---
title: "Who cites Vlad Firoiu — page 4 — 2,599 papers of our library"
description: "2,599 papers of the Elamur Research library cite the works of Vlad Firoiu, found in their bibliographies · page 4 of 8 · 301–400; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/vlad-firoiu/cited-by/page/4/"
---
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# Who cites Vlad Firoiu

2,622 citations of their works from 2,599 papers of our library (of the 149,439 whose bibliographies we read) · 718 with a page here, the most cited first · page 4 of 8 · 301–400 · [← Vlad Firoiu](https://md.research.elamur.ai/free/en/authors/vlad-firoiu/)

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301. **[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*
302. **[NormAd: A Framework for Measuring the Cultural Adaptability of Large Language Models](https://md.research.elamur.ai/free/en/papers/rao-2025-normad-framework-measuring-cultural-adaptability/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Abhinav Rao, Akhila Yerukola, Vishwa Shah, et al.*2025 · 46 citations*
303. [**A Survey on Deep Learning for Theorem Proving arXiv:2404.09939**Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-survey-deep-learning-theorem-proving/)
304. [**ARGS: Alignment as Reward-Guided Search arXiv:2402.01694**Maxim Khanov, Jirayu Burapacheep, Yixuan Li*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/khanov-2024-args-alignment-reward-guided-search/)
305. [**Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages arXiv:2410.16153**Xiang Yue, Yueqi Song, Akari Asai, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-pangea-fully-open-multilingual-multimodal/)
306. [**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/)
307. [**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/)
308. [**ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change arXiv:2401.09646**David Thulke, Yingbo Gao, Petrus Pelser, et al.*2024 · 45 citations*](https://md.research.elamur.ai/free/en/papers/thulke-2024-climategpt-towards-ai-synthesizing-interdisciplinary/)
309. **[Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/huang-2024-key-point-driven-data-synthesis/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yiming Huang, Xiao Liu, Yeyun Gong, et al.*2024 · 45 citations*
310. [**Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving arXiv:2405.12205**Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, et al.*2024 · 45 citations*](https://md.research.elamur.ai/free/en/papers/didolkar-2024-metacognitive-capabilities-llms-exploration-mathematical/)
311. [**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/)
312. [**Reasoning with Latent Thoughts: On the Power of Looped Transformers arXiv:2502.17416**Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/saunshi-2025-reasoning-latent-thoughts-power-looped/)
313. **[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*
314. **[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*
315. [**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/)
316. **[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*
317. **[Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision](https://md.research.elamur.ai/free/en/papers/wang-2024-multi-step-problem-solving-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Wang, Yunxuan Li, Yuexin Wu, et al.*2024 · 43 citations*
318. **[LUQ: Long-text Uncertainty Quantification for LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2024-luq-long-text-uncertainty-quantification/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Caiqi Zhang, Fangyu Liu, Marco Basaldella, et al.*2024 · 42 citations*
319. [**Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models arXiv:2404.12387**Reka Team: Aitor Ormazabal, Che Zheng, Cyprien de Masson d'Autume, et al.*2024 · 42 citations*](https://md.research.elamur.ai/free/en/papers/ormazabal-2024-reka-core-flash-edge-series/)
320. [**SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models arXiv:2311.08370**Bertie Vidgen, Nino Scherrer, Hannah Rose Kirk, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2023-simplesafetytests-test-suite-identifying-critical/)
321. [**DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models arXiv:2507.09955**Luolin Xiong, Haofen Wang, Xi Chen, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2025-deepseek-paradigm-shifts-technical/)
322. [**DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models arXiv:2411.00836**Chengke Zou, Xingang Guo, Rui Yang, et al.*2024 · 41 citations*](https://md.research.elamur.ai/free/en/papers/zou-2024-dynamath-dynamic-visual-benchmark-evaluating/)
323. [**To Believe or Not to Believe Your LLM arXiv:2406.02543**Yasin Abbasi Yadkori, Ilja Kuzborskij, Andras Gyorgy, et al.*2024 · 41 citations*](https://md.research.elamur.ai/free/en/papers/yadkori-2024-believe-believe-llm/)
324. **[MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scale](https://md.research.elamur.ai/free/en/papers/guo-2025-mammoth-vl-eliciting-multimodal-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiawei Guo, Tianyu Zheng, Yizhi Li, et al.*2025 · 40 citations*
325. **[Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?](https://md.research.elamur.ai/free/en/papers/yona-2024-can-large-language-models-faithfully/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gal Yona, Roee Aharoni, Mor Geva*2024 · 40 citations*
326. [**InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output arXiv:2407.03320**Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-internlm-xcomposer-2-5/)
327. [**Lean Copilot: Large Language Models as Copilots for Theorem Proving in Lean arXiv:2404.12534**Peiyang Song, Kaiyu Yang, Anima Anandkumar*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/song-2024-lean-copilot-large-language-models/)
328. [**Aligning Language Models with Preferences through f-divergence Minimization arXiv:2302.08215**Dongyoung Go, Tomasz Korbak, German Kruszewski, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/go-2023-aligning-language-models-preferences-through/)
329. [**ODIN: Disentangled Reward Mitigates Hacking in RLHF arXiv:2402.07319**Lichang Chen, Chen Zhu, Davit Soselia, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-odin-disentangled-reward-mitigates-hacking/)
330. **[JASMINE: Arabic GPT Models for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/nagoudi-2023-jasmine-arabic-gpt-models-few/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, AbdelRahim Elmadany, et al.*2023 · 38 citations*
331. **[Checklists Are Better Than Reward Models For Aligning Language Models](https://md.research.elamur.ai/free/en/papers/viswanathan-2025-checklists-better-than-reward-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Vijay Viswanathan, Yanchao Sun, Shuang Ma, et al.*2025 · 37 citations*
332. **[Design2Code: Benchmarking Multimodal Code Generation for Automated Front-End Engineering](https://md.research.elamur.ai/free/en/papers/si-2025-design2code-benchmarking-multimodal-code-generation/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chenglei Si, Yanzhe Zhang, Ryan Li, et al.*2025 · 37 citations*
333. **[Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?](https://md.research.elamur.ai/free/en/papers/jin-2025-exploring-concept-depth-how-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Mingyu Jin, Qinkai Yu, Jingyuan Huang, et al.*2025 · 36 citations*
334. [**Evaluating Frontier Models for Dangerous Capabilities arXiv:2403.13793**Mary Phuong, Matthew Aitchison, Elliot Catt, et al.*2024 · 36 citations*](https://md.research.elamur.ai/free/en/papers/phuong-2024-evaluating-frontier-models-dangerous-capabilities/)
335. [**Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models arXiv:2407.07263**Jupinder Parmar, Sanjev Satheesh, Mostofa Patwary, et al.*2024 · 36 citations*](https://md.research.elamur.ai/free/en/papers/parmar-2024-reuse-don-t-retrain-recipe/)
336. [**Collaborating with language models for embodied reasoning arXiv:2302.00763**Ishita Dasgupta, Christine Kaeser-Chen, Kenneth Marino, et al.*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/dasgupta-2023-collaborating-language-models-embodied-reasoning/)
337. **[Direct Judgement Preference Optimization](https://md.research.elamur.ai/free/en/papers/wang-2025-direct-judgement-preference-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**PeiFeng Wang, Austin Xu, Yilun Zhou, et al.*2025 · 35 citations*
338. [**Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap arXiv:2402.19450**Saurabh Srivastava, Annarose M B, Anto P, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2024-functional-benchmarks-robust-evaluation-reasoning/)
339. [**AgentGym: Evolving Large Language Model-based Agents across Diverse Environments arXiv:2406.04151**Zhiheng Xi, Yiwen Ding, Wenxiang Chen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/xi-2024-agentgym-evolving-large-language-model/)
340. [**The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input arXiv:2501.03200**Alon Jacovi, Andrew Wang, Chris Alberti, et al.*2025 · 32 citations*](https://md.research.elamur.ai/free/en/papers/jacovi-2025-facts-grounding-leaderboard-benchmarking-llms/)
341. [**ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild arXiv:2407.04172**Ahmed Masry, Megh Thakkar, Aayush Bajaj, et al.*2024 · 32 citations*](https://md.research.elamur.ai/free/en/papers/masry-2024-chartgemma-visual-instruction-tuning-chart/)
342. **[Derivational Morphology Reveals Analogical Generalization in Large Language Models](https://md.research.elamur.ai/free/en/papers/hofmann-2024-derivational-morphology-reveals-analogical-generalization/) [Proceedings of the National Academy of Sciences](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-national-academy-of-sciences/)**Valentin Hofmann, Leonie Weissweiler, David Mortensen, et al.*2024 · 32 citations*
343. **[SelfCodeAlign: Self-Alignment for Code Generation](https://md.research.elamur.ai/free/en/papers/wei-2024-selfcodealign-self-alignment-code-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxiang Wei, Federico Cassano, Jiawei Liu, et al.*2024 · 32 citations*
344. [**Nash Learning from Human Feedback arXiv:2312.00886**Remi Munos, Michal Valko, Daniele Calandriello, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/munos-2023-nash-learning-human-feedback/)
345. **[LiPO: Listwise Preference Optimization through Learning-to-Rank](https://md.research.elamur.ai/free/en/papers/liu-2025-lipo-listwise-preference-optimization-through/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tianqi Liu, Zhen Qin, Junru Wu, et al.*2025 · 31 citations*
346. [**A Survey of Small Language Models arXiv:2410.20011**Chien Van Nguyen, Xuan Shen, Ryan Aponte, et al.*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2024-survey-small-language-models/)
347. **[Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations](https://md.research.elamur.ai/free/en/papers/hagele-2024-scaling-laws-compute-optimal-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alexander Hägele, Elie Bakouch, Atli Kosson, et al.*2024 · 31 citations*
348. [**Weaver: Foundation Models for Creative Writing arXiv:2401.17268**Tiannan Wang; Jiamin Chen; Qingrui Jia; Shuai Wang; Ruoyu Fang; Huilin Wang; Zhaowei Gao; Chunzhao Xie; Chuou Xu; Jihong Dai; Yibin Liu; Jialong Wu; Shengwei Ding; Long Li; Zhiwei Huang; Xinle Deng; Teng Yu; Gangan Ma; Han Xiao; Zixin Chen; Danjun Xiang; Yunxia Wang; Yuanyuan Zhu; Yi Xiao; Jing Wang; Yiru Wang; Siran Ding; Jiayang Huang; Jiayi Xu; Yilihamu Tayier; Zhenyu Hu; Yuan Gao; Chengfeng Zheng; Yueshu Ye; Yihang Li; Lei Wan; Xinyue Jiang; Yujie Wang; Siyu Cheng; Zhule Song; Xiangru Tang; Xiaohua Xu; Ningyu Zhang; Huajun Chen; Yuchen Eleanor Jiang;, Wangchunshu Zhou*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-weaver-foundation-models-creative-writing/)
349. **[Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages](https://md.research.elamur.ai/free/en/papers/zhang-2024-enhancing-multilingual-capabilities-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanchi Zhang, Yile Wang, Zijun Liu, et al.*2024 · 30 citations*
350. [**Nemotron-4 15B Technical Report arXiv:2402.16819**Jupinder Parmar, Shrimai Prabhumoye, Joseph Jennings, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/parmar-2024-nemotron-4-15b-technical-report/)
351. **[ProxyQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/tan-2024-proxyqa-alternative-framework-evaluating-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Tan, Zhijiang Guo, Zhan Shi, et al.*2024 · 30 citations*
352. [**Efficient and Effective Vocabulary Expansion Towards Multilingual Large Language Models arXiv:2402.14714**Seungduk Kim, Seungtaek Choi, Myeongho Jeong*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-efficient-effective-vocabulary-expansion-towards/)
353. [**TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generation arXiv:2410.03608**Jonathan Cook, Tim Rocktaschel, Jakob Foerster, et al.*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/cook-2024-ticking-all-boxes-generated-checklists/)
354. [**Transformers Can Achieve Length Generalization But Not Robustly arXiv:2402.09371**Yongchao Zhou, Uri Alon, Xinyun Chen, et al.*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-transformers-achieve-length-generalization-but/)
355. [**T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling arXiv:2501.11651**Zhenyu Hou, Xin Lv, Rui Lu, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/hou-2025-t1-advancing-language-model-reasoning/)
356. **[ArMeme: Propagandistic Content in Arabic Memes](https://md.research.elamur.ai/free/en/papers/alam-2024-armeme-propagandistic-content-arabic-memes/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Firoj Alam, Abul Hasnat, Fatema Ahmad, et al.*2024 · 28 citations*
357. **[Can Large Language Models Unlock Novel Scientific Research Ideas?](https://md.research.elamur.ai/free/en/papers/kumar-2025-can-large-language-models-unlock/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sandeep Kumar, Tirthankar Ghosal, Vinayak Goyal, et al.*2025 · 27 citations*
358. **[LLM Agents Making Agent Tools](https://md.research.elamur.ai/free/en/papers/wolflein-2025-llm-agents-making-agent-tools/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Georg Wölflein, Dyke Ferber, Daniel Truhn, et al.*2025 · 27 citations*
359. [**LearnLM: Improving Gemini for learning**LearnLM Team*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/team-2024-learnlm-improving-gemini-learning/)
360. [**Sailor: Open Language Models for South-East Asia arXiv:2404.03608**Longxu Dou, Qian Liu, Guangtao Zeng, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/dou-2024-sailor-open-language-models-south/)
361. **[A Survey on Large Language Models for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-survey-large-language-models-mathematical/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Peng-Yuan Wang, Tian-Shuo Liu, Chenyang Wang, et al.*2025 · 26 citations*
362. **[Binary Classifier Optimization for Large Language Model Alignment](https://md.research.elamur.ai/free/en/papers/jung-2025-binary-classifier-optimization-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Seungjae Jung, Gunsoo Han, Daniel Wontae Nam, et al.*2025 · 26 citations*
363. **[TreeRL: LLM Reinforcement Learning with On-Policy Tree Search](https://md.research.elamur.ai/free/en/papers/hou-2025-treerl-llm-reinforcement-learning-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenyu Hou, Ziniu Hu, Yujiang Li, et al.*2025 · 26 citations*
364. [**Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent arXiv:2411.02265**Xingwu Sun, Yanfeng Chen, Yiqing Huang, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-hunyuan-large-open-source/)
365. [**AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks arXiv:2306.08107**Alexander Tornede, Difan Deng, Theresa Eimer, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/tornede-2023-automl-age-large-language-models/)
366. **[ChartCoder: Advancing Multimodal Large Language Model for Chart-to-Code Generation](https://md.research.elamur.ai/free/en/papers/zhao-2025-chartcoder-advancing-multimodal-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuanle Zhao, Xianzhen Luo, Qi Shi, et al.*2025 · 24 citations*
367. [**Beyond English-Centric LLMs: What Language Do Multilingual Language Models Think in? arXiv:2408.10811**Chengzhi Zhong, Fei Cheng, Qianying Liu, et al.*2024 · 24 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-english-centric-llms-language-multilingual/)
368. [**AI-Assisted Generation of Difficult Math Questions arXiv:2407.21009**Vedant Shah, Dingli Yu, Kaifeng Lyu, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/shah-2024-ai-assisted-generation-difficult-math/)
369. [**BOND: Aligning LLMs with Best-of-N Distillation arXiv:2407.14622**Pier Giuseppe Sessa, Robert Dadashi, Leonard Hussenot, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/sessa-2024-bond-aligning-llms-best-n/)
370. **[Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals](https://md.research.elamur.ai/free/en/papers/ortu-2024-competition-mechanisms-tracing-how-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Francesco Ortu, Zhijing Jin, Diego Doimo, et al.*2024 · 23 citations*
371. **[SemEval-2026 Task 11: Disentangling Content and Formal Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/valentino-2026-semeval-2026-task-11-disentangling/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Marco Valentino, Leonardo Ranaldi, Giulia Pucci, et al.*2026 · 22 citations*
372. **[AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark Dataset](https://md.research.elamur.ai/free/en/papers/nimo-2025-afrimed-qa-pan-african-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Charles Nimo, Tobi Olatunji, Abraham Toluwase Owodunni, et al.*2025 · 22 citations*
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374. **[Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token Recycling](https://md.research.elamur.ai/free/en/papers/luo-2025-turning-trash-into-treasure-accelerating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianzhen Luo, Yixuan Wang, Qingfu Zhu, et al.*2025 · 22 citations*
375. [**AI Sandbagging: Language Models can Strategically Underperform on Evaluations arXiv:2406.07358**Teun van der Weij, Felix Hofstatter, Ollie Jaffe, et al.*2024 · 22 citations*](https://md.research.elamur.ai/free/en/papers/weij-2024-ai-sandbagging-language-models-strategically/)
376. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
377. **[Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-multimodal-needle-haystack-benchmarking-long/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hengyi Wang, Haizhou Shi, Shiwei Tan, et al.*2025 · 21 citations*
378. **[PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/qiu-2025-phybench-holistic-evaluation-physical-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shi Qiu, Shaoyang Guo, Zhuo-Yang Song, et al.*2025 · 21 citations*
379. **[RuleArena: A Benchmark for Rule-Guided Reasoning with LLMs in Real-World Scenarios](https://md.research.elamur.ai/free/en/papers/zhou-2025-rulearena-benchmark-rule-guided-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiwen Zhou, Wenyue Hua, Liangming Pan, et al.*2025 · 21 citations*
380. [**MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning arXiv:2402.11260**Shu Yang; Muhammad Asif Ali; Cheng-Long Wang; Lijie Hu;, Di Wang*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-moral-moe-augmented-lora-llms/)
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382. **[CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/chen-2024-cofipara-coarse-fine-paradigm-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zixin Chen, Hongzhan Lin, Ziyang Luo, et al.*2024 · 20 citations*
383. [**MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific Understanding arXiv:2407.04903**Zekun Li, Xianjun Yang, Kyuri Choi, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-mmsci-dataset-graduate-level-multi/)
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385. [**Efficient RLHF: Reducing the Memory Usage of PPO arXiv:2309.00754**Michael Santacroce, Yadong Lu, Han Yu, et al.*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/santacroce-2023-efficient-rlhf-reducing-memory-usage/)
386. **[FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation](https://md.research.elamur.ai/free/en/papers/luo-2025-finmme-benchmark-dataset-financial-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyu Luo, Zhizhuo Kou, Liming Yang, et al.*2025 · 19 citations*
387. [**In-Context Principle Learning from Mistakes arXiv:2402.05403**Tianjun Zhang, Aman Madaan, Luyu Gao, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-context-principle-learning-mistakes/)
388. [**Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models arXiv:2405.02287**Piotr Padlewski, Max Bain, Matthew Henderson, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/padlewski-2024-vibe-eval-hard-evaluation-suite/)
389. **[OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization](https://md.research.elamur.ai/free/en/papers/he-2025-openwebvoyager-building-multimodal-web-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongliang He, Wenlin Yao, Kaixin Ma, et al.*2025 · 18 citations*
390. [**Chinchilla Scaling: A replication attempt arXiv:2404.10102**Tamay Besiroglu, Ege Erdil, Matthew Barnett, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/besiroglu-2024-chinchilla-scaling-replication-attempt/)
391. **[Propaganda to Hate: A Multimodal Analysis of Arabic Memes with Multi-Agent LLMs](https://md.research.elamur.ai/free/en/papers/alam-2024-propaganda-hate-multimodal-analysis-arabic/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Firoj Alam, Md. Rafiul Biswas, Uzair Shah, et al.*2024 · 18 citations*
392. [**Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning arXiv:2312.05230**Zhiting Hu, Tianmin Shu*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-language-models-agent-models-world/)
393. [**Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought arXiv:2504.05599**Yi Peng, Peiyu Wang, Xiaokun Wang, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/peng-2025-skywork-r1v-pioneering-multimodal/)
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395. **[OmniBench: Towards The Future of Universal Omni-Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-omnibench-towards-future-universal-omni/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yizhi Li, Yinghao Ma, Ge Zhang, et al.*2024 · 17 citations*
396. **[ActiveLLM: Large Language Model-Based Active Learning for Textual Few-Shot Scenarios](https://md.research.elamur.ai/free/en/papers/bayer-2026-activellm-large-language-model-based/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Markus Bayer, Justin Lutz, Christian Reuter*2026 · 16 citations*
397. **[CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome Reward](https://md.research.elamur.ai/free/en/papers/liu-2025-compassverifier-unified-robust-verifier-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shudong Liu, Hongwei Liu, Junnan Liu, et al.*2025 · 16 citations*
398. **[FactBench: A Dynamic Benchmark for In-the-Wild Language Model Factuality Evaluation](https://md.research.elamur.ai/free/en/papers/bayat-2025-factbench-dynamic-benchmark-wild-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Farima Fatahi Bayat, Lechen Zhang, Sheza Munir, et al.*2025 · 16 citations*
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400. [**Sparks of Science: Hypothesis Generation Using Structured Paper Data arXiv:2504.12976**Charles O'Neill, Tirthankar Ghosal, Roberta R\uaileanu, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/o-neill-2025-sparks-science-hypothesis-generation-using/)

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