---
title: "Who cites Yujia Li — page 5 — 4,002 papers of our library"
description: "4,002 papers of the Elamur Research library cite the works of Yujia Li, found in their bibliographies · page 5 of 10 · 401–500; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yujia-li/cited-by/page/5/"
---
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# Who cites Yujia Li

4,197 citations of their works from 4,002 papers of our library (of the 149,439 whose bibliographies we read) · 974 with a page here, the most cited first · page 5 of 10 · 401–500 · [← Yujia Li](https://md.research.elamur.ai/free/en/authors/yujia-li/)

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401. [**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/)
402. [**LEGO-Prover: Neural Theorem Proving with Growing Libraries arXiv:2310.00656**Haiming Wang, Huajian Xin, Chuanyang Zheng, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-lego-prover-neural-theorem-proving/)
403. [**Humans or LLMs as the Judge? A Study on Judgement Biases arXiv:2402.10669**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 78 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-llms-judge-study-judgement/)
404. **[AudioBench: A Universal Benchmark for Audio Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-audiobench-universal-benchmark-audio-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Xunlong Zou, Geyu Lin, et al.*2025 · 77 citations*
405. [**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/)
406. **[KMMLU: Measuring Massive Multitask Language Understanding in Korean](https://md.research.elamur.ai/free/en/papers/son-2025-kmmlu-measuring-massive-multitask-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guijin Son, Hanwool Lee, Sungdong Kim, et al.*2025 · 76 citations*
407. [**Llama-Nemotron: Efficient Reasoning Models arXiv:2505.00949**Akhiad Bercovich, Itay Levy, Izik Golan, et al.*2025 · 76 citations*](https://md.research.elamur.ai/free/en/papers/bercovich-2025-llama-nemotron-efficient-reasoning-models/)
408. [**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/)
409. [**Self-Reflection in LLM Agents: Effects on Problem-Solving Performance arXiv:2405.06682 · 2nd International Conference on Foundation and Large Language Models (FLLM 2024), pp. 476-483**Matthew Renze, Erhan Guven*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/renze-2024-self-reflection-llm-agents-effects/)
410. [**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/)
411. **[Improving Compositional Generalization with Latent Structure and Data Augmentation](https://md.research.elamur.ai/free/en/papers/qiu-2022-improving-compositional-generalization-latent-structure/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Linlu Qiu, Peter Shaw, Panupong Pasupat, et al.*2022 · 76 citations*
412. **[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*
413. [**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/)
414. [**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/)
415. **[MANTIS: Interleaved Multi-Image Instruction Tuning](https://md.research.elamur.ai/free/en/papers/jiang-2024-mantis-interleaved-multi-image-instruction/) [Transactions on Machine Learning Research](https://md.research.elamur.ai/free/en/venues/transactions-on-machine-learning-research/)**Dongfu Jiang, Xuan He, Huaye Zeng, et al.*2024 · 74 citations*
416. **[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*
417. [**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/)
418. [**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/)
419. [**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/)
420. [**Long Context Transfer from Language to Vision arXiv:2406.16852**Peiyuan Zhang, Kaichen Zhang, Bo Li, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-long-context-transfer-language-vision/)
421. [**TACO: Topics in Algorithmic COde generation dataset arXiv:2312.14852**Rongao Li, Jie Fu, Bo-Wen Zhang, et al.*2023 · 73 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-taco-topics-algorithmic-code-generation/)
422. [**What Language Model to Train if You Have One Million GPU Hours? arXiv:2210.15424**Teven Le Scao, Thomas Wang, Daniel Hesslow, et al.*2022 · 73 citations*](https://md.research.elamur.ai/free/en/papers/scao-2022-language-model-train-if-have/)
423. **[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*
424. [**InPars: Data Augmentation for Information Retrieval using Large Language Models arXiv:2202.05144**Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, et al.*2022 · 72 citations*](https://md.research.elamur.ai/free/en/papers/bonifacio-2022-inpars-data-augmentation-information-retrieval/)
425. [**The Ghost in the Machine has an American accent: value conflict in GPT-3 arXiv:2203.07785**Rebecca L Johnson, Giada Pistilli, Natalia Menedez-Gonzalez, et al.*2022 · 72 citations*](https://md.research.elamur.ai/free/en/papers/johnson-2022-ghost-machine-has-american-accent/)
426. **[Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scale](https://md.research.elamur.ai/free/en/papers/sartran-2022-transformer-grammars-augmenting-transformer-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Laurent Sartran, Samuel Barrett, Adhiguna Kuncoro, et al.*2022 · 72 citations*
427. **[Judging the Judges: A Systematic Study of Position Bias in LLM-as-a-Judge](https://md.research.elamur.ai/free/en/papers/shi-2025-judging-judges-systematic-study-position/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Lin Shi, Chiyu Ma, Wenhua Liang, et al.*2025 · 71 citations*
428. **[LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing](https://md.research.elamur.ai/free/en/papers/du-2024-llms-assist-nlp-researchers-critique/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiangshu Du, Yibo Wang, Wenting Zhao, et al.*2024 · 71 citations*
429. **[Entailer: Answering Questions with Faithful and Truthful Chains of Reasoning](https://md.research.elamur.ai/free/en/papers/tafjord-2022-entailer-answering-questions-faithful/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Oyvind Tafjord, Bhavana Dalvi Mishra, Peter Clark*2022 · 71 citations*
430. [**StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts**Zhengxiang Shi, Qiang Zhang, Aldo Lipani*2022 · 71 citations*](https://md.research.elamur.ai/free/en/papers/shi-2022-stepgame-new-benchmark-robust-multi/)
431. **[Group-in-Group Policy Optimization for LLM Agent Training](https://md.research.elamur.ai/free/en/papers/feng-2025-group-group-policy-optimization-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lang Feng, Zhenghai Xue, Tingcong Liu, et al.*2025 · 69 citations*
432. **[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*
433. **[Execution-Based Evaluation for Open-Domain Code Generation](https://md.research.elamur.ai/free/en/papers/wang-2023-execution-based-evaluation-open-domain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiruo Wang, Shuyan Zhou, Daniel Fried, et al.*2023 · 69 citations*
434. [**Competitive Programming with Large Reasoning Models arXiv:2502.06807**OpenAI: Ahmed El-Kishky, Alexander Wei, Andre Saraiva, et al.*2025 · 68 citations*](https://md.research.elamur.ai/free/en/papers/el-kishky-2025-competitive-programming-large-reasoning-models/)
435. [**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/)
436. [**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/)
437. **[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*
438. [**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/)
439. **[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*
440. **[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*
441. [**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/)
442. **[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*
443. **[On the Effects of Data Scale on UI Control Agents](https://md.research.elamur.ai/free/en/papers/li-2024-effects-data-scale-ui-control/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wei Li, William Bishop, Alice Li, et al.*2024 · 67 citations*
444. [**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/)
445. **[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*
446. **[ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidence](https://md.research.elamur.ai/free/en/papers/wu-2024-clasheval-quantifying-tug-war-between/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kevin Wu, Eric Wu, James Zou*2024 · 65 citations*
447. [**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/)
448. **[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*
449. [**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/)
450. **[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*
451. [**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/)
452. **[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*
453. [**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/)
454. **[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*
455. [**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/)
456. **[Can Language Models Handle Recursively Nested Grammatical Structures? A Case Study on Comparing Models and Humans](https://md.research.elamur.ai/free/en/papers/lampinen-2024-can-language-models-handle-recursively/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Andrew Lampinen*2024 · 63 citations*
457. [**ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2112.12731**Shuohuan Wang, Yu Sun, Yang Xiang, et al.*2021 · 63 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-ernie-3-0-titan/)
458. **[SatLM: Satisfiability-Aided Language Models Using Declarative Prompting](https://md.research.elamur.ai/free/en/papers/ye-2023-satlm-satisfiability-aided-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xi Ye, Qiaochu Chen, Isil Dillig, et al.*2023 · 62 citations*
459. **[NaturalProver: Grounded Mathematical Proof Generation with Language Models](https://md.research.elamur.ai/free/en/papers/welleck-2022-naturalprover-grounded-mathematical-proof-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Sean Welleck, Jiacheng Liu, Ximing Lu, et al.*2022 · 62 citations*
460. [**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/)
461. [**MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark arXiv:2402.04788**Dongping Chen, Ruoxi Chen, Shilin Zhang, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-mllm-judge-assessing-multimodal-llm/)
462. [**Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models arXiv:2402.02207**Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/zong-2024-safety-fine-tuning-almost-no/)
463. [**mmBERT: A Modern Multilingual Encoder with Annealed Language Learning arXiv:2509.06888**Marc Marone, Orion Weller, William Fleshman, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/marone-2025-mmbert-modern-multilingual-encoder-annealed/)
464. **[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*
465. [**Rho-1: Not All Tokens Are What You Need arXiv:2404.07965**Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-rho-1-all-tokens-need/)
466. **[ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-prorl-prolonged-reinforcement-learning-expands/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Mingjie Liu, Shizhe Diao, Ximing Lu, et al.*2025 · 58 citations*
467. [**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/)
468. [**Dialect prejudice predicts AI decisions about people's character, employability, and criminality arXiv:2403.00742**Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/hofmann-2024-dialect-prejudice-predicts-ai-decisions/)
469. [**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/)
470. **[OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI](https://md.research.elamur.ai/free/en/papers/huang-2024-olympicarena-benchmarking-multi-discipline-cognitive/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhen Huang, Zengzhi Wang, Shijie Xia, et al.*2024 · 56 citations*
471. **[Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions](https://md.research.elamur.ai/free/en/papers/zelikman-2023-parsel-algorithmic-reasoning-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Eric Zelikman, Qian Huang, Gabriel Poesia, et al.*2023 · 56 citations*
472. [**AI Agents That Matter arXiv:2407.01502**Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/kapoor-2024-ai-agents-that-matter/)
473. [**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/)
474. **[InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-4khd-pioneering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 54 citations*
475. **[M³CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/chen-2024-m-3-cot-novel-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiguang Chen, Libo Qin, Jin Zhang, et al.*2024 · 54 citations*
476. [**Beyond Accuracy: Evaluating the Reasoning Behavior of Large Language Models — A Survey arXiv:2404.01869**Philipp Mondorf, Barbara Plank*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/mondorf-2024-accuracy-evaluating-reasoning-behavior-large/)
477. [**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/)
478. **[JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ma-2024-janusflow-harmonizing-autoregression-rectified/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Yiyang Ma, Xingchao Liu, Xiaokang Chen, et al.*2024 · 52 citations*
479. [**AutoML-GPT: Automatic Machine Learning with GPT arXiv:2305.02499**Shujian Zhang, Chengyue Gong, Lemeng Wu, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-automl-gpt-automatic-machine-learning/)
480. [**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/)
481. [**RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning arXiv:2410.02089**Jonas Gehring, Kunhao Zheng, Jade Copet, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2024-rlef-grounding-code-llms-execution/)
482. [**On the application of Large Language Models for language teaching and assessment technology arXiv:2307.08393**Andrew Caines, Luca Benedetto, Shiva Taslimipoor, et al.*2023 · 51 citations*](https://md.research.elamur.ai/free/en/papers/caines-2023-application-large-language-models-language/)
483. [**MiniMax-01: Scaling Foundation Models with Lightning Attention arXiv:2501.08313**MiniMax, Aonian Li, Bangwei Gong, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-01-scaling-foundation/)
484. [**PanGu-Coder: Program Synthesis with Function-Level Language Modeling arXiv:2207.11280**Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, et al.*2022 · 49 citations*](https://md.research.elamur.ai/free/en/papers/christopoulou-2022-pangu-coder-program-synthesis/)
485. [**Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy arXiv:2507.01352**Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.*2025 · 48 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-skywork-reward-v2-scaling/)
486. **[Attribute First, then Generate: Locally-attributable Grounded Text Generation](https://md.research.elamur.ai/free/en/papers/slobodkin-2024-attribute-first-then-generate-locally/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aviv Slobodkin, Eran Hirsch, Arie Cattan, et al.*2024 · 48 citations*
487. **[IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages](https://md.research.elamur.ai/free/en/papers/khan-2024-indicllmsuite-blueprint-creating-pre-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammed Safi Ur Rahman Khan, Priyam Mehta, Ananth Sankar, et al.*2024 · 48 citations*
488. [**Language models scale reliably with over-training and on downstream tasks arXiv:2403.08540**Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/gadre-2024-language-models-scale-reliably-over/)
489. [**Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies arXiv:2407.13623**Chaofan Tao, Qian Liu, Longxu Dou, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/tao-2024-scaling-laws-vocabulary-larger-models/)
490. **[AlGhafa Evaluation Benchmark for Arabic Language Models](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-alghafa-evaluation-benchmark-arabic-language/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Ebtesam Almazrouei, Ruxandra Cojocaru, Michele Baldo, et al.*2023 · 46 citations*
491. [**EuroLLM-9B: Technical Report arXiv:2506.04079**Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.*2025 · 45 citations*](https://md.research.elamur.ai/free/en/papers/martins-2025-eurollm-9b-technical-report/)
492. [**Gemini Embedding: Generalizable Embeddings from Gemini arXiv:2503.07891**Jinhyuk Lee, Feiyang Chen, Sahil Dua, et al.*2025 · 45 citations*](https://md.research.elamur.ai/free/en/papers/lee-2025-gemini-embedding-generalizable-embeddings-gemini/)
493. **[CoCoMIC: Code Completion by Jointly Modeling In-file and Cross-file Context](https://md.research.elamur.ai/free/en/papers/ding-2024-cocomic-code-completion-jointly-modeling/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yangruibo Ding, Zijian Wang, Wasi Ahmad, et al.*2024 · 45 citations*
494. [**Contrastive Chain-of-Thought Prompting arXiv:2311.09277**Yew Ken Chia, Guizhen Chen, Luu Anh Tuan, et al.*2023 · 45 citations*](https://md.research.elamur.ai/free/en/papers/chia-2023-contrastive-chain-thought-prompting/)
495. [**olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models arXiv:2502.18443**Jake Poznanski, Aman Rangapur, Jon Borchardt, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/poznanski-2025-olmocr-unlocking-trillions-tokens-pdfs/)
496. **[Stop Looking for “Important Tokens” in Multimodal Language Models: Duplication Matters More](https://md.research.elamur.ai/free/en/papers/wen-2025-stop-looking-important-tokens-multimodal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zichen Wen, Yifeng Gao, Shaobo Wang, et al.*2025 · 44 citations*
497. **[Augmenting Math Word Problems via Iterative Question Composing](https://md.research.elamur.ai/free/en/papers/liu-2024-augmenting-math-word-problems-iterative/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Haoxiong Liu, Yifan Zhang, Yifan Luo, et al.*2024 · 44 citations*
498. [**HyperCLOVA X Technical Report arXiv:2404.01954**Kang Min Yoo, Jaegeun Han, Sookyo In, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/yoo-2024-hyperclova-x-technical-report/)
499. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/)
500. **[General-Reasoner: Advancing LLM Reasoning Across All Domains](https://md.research.elamur.ai/free/en/papers/ma-2025-general-reasoner-advancing-llm-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xueguang Ma, Qian Liu, Dongfu Jiang, et al.*2025 · 43 citations*

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