---
title: "Who cites Mary Phuong — page 3 — 2,297 papers of our library"
description: "2,297 papers of the Elamur Research library cite the works of Mary Phuong, found in their bibliographies · page 3 of 7 · 201–300; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/mary-phuong/cited-by/page/3/"
---
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# Who cites Mary Phuong

2,319 citations of their works from 2,297 papers of our library (of the 149,439 whose bibliographies we read) · 636 with a page here, the most cited first · page 3 of 7 · 201–300 · [← Mary Phuong](https://md.research.elamur.ai/free/en/authors/mary-phuong/)

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201. **[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*
202. **[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*
203. [**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/)
204. **[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*
205. [**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/)
206. **[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*
207. [**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/)
208. **[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*
209. **[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*
210. [**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/)
211. [**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/)
212. [**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/)
213. [**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/)
214. [**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/)
215. [**Premise Order Matters in Reasoning with Large Language Models arXiv:2402.08939**Xinyun Chen, Ryan A. Chi, Xuezhi Wang, et al.*2024 · 58 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-premise-order-matters-reasoning-large/)
216. [**Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla arXiv:2307.09458**Tom Lieberum, Matthew Rahtz, Janos Kramar, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/lieberum-2023-circuit-analysis-interpretability-scale-evidence/)
217. **[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*
218. [**HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly arXiv:2410.02694**Howard Yen, Tianyu Gao, Minmin Hou, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/yen-2024-helmet-evaluate-long-context-language/)
219. [**StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models arXiv:2403.07714**Zhicheng Guo, Sijie Cheng, Hao Wang, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/guo-2024-stabletoolbench-towards-stable-large-scale/)
220. [**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/)
221. [**A Survey of Resource-efficient LLM and Multimodal Foundation Models arXiv:2401.08092**Mengwei Xu, Wangsong Yin, Dongqi Cai, et al.*2024 · 54 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-survey-resource-efficient-llm-multimodal/)
222. **[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*
223. **[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*
224. [**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/)
225. [**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/)
226. [**Towards responsible development of generative AI for education: An evaluation-driven approach**Jurenka*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/jurenka-2024-responsible-development-generative-ai-education/)
227. [**Reasoning Models Know When They're Right: Probing Hidden States for Self-Verification arXiv:2504.05419**Anqi Zhang, Yulin Chen, Jane Pan, et al.*2025 · 52 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-reasoning-models-know-they-re/)
228. **[VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2025-vl-rethinker-incentivizing-self-reflection/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Haozhe Wang, Chao Qu, Zuming Huang, et al.*2025 · 52 citations*
229. **[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*
230. [**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/)
231. [**How to Train Data-Efficient LLMs arXiv:2402.09668**Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/sachdeva-2024-train-data-efficient-llms/)
232. [**Zamba: A Compact 7B SSM Hybrid Model arXiv:2405.16712**Paolo Glorioso, Quentin Anthony, Yury Tokpanov, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/glorioso-2024-zamba-compact-7b-ssm-hybrid/)
233. [**MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning arXiv:2503.07365**Fanqing Meng, Lingxiao Du, Zongkai Liu, et al.*2025 · 49 citations*](https://md.research.elamur.ai/free/en/papers/meng-2025-mm-eureka-exploring-frontiers-multimodal/)
234. **[MathPile: A Billion-Token-Scale Pretraining Corpus for Math](https://md.research.elamur.ai/free/en/papers/wang-2023-mathpile-billion-token-scale-pretraining/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zengzhi Wang, Xuefeng Li, Rui Xia, et al.*2023 · 49 citations*
235. [**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/)
236. [**Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models arXiv:2406.02061**Marianna Nezhurina, Lucia Cipolina-Kun, Mehdi Cherti, et al.*2024 · 48 citations*](https://md.research.elamur.ai/free/en/papers/nezhurina-2024-alice-wonderland-simple-tasks-showing/)
237. **[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*
238. [**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/)
239. [**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/)
240. [**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/)
241. [**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/)
242. **[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*
243. [**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/)
244. [**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/)
245. [**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/)
246. **[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*
247. **[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*
248. [**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/)
249. **[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*
250. **[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*
251. **[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*
252. [**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/)
253. [**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/)
254. [**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/)
255. [**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/)
256. **[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*
257. **[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*
258. [**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/)
259. [**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/)
260. [**Introducing v0.5 of the AI Safety Benchmark from MLCommons arXiv:2404.12241**Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2024-introducing-v0-5-ai-safety/)
261. [**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/)
262. **[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*
263. **[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*
264. **[Measuring AI Ability to Complete Long Software Tasks](https://md.research.elamur.ai/free/en/papers/kwa-2025-measuring-ai-ability-complete/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Thomas Kwa, Ben West, Joel Becker, et al.*2025 · 36 citations*
265. [**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/)
266. [**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/)
267. **[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*
268. [**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/)
269. [**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/)
270. [**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/)
271. [**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/)
272. **[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*
273. **[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*
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275. [**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/)
276. **[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*
277. [**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/)
278. **[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*
279. [**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/)
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281. [**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/)
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287. [**LearnLM: Improving Gemini for learning**LearnLM Team*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/team-2024-learnlm-improving-gemini-learning/)
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291. [**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/)
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293. [**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/)
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