---
title: "Who cites Michele Catasta — page 6 — 3,615 citing papers"
description: "3,615 papers of the Elamur Research library cite the works of Michele Catasta, found in their bibliographies · page 6 of 11 · 501–600; the…"
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---
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# Who cites Michele Catasta

3,880 citations of their works from 3,615 papers of our library (of the 149,439 whose bibliographies we read) · 1,001 with a page here, the most cited first · page 6 of 11 · 501–600 · [← Michele Catasta](https://md.research.elamur.ai/free/en/authors/michele-catasta/)

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501. **[LLMs cannot find reasoning errors, but can correct them given the error location](https://md.research.elamur.ai/free/en/papers/tyen-2024-llms-cannot-find-reasoning-errors/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gladys Tyen, Hassan Mansoor, Victor Carbune, et al.*2024 · 85 citations*
502. **[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*
503. [**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/)
504. [**Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOM arXiv:2303.01911**Rachel Bawden, François Yvon*2023 · 85 citations*](https://md.research.elamur.ai/free/en/papers/bawden-2023-investigating-translation-performance-large-multilingual/)
505. [**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/)
506. **[Selectively Answering Ambiguous Questions](https://md.research.elamur.ai/free/en/papers/cole-2023-selectively-answering-ambiguous-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jeremy Cole, Michael Zhang, Daniel Gillick, et al.*2023 · 84 citations*
507. **[Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples](https://md.research.elamur.ai/free/en/papers/saparov-2023-testing-general-deductive-reasoning-capacity/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, et al.*2023 · 84 citations*
508. **[Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/kim-2023-tree-clarifications-answering-ambiguous-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gangwoo Kim, Sungdong Kim, Byeongguk Jeon, et al.*2023 · 84 citations*
509. [**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/)
510. **[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*
511. **[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*
512. **[Mitigating the Alignment Tax of RLHF](https://md.research.elamur.ai/free/en/papers/lin-2024-mitigating-alignment-tax-rlhf/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yong Lin, Hangyu Lin, Wei Xiong, et al.*2024 · 83 citations*
513. **[LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development](https://md.research.elamur.ai/free/en/papers/chalkidis-2023-lexfiles-legallama-facilitating-english-multinational/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ilias Chalkidis, Nicolas Garneau, Catalina Goanta, et al.*2023 · 83 citations*
514. **[ORCA: A Challenging Benchmark for Arabic Language Understanding](https://md.research.elamur.ai/free/en/papers/elmadany-2023-orca-challenging-benchmark-arabic-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**AbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed*2023 · 83 citations*
515. [**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/)
516. [**CodeGemma: Open Code Models Based on Gemma arXiv:2406.11409**CodeGemma Team: Heri Zhao, Jeffrey Hui, Joshua Howland, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-codegemma-open-code-models-based/)
517. [**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/)
518. [**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/)
519. **[Multilingual LLMs are Better Cross-lingual In-context Learners with Alignment](https://md.research.elamur.ai/free/en/papers/tanwar-2023-multilingual-llms-are-better-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eshaan Tanwar, Subhabrata Dutta, Manish Borthakur, et al.*2023 · 82 citations*
520. **[OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models](https://md.research.elamur.ai/free/en/papers/huang-2025-opencoder-open-cookbook-top-tier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siming Huang, Tianhao Cheng, Jason Klein Liu, et al.*2025 · 81 citations*
521. **[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*
522. [**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/)
523. **[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*
524. **[D4: Improving LLM Pretraining via Document De-Duplication and Diversification](https://md.research.elamur.ai/free/en/papers/tirumala-2023-d4-improving-llm-pretraining-document/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kushal Tirumala, Daniel Simig, Armen Aghajanyan, et al.*2023 · 81 citations*
525. [**Talk like a Graph: Encoding Graphs for Large Language Models arXiv:2310.04560**Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/fatemi-2023-talk-like-graph-encoding-graphs/)
526. [**Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention arXiv:2404.07143**Tsendsuren Munkhdalai, Manaal Faruqui, Siddharth Gopal*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/munkhdalai-2024-leave-no-context-behind-efficient/)
527. [**Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning arXiv:2410.14211**Xingyu Tan, Xiaoyang Wang, Qing Liu, et al.*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/tan-2024-paths-over-graph-knowledge-graph/)
528. [**PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models arXiv:2402.07867**Wei Zou, Runpeng Geng, Binghui Wang, et al.*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/zou-2024-poisonedrag-knowledge-corruption-attacks-retrieval/)
529. **[Mitigating Label Biases for In-context Learning](https://md.research.elamur.ai/free/en/papers/fei-2023-mitigating-label-biases-context-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Fei, Yifan Hou, Zeming Chen, et al.*2023 · 80 citations*
530. [**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/)
531. [**Out-of-Distribution Detection and Selective Generation for Conditional Language Models arXiv:2209.15558**Jie Ren, Jiaming Luo, Yao Zhao, et al.*2022 · 80 citations*](https://md.research.elamur.ai/free/en/papers/ren-2022-out-distribution-detection-selective-generation/)
532. [**BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text arXiv:2403.18421**Elliot Bolton, Abhinav Venigalla, Michihiro Yasunaga, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/bolton-2024-biomedlm-2-7b-parameter-language/)
533. [**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/)
534. [**LLaMA Beyond English: An Empirical Study on Language Capability Transfer arXiv:2401.01055**Jun Zhao, Zhihao Zhang, Luhui Gao, et al.*2024 · 78 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-llama-english-empirical-study-language/)
535. **[Language models are not naysayers: An analysis of language models on negation benchmarks](https://md.research.elamur.ai/free/en/papers/truong-2023-language-models-naysayers-analysis-language/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Thinh Hung Truong, Timothy Baldwin, Karin Verspoor, et al.*2023 · 78 citations*
536. [**SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling arXiv:2312.15166**Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-solar-10-7b-scaling-large/)
537. [**Solving Math Word Problems by Combining Language Models With Symbolic Solvers arXiv:2304.09102**Joy He-Yueya, Gabriel Poesia, Rose E. Wang, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/yueya-2023-solving-math-word-problems-combining/)
538. [**Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators arXiv:2403.16950**Yinhong Liu, Han Zhou, Zhijiang Guo, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-aligning-human-judgement-role-pairwise/)
539. [**G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model arXiv:2312.11370**Jiahui Gao, Renjie Pi, Jipeng Zhang, et al.*2023 · 76 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-g-llava-solving-geometric-problem/)
540. **[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*
541. [**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/)
542. [**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/)
543. **[SciCode: A Research Coding Benchmark Curated by Scientists](https://md.research.elamur.ai/free/en/papers/tian-2024-scicode-research-coding-benchmark/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Minyang Tian, Luyu Gao, Shizhuo Dylan Zhang, et al.*2024 · 75 citations*
544. **[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*
545. **[CREATOR: Tool Creation for Disentangling Abstract and Concrete Reasoning of Large Language Models](https://md.research.elamur.ai/free/en/papers/qian-2023-creator-tool-creation-disentangling-abstract/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Qian, Chi Han, Yi Fung, et al.*2023 · 75 citations*
546. [**GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking arXiv:2305.15066**Jiayan Guo, Lun Du, Hengyu Liu, et al.*2023 · 75 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-gpt4graph-large-language-models-understand/)
547. [**Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning arXiv:2305.19523**Xiaoxin He, Xavier Bresson, Thomas Laurent, et al.*2023 · 75 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-harnessing-explanations-llm-lm-interpreter/)
548. [**Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integration arXiv:2306.09093**Chenyang Lyu, Minghao Wu, Longyue Wang, et al.*2023 · 75 citations*](https://md.research.elamur.ai/free/en/papers/lyu-2023-macaw-llm-multi-modal-language/)
549. **[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*
550. [**Gecko: Versatile Text Embeddings Distilled from Large Language Models arXiv:2403.20327**Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-gecko-versatile-text-embeddings-distilled/)
551. **[MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks](https://md.research.elamur.ai/free/en/papers/ahuja-2024-megaverse-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.*2024 · 74 citations*
552. [**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/)
553. [**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/)
554. [**AlignBench: Benchmarking Chinese Alignment of Large Language Models arXiv:2311.18743**Xiao Liu, Xuanyu Lei, Shengyuan Wang, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-alignbench-benchmarking-chinese-alignment/)
555. [**Large Language Models as Analogical Reasoners arXiv:2310.01714**Michihiro Yasunaga, Xinyun Chen, Yujia Li, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/yasunaga-2023-large-language-models-analogical-reasoners/)
556. [**ReLoRA: High-Rank Training Through Low-Rank Updates arXiv:2307.05695**Vladislav Lialin, Namrata Shivagunde, Sherin Muckatira, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/lialin-2023-relora-high-rank-training-through/)
557. **[Iterative Translation Refinement with Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2024-iterative-translation-refinement-large-language/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Pinzhen Chen, Zhicheng Guo, Barry Haddow, et al.*2024 · 73 citations*
558. **[ReCEval: Evaluating Reasoning Chains via Correctness and Informativeness](https://md.research.elamur.ai/free/en/papers/prasad-2023-receval-evaluating-reasoning-chains-correctness/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Archiki Prasad, Swarnadeep Saha, Xiang Zhou, et al.*2023 · 73 citations*
559. [**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/)
560. **[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*
561. **[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*
562. [**Chain-of-Thought Hub: A Continuous Effort to Measure Large Language Models' Reasoning Performance arXiv:2305.17306**Yao Fu, Litu Ou, Mingyu Chen, et al.*2023 · 72 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-chain-thought-hub-continuous-effort/)
563. **[Unveiling the Implicit Toxicity in Large Language Models](https://md.research.elamur.ai/free/en/papers/wen-2023-unveiling-implicit-toxicity-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiaxin Wen, Pei Ke, Hao Sun, et al.*2023 · 72 citations*
564. **[Few-Shot Semantic Parsing with Language Models Trained on Code](https://md.research.elamur.ai/free/en/papers/shin-2022-few-shot-semantic-parsing-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Richard Shin, Benjamin Van Durme*2022 · 72 citations*
565. [**CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles Findings of the Association for Computational Linguistics: EMNLP 2023**Shashank Sonkar, Naiming Liu, Debshila Mallick, et al.*2023 · 71 citations*](https://md.research.elamur.ai/free/en/papers/sonkar-2023-class-design-framework-building-intelligent/)
566. **[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*
567. **[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*
568. [**ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data and Comprehensive Evaluation arXiv:2306.09968**Guangyu Wang, Guoxing Yang, Zongxin Du, et al.*2023 · 70 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-clinicalgpt-large-language-models-finetuned/)
569. [**Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training arXiv:2305.14342**Hong Liu, Zhiyuan Li, David Hall, et al.*2023 · 70 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-sophia-scalable-stochastic-second-order/)
570. **[Automatic Generation of Socratic Subquestions for Teaching Math Word Problems](https://md.research.elamur.ai/free/en/papers/shridhar-2022-automatic-generation-socratic-subquestions-teaching/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kumar Shridhar, Jakub Macina, Mennatallah El-Assady, et al.*2022 · 70 citations*
571. **[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*
572. [**Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning arXiv:2309.05444**Ted Zadouri, Ahmet Ustun, Arash Ahmadian, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/zadouri-2023-pushing-mixture-experts-limit-extremely/)
573. **[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*
574. [**VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks arXiv:2504.05118**Yu Yue, Yufeng Yuan, Qiying Yu, et al.*2025 · 68 citations*](https://md.research.elamur.ai/free/en/papers/yue-2025-vapo-efficient-reliable-reinforcement-learning/)
575. **[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*
576. [**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/)
577. [**Contrastive Decoding Improves Reasoning in Large Language Models arXiv:2309.09117**Sean O'Brien, Mike Lewis*2023 · 68 citations*](https://md.research.elamur.ai/free/en/papers/o-brien-2023-contrastive-decoding-improves-reasoning-large/)
578. **[Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy](https://md.research.elamur.ai/free/en/papers/ippolito-2023-preventing-generation-verbatim-memorization-language/) [International Natural Language Generation Conference (INLG)](https://md.research.elamur.ai/free/en/venues/inlg/)**Daphne Ippolito, Florian Tramer, Milad Nasr, et al.*2023 · 68 citations*
579. **[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*
580. [**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/)
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582. **[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*
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584. **[Crawling the Internal Knowledge-Base of Language Models](https://md.research.elamur.ai/free/en/papers/cohen-2023-crawling-internal-knowledge-base-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Roi Cohen, Mor Geva, Jonathan Berant, et al.*2023 · 67 citations*
585. [**What Algorithms can Transformers Learn? A Study in Length Generalization arXiv:2310.16028**Hattie Zhou, Arwen Bradley, Etai Littwin, et al.*2023 · 67 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-algorithms-transformers-learn-study-length/)
586. [**An Open Source Data Contamination Report for Large Language Models arXiv:2310.17589**Yucheng Li, Frank Guerin, Chenghua Lin*2023 · 66 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-open-source-data-contamination-report/)
587. [**ARB: Advanced Reasoning Benchmark for Large Language Models arXiv:2307.13692**Tomohiro Sawada, Daniel Paleka, Alexander Havrilla, et al.*2023 · 66 citations*](https://md.research.elamur.ai/free/en/papers/sawada-2023-arb-advanced-reasoning-benchmark-large/)
588. [**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/)
589. [**Large Language Models As Evolution Strategies arXiv:2402.18381**Robert Tjarko Lange, Yingtao Tian, Yujin Tang*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/lange-2024-large-language-models-evolution-strategies/)
590. [**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/)
591. **[A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models](https://md.research.elamur.ai/free/en/papers/stolfo-2023-causal-framework-quantify-robustness-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, et al.*2023 · 65 citations*
592. [**Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic Tasks arXiv:2305.14201**Tiedong Liu, Bryan Kian Hsiang Low*2023 · 65 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-goat-fine-tuned-llama-outperforms/)
593. **[Questions Are All You Need to Train a Dense Passage Retriever](https://md.research.elamur.ai/free/en/papers/sachan-2023-questions-are-all-you-need/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Devendra Singh Sachan, Mike Lewis, Dani Yogatama, et al.*2023 · 65 citations*
594. **[Why think step by step? Reasoning emerges from the locality of experience](https://md.research.elamur.ai/free/en/papers/prystawski-2023-why-think-step-step-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ben Prystawski, Michael Y. Li, Noah D. Goodman*2023 · 65 citations*
595. [**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/)
596. **[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*
597. **[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*
598. [**OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models arXiv:2402.01739**Fuzhao Xue, Zian Zheng, Yao Fu, et al.*2024 · 64 citations*](https://md.research.elamur.ai/free/en/papers/xue-2024-openmoe-early-effort-open-mixture/)
599. [**CValues: Measuring the Values of Chinese Large Language Models from Safety to Responsibility arXiv:2307.09705**Guohai Xu, Jiayi Liu, Ming Yan, et al.*2023 · 64 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-cvalues-measuring-values-chinese/)
600. [**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/)

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