---
title: "Who cites Peter Albert — page 7 — 7,085 papers of our library"
description: "7,085 papers of the Elamur Research library cite the works of Peter Albert, found in their bibliographies · page 7 of 16 · 601–700; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/peter-albert/cited-by/page/7/"
---
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# Who cites Peter Albert

7,087 citations of their works from 7,085 papers of our library (of the 149,439 whose bibliographies we read) · 1,512 with a page here, the most cited first · page 7 of 16 · 601–700 · [← Peter Albert](https://md.research.elamur.ai/free/en/authors/peter-albert/)

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601. [**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/)
602. [**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/)
603. **[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*
604. **[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*
605. **[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*
606. [**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/)
607. **[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*
608. [**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/)
609. **[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*
610. **[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*
611. [**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/)
612. [**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/)
613. [**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/)
614. **[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*
615. **[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*
616. [**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/)
617. [**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/)
618. **[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*
619. **[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*
620. **[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*
621. [**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/)
622. [**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/)
623. [**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/)
624. [**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/)
625. [**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/)
626. [**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/)
627. [**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/)
628. [**Data Filtering Networks arXiv:2309.17425**Alex Fang, Albin Madappally Jose, Amit Jain, et al.*2023 · 60 citations*](https://md.research.elamur.ai/free/en/papers/fang-2023-data-filtering-networks/)
629. **[TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties](https://md.research.elamur.ai/free/en/papers/kadaoui-2023-tarjamat-evaluation-bard-chatgpt-machine/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Karima Kadaoui, Samar M. Magdy, Abdul Waheed, et al.*2023 · 60 citations*
630. **[BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models](https://md.research.elamur.ai/free/en/papers/dong-2024-bamboo-comprehensive-benchmark-evaluating-long/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zican Dong, Tianyi Tang, Junyi Li, et al.*2024 · 59 citations*
631. **[Instruction Pre-Training: Language Models are Supervised Multitask Learners](https://md.research.elamur.ai/free/en/papers/cheng-2024-instruction-pre-training-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Daixuan Cheng, Yuxian Gu, Shaohan Huang, et al.*2024 · 59 citations*
632. **[MAPO: Advancing Multilingual Reasoning through Multilingual-Alignment-as-Preference Optimization](https://md.research.elamur.ai/free/en/papers/she-2024-mapo-advancing-multilingual-reasoning-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuaijie She, Wei Zou, Shujian Huang, et al.*2024 · 59 citations*
633. [**Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling arXiv:2406.07522**Liliang Ren, Yang Liu, Yadong Lu, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/ren-2024-samba-simple-hybrid-state-space/)
634. [**Simple linear attention language models balance the recall-throughput tradeoff arXiv:2402.18668**Simran Arora, Sabri Eyuboglu, Michael Zhang, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/arora-2024-simple-linear-attention-language-models/)
635. [**Benchmarking Generation and Evaluation Capabilities of Large Language Models for Instruction Controllable Summarization arXiv:2311.09184**Yixin Liu, Alexander R. Fabbri, Jiawen Chen, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-benchmarking-generation-evaluation-capabilities-large/)
636. [**EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models arXiv:2312.06281**Samuel J. Paech*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/paech-2023-eq-bench-emotional-intelligence-benchmark/)
637. [**Investigating the Catastrophic Forgetting in Multimodal Large Language Models arXiv:2309.10313**Yuexiang Zhai, Shengbang Tong, Xiao Li, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/zhai-2023-investigating-catastrophic-forgetting-multimodal-large/)
638. **[SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs](https://md.research.elamur.ai/free/en/papers/xu-2025-softcot-soft-chain-thought-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yige Xu, Xu Guo, Zhiwei Zeng, et al.*2025 · 58 citations*
639. [**A Practical Review of Mechanistic Interpretability for Transformer-Based Language Models arXiv:2407.02646**Daking Rai, Yilun Zhou, Shi Feng, et al.*2024 · 58 citations*](https://md.research.elamur.ai/free/en/papers/rai-2024-practical-review-mechanistic-interpretability-transformer/)
640. **[ChatQA: Surpassing GPT-4 on Conversational QA and RAG](https://md.research.elamur.ai/free/en/papers/liu-2024-chatqa-surpassing-gpt-4-conversational/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zihan Liu, Wei Ping, Rajarshi Roy, et al.*2024 · 58 citations*
641. [**Free Process Rewards without Process Labels arXiv:2412.01981**Lifan Yuan, Wendi Li, Huayu Chen, et al.*2024 · 58 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2024-free-process-rewards-process-labels/)
642. [**MaLA-500: Massive Language Adaptation of Large Language Models arXiv:2401.13303**Peiqin Lin, Shaoxiong Ji, Jorg Tiedemann, et al.*2024 · 58 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-mala-500-massive-language-adaptation/)
643. **[MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs](https://md.research.elamur.ai/free/en/papers/lu-2024-mathgenie-generating-synthetic-data-question/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zimu Lu, Aojun Zhou, Houxing Ren, et al.*2024 · 58 citations*
644. [**EduChat: A Large-Scale Language Model-based Chatbot System for Intelligent Education arXiv:2308.02773**Yuhao Dan, Zhikai Lei, Yiyang Gu, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/dan-2023-educhat-large-scale-language-model/)
645. [**LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning arXiv:2308.03303**Longteng Zhang, Lin Zhang, Shaohuai Shi, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-lora-fa-efficient-effective-low/)
646. **[Autonomous LLM-driven research from data to human-verifiable research papers](https://md.research.elamur.ai/free/en/papers/ifargan-2024-autonomous-llm-driven-research/) [NEJM AI](https://md.research.elamur.ai/free/en/venues/nejm-ai/)**Tal Ifargan, Lukas Hafner, Maor Kern, et al.*2024 · 57 citations*
647. [**Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws arXiv:2401.00448**Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/sardana-2024-chinchilla-optimal-accounting-inference-language/)
648. **[Can LLMs Learn from Previous Mistakes? Investigating LLMs' Errors to Boost for Reasoning](https://md.research.elamur.ai/free/en/papers/tong-2024-can-llms-learn-previous-mistakes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongqi Tong, Dawei Li, Sizhe Wang, et al.*2024 · 57 citations*
649. [**Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning arXiv:2401.10480**Yiwei Li, Peiwen Yuan, Shaoxiong Feng, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-escape-sky-high-cost-early/)
650. [**HelpSteer2-Preference: Complementing Ratings with Preferences arXiv:2410.01257**Zhilin Wang, Alexander Bukharin, Olivier Delalleau, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-helpsteer2-preference-complementing-ratings-preferences/)
651. **[Reducing Transformer Key-Value Cache Size with Cross-Layer Attention](https://md.research.elamur.ai/free/en/papers/brandon-2024-reducing-transformer-key-value-cache/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**William Brandon, Mayank Mishra, Aniruddha Nrusimha, et al.*2024 · 57 citations*
652. [**RegMix: Data Mixture as Regression for Language Model Pre-training arXiv:2407.01492**Qian Liu, Xiaosen Zheng, Niklas Muennighoff, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-regmix-data-mixture-regression-language/)
653. **[TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space](https://md.research.elamur.ai/free/en/papers/zhang-2024-truthx-alleviating-hallucinations-editing-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaolei Zhang, Tian Yu, Yang Feng*2024 · 57 citations*
654. **[Understanding and Mitigating Language Confusion in LLMs](https://md.research.elamur.ai/free/en/papers/marchisio-2024-understanding-mitigating-language-confusion-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kelly Marchisio, Wei-Yin Ko, Alexandre Berard, et al.*2024 · 57 citations*
655. **[Unintended Impacts of LLM Alignment on Global Representation](https://md.research.elamur.ai/free/en/papers/ryan-2024-unintended-impacts-llm-alignment-global/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael J Ryan, William Held, Diyi Yang*2024 · 57 citations*
656. [**Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking arXiv:2402.09369**Yi Fung, Ruining Zhao, Jae Doo, et al.*2024 · 56 citations*](https://md.research.elamur.ai/free/en/papers/fung-2024-massively-multi-cultural-knowledge-acquisition/)
657. **[RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold](https://md.research.elamur.ai/free/en/papers/setlur-2024-rl-incorrect-synthetic-data-scales/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Amrith Setlur, Saurabh Garg, Xinyang Geng, et al.*2024 · 56 citations*
658. **[The Art of Saying No: Contextual Noncompliance in Language Models](https://md.research.elamur.ai/free/en/papers/brahman-2024-art-saying-no-contextual-noncompliance/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.*2024 · 56 citations*
659. [**The Earth is Flat because...: Investigating LLMs' Belief towards Misinformation via Persuasive Conversation arXiv:2312.09085**Rongwu Xu, Brian S. Lin, Shujian Yang, et al.*2023 · 56 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-earth-flat-because-investigating-llms/)
660. **[PlanGenLLMs: A Modern Survey of LLM Planning Capabilities](https://md.research.elamur.ai/free/en/papers/wei-2025-plangenllms-modern-survey-llm-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Wei, Zihao Zhang, Shenghua He, et al.*2025 · 55 citations*
661. **[Democratizing LLMs for Low-Resource Languages by Leveraging their English Dominant Abilities with Linguistically-Diverse Prompts](https://md.research.elamur.ai/free/en/papers/nguyen-2024-democratizing-llms-low-resource-languages/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuan-Phi Nguyen, Mahani Aljunied, Shafiq Joty, et al.*2024 · 55 citations*
662. [**HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly arXiv:2410.02694**Howard Yen, Tianyu Gao, Minmin Hou, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/yen-2024-helmet-evaluate-long-context-language/)
663. **[Hopping Too Late: Exploring the Limitations of Large Language Models on Multi-Hop Queries](https://md.research.elamur.ai/free/en/papers/biran-2024-hopping-too-late-exploring-limitations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eden Biran, Daniela Gottesman, Sohee Yang, et al.*2024 · 55 citations*
664. **[Language Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the Missing AANNs](https://md.research.elamur.ai/free/en/papers/misra-2024-language-models-learn-rare-phenomena/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kanishka Misra, Kyle Mahowald*2024 · 55 citations*
665. **[REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2024-rear-relevance-aware-retrieval-augmented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuhao Wang, Ruiyang Ren, Junyi Li, et al.*2024 · 55 citations*
666. **[SciAgent: Tool-augmented Language Models for Scientific Reasoning](https://md.research.elamur.ai/free/en/papers/ma-2024-sciagent-tool-augmented-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yubo Ma, Zhibin Gou, Junheng Hao, et al.*2024 · 55 citations*
667. [**Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs arXiv:2402.14903**Aaditya K. Singh, DJ Strouse*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-tokenization-counts-impact-tokenization-arithmetic/)
668. [**LM-Polygraph: Uncertainty Estimation for Language Models arXiv:2311.07383**Ekaterina Fadeeva, Roman Vashurin, Akim Tsvigun, et al.*2023 · 55 citations*](https://md.research.elamur.ai/free/en/papers/fadeeva-2023-lm-polygraph-uncertainty-estimation-language/)
669. [**Zoology: Measuring and Improving Recall in Efficient Language Models arXiv:2312.04927**Simran Arora; Sabri Eyuboglu; Aman Timalsina; Isys Johnson; Michael Poli; James Zou; Atri Rudra;, Christopher Re*2023 · 55 citations*](https://md.research.elamur.ai/free/en/papers/arora-2023-zoology-measuring-improving-recall-efficient/)
670. [**A Survey of Resource-efficient LLM and Multimodal Foundation Models arXiv:2401.08092**Mengwei Xu, Wangsong Yin, Dongqi Cai, et al.*2024 · 54 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-survey-resource-efficient-llm-multimodal/)
671. [**ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL arXiv:2402.19446**Yifei Zhou, Andrea Zanette, Jiayi Pan, et al.*2024 · 54 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-archer-training-language-model-agents/)
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673. [**Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models arXiv:2406.13542**Guanting Dong, Keming Lu, Chengpeng Li, et al.*2024 · 54 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-self-play-execution-feedback-improving/)
674. [**Scaling Laws of RoPE-based Extrapolation arXiv:2310.05209**Xiaoran Liu, Hang Yan, Shuo Zhang, et al.*2023 · 54 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-scaling-laws-rope-based/)
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677. [**Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning arXiv:2406.14283**Chaojie Wang, Yanchen Deng, Zhiyi Lyu, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-q-improving-multi-step-reasoning/)
678. **[Trial and Error: Exploration-Based Trajectory Optimization of LLM Agents](https://md.research.elamur.ai/free/en/papers/song-2024-trial-error-exploration-based-trajectory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifan Song, Da Yin, Xiang Yue, et al.*2024 · 53 citations*
679. **[Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding](https://md.research.elamur.ai/free/en/papers/belay-2025-evaluating-capabilities-large-language-models/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tadesse Destaw Belay, Israel Abebe Azime, Abinew Ali Ayele, et al.*2025 · 52 citations*
680. **[Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization](https://md.research.elamur.ai/free/en/papers/zhang-2024-agent-pro-learning-evolve-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqi Zhang, Ke Tang, Hai Wu, et al.*2024 · 52 citations*
681. **[Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?](https://md.research.elamur.ai/free/en/papers/balepur-2024-artifacts-or-abduction-how-do/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger*2024 · 52 citations*
682. [**Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance arXiv:2403.16952**Jiasheng Ye, Peiju Liu, Tianxiang Sun, et al.*2024 · 52 citations*](https://md.research.elamur.ai/free/en/papers/ye-2024-data-mixing-laws-optimizing-data/)
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684. [**LLM Internal States Reveal Hallucination Risk Faced With a Query arXiv:2407.03282**Ziwei Ji, Delong Chen, Etsuko Ishii, et al.*2024 · 52 citations*](https://md.research.elamur.ai/free/en/papers/ji-2024-llm-internal-states-reveal-hallucination/)
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686. [**PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training arXiv:2309.10400**Dawei Zhu, Nan Yang, Liang Wang, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-pose-efficient-context-window/)
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689. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/)
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699. [**SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphs arXiv:2308.03349**Shengzhi Li, Nima Tajbakhsh*2023 · 50 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-scigraphqa-large-scale-synthetic-multi/)
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