en/papers/wu-2024-reft-representation-finetuning-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhengxuan Wu, Aryaman Arora, Zheng Wang, et al.*2024 · 74 citations*
612. **[SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration](https://md.research.elamur.ai/free/en/papers/zhang-2024-sageattention-accurate-8-bit-attention/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Jintao Zhang, Jia Wei, Haofeng Huang, et al.*2024 · 74 citations*
613. [**When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards arXiv:2402.01781**Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/alzahrani-2024-benchmarks-targets-revealing-sensitivity-large/)
614. **[MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning](https://md.research.elamur.ai/free/en/papers/sprague-2023-musr-testing-limits-chain-thought/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Zayne Sprague, Xi Ye, Kaj Bostrom, et al.*2023 · 74 citations*
615. [**Benchmarking Benchmark Leakage in Large Language Models arXiv:2404.18824**Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/)
616. [**Repetition Improves Language Model Embeddings arXiv:2402.15449**Jacob Mitchell Springer, Suhas Kotha, Daniel Fried, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/springer-2024-repetition-improves-language-model-embeddings/)
617. **[WebThinker: Empowering Large Reasoning Models with Deep Research Capability](https://md.research.elamur.ai/free/en/papers/li-2025-webthinker-empowering-large-reasoning-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoxi Li, Jiajie Jin, Guanting Dong, et al.*2025 · 72 citations*
618. **[WebWalker: Benchmarking LLMs in Web Traversal](https://md.research.elamur.ai/free/en/papers/wu-2025-webwalker-benchmarking-llms-web-traversal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jialong Wu, Wenbiao Yin, Yong Jiang, et al.*2025 · 72 citations*
619. [**A Primer on the Inner Workings of Transformer-based Language Models arXiv:2405.00208**Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ferrando-2024-primer-inner-workings-transformer-based/)
620. **[Black-Box Prompt Optimization: Aligning Large Language Models without Model Training](https://md.research.elamur.ai/free/en/papers/cheng-2024-black-box-prompt-optimization-aligning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiale Cheng, Xiao Liu, Kehan Zheng, et al.*2024 · 72 citations*
621. **[HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM](https://md.research.elamur.ai/free/en/papers/wang-2024-helpsteer-multi-attribute-helpfulness-dataset/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zhilin Wang, Yi Dong, Jiaqi Zeng, et al.*2024 · 72 citations*
622. [**Secrets of RLHF in Large Language Models Part II: Reward Modeling arXiv:2401.06080**Binghai Wang, Rui Zheng, Lu Chen, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-secrets-rlhf-large-language-models/)
623. **[Towards Safer Large Language Models through Machine Unlearning](https://md.research.elamur.ai/free/en/papers/liu-2024-safer-large-language-models-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, et al.*2024 · 72 citations*
624. [**Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation arXiv:2307.15337**Xuefei Ning, Zinan Lin, Zixuan Zhou, et al.*2023 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ning-2023-skeleton-thought-prompting-llms-efficient/)
625. [**The Unreasonable Ineffectiveness of the Deeper Layers arXiv:2403.17887**Andrey Gromov, Kushal Tirumala, Hassan Shapourian, et al.*2024 · 71 citations*](https://md.research.elamur.ai/free/en/papers/gromov-2024-unreasonable-ineffectiveness-deeper-layers/)
626. **[Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks](https://md.research.elamur.ai/free/en/papers/kang-2023-knowledge-augmented-reasoning-distillation-small/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Minki Kang, Seanie Lee, Jinheon Baek, et al.*2023 · 71 citations*
627. **[IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models](https://md.research.elamur.ai/free/en/papers/adelani-2025-irokobench-new-benchmark-african-languages/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**David Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime, et al.*2025 · 70 citations*
628. **[Aligning Large and Small Language Models via Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/ranaldi-2024-aligning-large-small-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Leonardo Ranaldi, Andre Freitas*2024 · 70 citations*
629. **[MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark](https://md.research.elamur.ai/free/en/papers/liu-2024-mathbench-evaluating-theory-application-proficiency/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongwei Liu, Zilong Zheng, Yuxuan Qiao, et al.*2024 · 70 citations*
630. **[Tug-of-War between Knowledge: Exploring and Resolving Knowledge Conflicts in Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/jin-2024-tug-war-between-knowledge-exploring/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zhuoran Jin, Pengfei Cao, Yubo Chen, et al.*2024 · 70 citations*
631. **[Recent Advances in Speech Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/cui-2025-recent-advances-speech-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqian Cui, Dianzhi Yu, Xiaoqi Jiao, et al.*2025 · 69 citations*
632. **[Aligner: Efficient Alignment by Learning to Correct](https://md.research.elamur.ai/free/en/papers/ji-2024-aligner-efficient-alignment-learning-correct/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaming Ji, Boyuan Chen, Hantao Lou, et al.*2024 · 69 citations*
633. **[Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2024-self-alignment-factuality-mitigating-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoying Zhang, Baolin Peng, Ye Tian, et al.*2024 · 69 citations*
634. [**CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation arXiv:2311.18702**Pei Ke, Bosi Wen, Zhuoer Feng, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/ke-2023-critiquellm-informative-critique-generation/)
635. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.*2026 · 68 citations*
636. **[Learning to Reason under Off-Policy Guidance](https://md.research.elamur.ai/free/en/papers/yan-2025-learning-reason-under-off-policy/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jianhao Yan, Yafu Li, Zican Hu, et al.*2025 · 68 citations*
637. **[A Thorough Examination of Decoding Methods in the Era of LLMs](https://md.research.elamur.ai/free/en/papers/shi-2024-thorough-examination-decoding-methods-era/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chufan Shi, Haoran Yang, Deng Cai, et al.*2024 · 68 citations*
638. [**Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents arXiv:2408.07199**Pranav Putta, Edmund Mills, Naman Garg, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/putta-2024-agent-q-advanced-reasoning-learning/)
639. **[Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards](https://md.research.elamur.ai/free/en/papers/wang-2024-arithmetic-control-llms-diverse-user/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoxiang Wang, Yong Lin, Wei Xiong, et al.*2024 · 68 citations*
640. **[KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction](https://md.research.elamur.ai/free/en/papers/li-2024-knowcoder-coding-structured-knowledge-into/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zixuan Li, Yutao Zeng, Yuxin Zuo, et al.*2024 · 68 citations*
641. [**MagicPIG: LSH Sampling for Efficient LLM Generation arXiv:2410.16179**Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/)
642. **[Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration](https://md.research.elamur.ai/free/en/papers/feng-2024-modular-pluralism-pluralistic-alignment-multi/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shangbin Feng, Taylor Sorensen, Yuhan Liu, et al.*2024 · 68 citations*
643. **[TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks](https://md.research.elamur.ai/free/en/papers/xu-2024-theagentcompany-benchmarking-llm-agents/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Frank F. Xu, Yufan Song, Boxuan Li, et al.*2024 · 68 citations*
644. [**Branch-Solve-Merge Improves Large Language Model Evaluation and Generation arXiv:2310.15123**Swarnadeep Saha, Omer Levy, Asli Celikyilmaz, et al.*2023 · 68 citations*](https://md.research.elamur.ai/free/en/papers/saha-2023-branch-solve-merge-improves-large/)
645. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
646. [**An Empirical Study of Mamba-based Language Models arXiv:2406.07887**Roger Waleffe, Wonmin Byeon, Duncan Riach, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/waleffe-2024-empirical-study-mamba-based-language/)
647. **[Are Large Language Models Capable of Generating Human-Level Narratives?](https://md.research.elamur.ai/free/en/papers/tian-2024-are-large-language-models-capable/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yufei Tian, Tenghao Huang, Miri Liu, et al.*2024 · 67 citations*
648. **[Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2024-buffer-thoughts-thought-augmented-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ling Yang, Zhaochen Yu, Tianjun Zhang, et al.*2024 · 67 citations*
649. [**FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion arXiv:2406.06858**Li-Wen Chang, Wenlei Bao, Qi Hou, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/chang-2024-flux-fast-software-based-communication/)
650. [**MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark arXiv:2410.19168**S Sakshi, Utkarsh Tyagi, Sonal Kumar, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/sakshi-2024-mmau-massive-multi-task-audio/)
651. **[Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue](https://md.research.elamur.ai/free/en/papers/gu-2024-model-editing-harms-general-abilities/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jia-Chen Gu, Hao-Xiang Xu, Jun-Yu Ma, et al.*2024 · 67 citations*
652. **[MT-Eval: A Multi-Turn Capabilities Evaluation Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/kwan-2024-mt-eval-multi-turn-capabilities/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wai-Chung Kwan, Xingshan Zeng, Yuxin Jiang, et al.*2024 · 67 citations*
653. **[OffsetBias: Leveraging Debiased Data for Tuning Evaluators](https://md.research.elamur.ai/free/en/papers/park-2024-offsetbias-leveraging-debiased-data-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junsoo Park, Seungyeon Jwa, Ren Meiying, et al.*2024 · 67 citations*
654. **[On Context Utilization in Summarization with Large Language Models](https://md.research.elamur.ai/free/en/papers/ravaut-2024-context-utilization-summarization-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mathieu Ravaut, Aixin Sun, Nancy Chen, et al.*2024 · 67 citations*
655. [**AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation arXiv:2311.07397**Junyang Wang, Yuhang Wang, Guohai Xu, et al.*2023 · 67 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-amber-llm-free-multi-dimensional/)
656. [**Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications arXiv:2402.05162**Boyi Wei, Kaixuan Huang, Yangsibo Huang, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/wei-2024-assessing-brittleness-safety-alignment-pruning/)
657. **[C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness](https://md.research.elamur.ai/free/en/papers/kang-2024-c3ot-generating-shorter-chain-thought/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yu Kang, Xianghui Sun, Liangyu Chen, et al.*2024 · 66 citations*
658. [**JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks arXiv:2404.03027**Weidi Luo, Siyuan Ma, Xiaogeng Liu, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-jailbreakv-benchmark-assessing-robustness-multimodal/)
659. **[Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models](https://md.research.elamur.ai/free/en/papers/amayuelas-2024-knowledge-knowledge-exploring-known-unknowns/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alfonso Amayuelas, Kyle Wong, Liangming Pan, et al.*2024 · 66 citations*
660. [**Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models arXiv:2311.08692**Keming Lu, Hongyi Yuan, Runji Lin, et al.*2023 · 66 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-routing-expert-efficient-reward-guided/)
661. **[MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/chang-2025-main-rag-multi-agent-filtering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chia-Yuan Chang, Zhimeng Jiang, Vineeth Rakesh, et al.*2025 · 65 citations*
662. **[Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset](https://md.research.elamur.ai/free/en/papers/su-2025-nemotron-cc-transforming-common-crawl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dan Su, Kezhi Kong, Ying Lin, et al.*2025 · 65 citations*
663. [**CycleResearcher: Improving Automated Research via Automated Review arXiv:2411.00816**Yixuan Weng, Minjun Zhu, Guangsheng Bao, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/weng-2024-cycleresearcher-improving-automated-research/)
664. **[On the Multilingual Ability of Decoder-based Pre-trained Language Models: Finding and Controlling Language-Specific Neurons](https://md.research.elamur.ai/free/en/papers/kojima-2024-multilingual-ability-decoder-based-pre/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Takeshi Kojima, Itsuki Okimura, Yusuke Iwasawa, et al.*2024 · 65 citations*
665. **[Small LLMs Are Weak Tool Learners: A Multi-LLM Agent](https://md.research.elamur.ai/free/en/papers/shen-2024-small-llms-are-weak-tool/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weizhou Shen, Chenliang Li, Hongzhan Chen, et al.*2024 · 65 citations*
666. [**Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models arXiv:2402.13064**Haoran Li, Qingxiu Dong, Zhengyang Tang, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-synthetic-data-almost-scratch-generalized/)
667. [**We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning? arXiv:2407.01284**Runqi Qiao, Qiuna Tan, Guanting Dong, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2024-math-large-multimodal-model-achieve/)
668. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
669. **[CoT-Valve: Length-Compressible Chain-of-Thought Tuning](https://md.research.elamur.ai/free/en/papers/ma-2025-cot-valve-length-compressible-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyin Ma, Guangnian Wan, Runpeng Yu, et al.*2025 · 64 citations*
670. [**Layer by Layer: Uncovering Hidden Representations in Language Models arXiv:2502.02013**Oscar Skean, Md Rifat Arefin, Dan Zhao, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/skean-2025-layer-layer-uncovering-hidden-representations/)
671. **[Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge](https://md.research.elamur.ai/free/en/papers/wu-2025-meta-rewarding-language-models-self/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianhao Wu, Weizhe Yuan, Olga Golovneva, et al.*2025 · 64 citations*
672. **[SpiRit-LM: Interleaved Spoken and Written Language Model](https://md.research.elamur.ai/free/en/papers/nguyen-2025-spirit-lm-interleaved-spoken-written/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tu Anh Nguyen, Benjamin Muller, Bokai Yu, et al.*2025 · 64 citations*
673. **[SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution](https://md.research.elamur.ai/free/en/papers/wei-2025-swe-rl-advancing-llm-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxiang Wei, Olivier Duchenne, Jade Copet, et al.*2025 · 64 citations*
674. **[Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2024-agent-flan-designing-data-methods/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zehui Chen, Kuikun Liu, Qiuchen Wang, et al.*2024 · 64 citations*
675. [**Evaluation of OpenAI o1: Opportunities and Challenges of AGI arXiv:2409.18486**Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.*2024 · 64 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-evaluation-openai-o1-opportunities-challenges/)
676. **[MARIO: MAth Reasoning with code Interpreter Output - A Reproducible Pipeline](https://md.research.elamur.ai/free/en/papers/liao-2024-mario-math-reasoning-code-interpreter/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Minpeng Liao, Chengxi Li, Wei Luo, et al.*2024 · 64 citations*
677. [**Learning From Mistakes Makes LLM Better Reasoner arXiv:2310.20689**Shengnan An, Zexiong Ma, Zeqi Lin, et al.*2023 · 64 citations*](https://md.research.elamur.ai/free/en/papers/an-2023-learning-mistakes-makes-llm-better/)
678. **[Leveraging Large Language Models for NLG Evaluation: Advances and Challenges](https://md.research.elamur.ai/free/en/papers/li-2024-leveraging-large-language-models-nlg/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Li, Xiaohan Xu, Tao Shen, et al.*2024 · 63 citations*
679. **[Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning](https://md.research.elamur.ai/free/en/papers/yang-2024-self-distillation-bridges-distribution-gap/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaorui Yang, Tianyu Pang, Haozhe Feng, et al.*2024 · 63 citations*
680. [**VinePPO: Refining Credit Assignment in RL Training of LLMs arXiv:2410.01679**Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, et al.*2024 · 63 citations*](https://md.research.elamur.ai/free/en/papers/kazemnejad-2024-vineppo-refining-credit-assignment-rl/)
681. [**Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens arXiv:2401.17377**Jiacheng Liu, Sewon Min, Luke Zettlemoyer, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-infini-gram-scaling-unbounded-n/)
682. [**Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding arXiv:2401.12954**Mirac Suzgun, Adam Tauman Kalai*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/suzgun-2024-meta-prompting-enhancing-language-models/)
683. **[Multimodal Table Understanding](https://md.research.elamur.ai/free/en/papers/zheng-2024-multimodal-table-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingyu Zheng, Xinwei Feng, Qingyi Si, et al.*2024 · 62 citations*
684. [**OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs arXiv:2411.14199**Akari Asai, Jacqueline He, Rulin Shao, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/asai-2024-openscholar-synthesizing-scientific-literature/)
685. **[ToMBench: Benchmarking Theory of Mind in Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2024-tombench-benchmarking-theory-mind-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhuang Chen, Jincenzi Wu, Jinfeng Zhou, et al.*2024 · 62 citations*
686. [**OpenAgents: An Open Platform for Language Agents in the Wild arXiv:2310.10634**Tianbao Xie, Fan Zhou, Zhoujun Cheng, et al.*2023 · 62 citations*](https://md.research.elamur.ai/free/en/papers/xie-2023-openagents-open-platform-language-agents/)
687. [**Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves arXiv:2311.04205**Yihe Deng, Weitong Zhang, Zixiang Chen, et al.*2023 · 62 citations*](https://md.research.elamur.ai/free/en/papers/deng-2023-rephrase-respond-let-large-language/)
688. **[Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-is-translation-all-you-need/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chaoqun Liu, Wenxuan Zhang, Yiran Zhao, et al.*2025 · 61 citations*
689. **[Small Models Struggle to Learn from Strong Reasoners](https://md.research.elamur.ai/free/en/papers/li-2025-small-models-struggle-learn-strong/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuetai Li, Xiang Yue, Zhangchen Xu, et al.*2025 · 61 citations*
690. **[One-Shot Learning as Instruction Data Prospector for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-one-shot-learning-as-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunshui Li, Binyuan Hui, Xiaobo Xia, et al.*2024 · 61 citations*
691. [**Teaching Large Language Models to Reason with Reinforcement Learning arXiv:2403.04642**Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-teaching-large-language-models-reason/)
692. [**Tree Search for Language Model Agents arXiv:2407.01476**Jing Yu Koh, Stephen McAleer, Daniel Fried, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/koh-2024-tree-search-language-model-agents/)
693. [**In-context Pretraining: Language Modeling Beyond Document Boundaries arXiv:2310.10638**Weijia Shi, Sewon Min, Maria Lomeli, et al.*2023 · 61 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-context-pretraining-language-modeling-document/)
694. [**Large Language Models Are Not Strong Abstract Reasoners arXiv:2305.19555**Gael Gendron, Qiming Bao, Michael Witbrock, et al.*2023 · 61 citations*](https://md.research.elamur.ai/free/en/papers/gendron-2023-large-language-models-strong-abstract/)
695. [**ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning arXiv:2502.01100**Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, et al.*2025 · 60 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-zebralogic-scaling-limits-llms-logical/)
696. [**Compressed Chain of Thought: Efficient Reasoning Through Dense Representations arXiv:2412.13171**Jeffrey Cheng, Benjamin Van Durme*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-compressed-chain-thought-efficient-reasoning/)
697. [**Making Text Embedders Few-Shot Learners arXiv:2409.15700**Chaofan Li, MingHao Qin, Shitao Xiao, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-making-text-embedders-few-shot/)
698. [**mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models arXiv:2408.04840**Jiabo Ye, Haiyang Xu, Haowei Liu, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/ye-2024-mplug-owl3-towards-long-image/)
699. [**Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning arXiv:2402.00530**Ming Li, Yong Zhang, Shwai He, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-superfiltering-weak-strong-data-filtering/)
700. [**CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Models arXiv:2311.16832**Jinfeng Zhou, Zhuang Chen, Dazhen Wan, et al.*2023 · 60 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-characterglm-customizing-chinese-conversational-ai/)

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