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title: "Who cites Think you have — page 4 — 1,933 citing papers"
description: "1933 papers of the Elamur Research library cite «Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge»…"
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# Who cites «Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge»

1933 papers of our library cite it (of the 149,439 whose bibliographies we read) · 491 with a page here, the most cited first · page 4 of 5 · 301–400 · [← back to «Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge»](https://md.research.elamur.ai/free/en/papers/clark-2018-think-have-solved-question-answering/)

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301. **[FedMKT: Federated Mutual Knowledge Transfer for Large and Small Language Models](https://md.research.elamur.ai/free/en/papers/fan-2025-fedmkt-federated-mutual-knowledge-transfer/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tao Fan, Guoqiang Ma, Yan Kang, et al.*2025 · 10 citations*
302. [**Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought arXiv:2505.15431**Tencent Hunyuan Team, Ao Liu, Botong Zhou, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-hunyuan-hunyuan-turbos-advancing-large/)
303. [**Implicit Reasoning in Large Language Models: A Comprehensive Survey arXiv:2509.02350**Jindong Li, Yali Fu, Li Fan, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-implicit-reasoning-large-language-models/)
304. [**JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models arXiv:2501.14851**Michael K. Chen, Xikun Zhang, Dacheng Tao*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-justlogic-comprehensive-benchmark-evaluating-deductive/)
305. [**Knowledge Distillation of Black-Box Large Language Models arXiv:2401.07013**Hongzhan Chen, Ruijun Chen, Yuqi Yi, et al.*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-knowledge-distillation-black-box-large/)
306. [**Debiasing Algorithm through Model Adaptation arXiv:2310.18913**Tomasz Limisiewicz, David Mareček, Tomaš Musil*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/limisiewicz-2023-debiasing-algorithm-through-model-adaptation/)
307. **[Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning](https://md.research.elamur.ai/free/en/papers/xu-2025-parenting-optimizing-knowledge-selection-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongxin Xu, Ruizhe Zhang, Xinke Jiang, et al.*2025 · 9 citations*
308. [**CTPD: Cross Tokenizer Preference Distillation arXiv:2601.11865**Truong Nguyen, Phi Van Dat, Ngan Nguyen, et al.*2026 · 8 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2026-ctpd-cross-tokenizer-preference-distillation/)
309. **[Faster MoE LLM Inference for Extremely Large Models](https://md.research.elamur.ai/free/en/papers/yang-2026-faster-moe-llm-inference-extremely/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoqi Yang, Luohe Shi, Qiwei Li, et al.*2026 · 8 citations*
310. **[Nature-Inspired Population-Based Evolution of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-nature-inspired-population-based-evolution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiqun Zhang, Peng Ye, Xiaocui Yang, et al.*2026 · 8 citations*
311. **[EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence Checking](https://md.research.elamur.ai/free/en/papers/wei-2025-equibench-benchmarking-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anjiang Wei, Jiannan Cao, Ran Li, et al.*2025 · 8 citations*
312. **[Genius: A Generalizable and Purely Unsupervised Self-Training Framework For Advanced Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2025-genius-generalizable-purely-unsupervised-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangzhi Xu, Hang Yan, Chang Ma, et al.*2025 · 8 citations*
313. **[Nudging: Inference-time Alignment of LLMs via Guided Decoding](https://md.research.elamur.ai/free/en/papers/fei-2025-nudging-inference-time-alignment-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Fei, Yasaman Razeghi, Sameer Singh*2025 · 8 citations*
314. **[On Many-Shot In-Context Learning for Long-Context Evaluation](https://md.research.elamur.ai/free/en/papers/zou-2025-many-shot-context-learning-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kaijian Zou, Muhammad Khalifa, Lu Wang*2025 · 8 citations*
315. [**PanGu-π Pro:Rethinking Optimization and Architecture for Tiny Language Models arXiv:2402.02791**Yehui Tang, Kai Han, Fangcheng Liu, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-pangu-pi-pro-rethinking/)
316. **[Beyond Random Sampling: Efficient Language Model Pretraining via Curriculum Learning](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-random-sampling-efficient-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yang Zhang, Amr Mohamed, Hadi Abdine, et al.*2026 · 7 citations*
317. **[DEBATE, TRAIN, EVOLVE: Self-Evolution of Language Model Reasoning](https://md.research.elamur.ai/free/en/papers/srivastava-2025-debate-train-evolve-self-evolution/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gaurav Srivastava, Zhenyu Bi, Meng Lu, et al.*2025 · 7 citations*
318. **[Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization](https://md.research.elamur.ai/free/en/papers/zhang-2025-get-confused-cautiously-textual-sequence/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zhaohan Zhang, Ziquan Liu, Ioannis Patras*2025 · 7 citations*
319. **[ICLEval: Evaluating In-Context Learning Ability of Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-icleval-evaluating-context-learning-ability/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Wentong Chen, Yankai Lin, ZhenHao Zhou, et al.*2025 · 7 citations*
320. [**MoM: Linear Sequence Modeling with Mixture-of-Memories arXiv:2502.13685**Jusen Du, Weigao Sun, Disen Lan, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/du-2025-mom-linear-sequence-modeling-mixture/)
321. **[NorEval: A Norwegian Language Understanding and Generation Evaluation Benchmark](https://md.research.elamur.ai/free/en/papers/mikhailov-2025-noreval-norwegian-language-understanding-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Vladislav Mikhailov, Tita Enstad, David Samuel, et al.*2025 · 7 citations*
322. **[WiCkeD: A Simple Method to Make Multiple Choice Benchmarks More Challenging](https://md.research.elamur.ai/free/en/papers/elhady-2025-wicked-simple-method-make-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ahmed Elhady, Eneko Agirre, Mikel Artetxe*2025 · 7 citations*
323. **[Enhancing Systematic Decompositional Natural Language Inference Using Informal Logic](https://md.research.elamur.ai/free/en/papers/weir-2024-enhancing-systematic-decompositional-natural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nathaniel Weir, Kate Sanders, Orion Weller, et al.*2024 · 7 citations*
324. [**FBI-LLM: Scaling Up Fully Binarized LLMs from Scratch via Autoregressive Distillation arXiv:2407.07093**Liqun Ma, Mingjie Sun, Zhiqiang Shen*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/ma-2024-fbi-llm-scaling-up-fully/)
325. [**GRIN: GRadient-INformed MoE arXiv:2409.12136**Liyuan Liu, Young Jin Kim, Shuohang Wang, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-grin-gradient-informed-moe/)
326. **[Demystifying Multi-Agent Debate: The Role of Confidence and Diversity](https://md.research.elamur.ai/free/en/papers/zhu-2026-demystifying-multi-agent-debate-role/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaochen Zhu, Caiqi Zhang, Yizhou Chi, et al.*2026 · 6 citations*
327. **[PDTrim: Targeted Pruning for Prefill-Decode Disaggregation in Inference](https://md.research.elamur.ai/free/en/papers/zhang-2026-pdtrim-targeted-pruning-prefill-decode/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Zhang, Lyu Mengsi, Zhuo Chen, et al.*2026 · 6 citations*
328. **[RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization](https://md.research.elamur.ai/free/en/papers/dong-2026-rl-plus-countering-capability-boundary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihong Dong, Xue Jiang, Yongding Tao, et al.*2026 · 6 citations*
329. **[Softpick: No Attention Sink, No Massive Activations with Rectified Softmax](https://md.research.elamur.ai/free/en/papers/zuhri-2026-softpick-no-attention-sink-no/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zayd Muhammad Kawakibi Zuhri, Erland Hilman Fuadi, Alham Fikri Aji*2026 · 6 citations*
330. **[Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2026-why-supervised-fine-tuning-fails/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 6 citations*
331. **[BeamLoRA: Beam-Constraint Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/gu-2025-beamlora-beam-constraint-low-rank/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Naibin Gu, Zhenyu Zhang, Xiyu Liu, et al.*2025 · 6 citations*
332. **[MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-metafaith-faithful-natural-language-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.*2025 · 6 citations*
333. [**Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUs arXiv:2504.07866**Yichun Yin, Wenyong Huang, Kaikai Song, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/yin-2025-pangu-ultra-pushing-limits/)
334. **[Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs](https://md.research.elamur.ai/free/en/papers/anshumann-2025-sparse-logit-sampling-accelerating-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anshumann, Mohd Abbas Zaidi, Akhil Kedia, et al.*2025 · 6 citations*
335. [**SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese arXiv:2401.11819**Liang Xu, Hang Xue, Lei Zhu, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-superclue-math6-graded-multi/)
336. **[ARCQuant: Boosting NVFP4 Quantization with Augmented Residual Channels for LLMs](https://md.research.elamur.ai/free/en/papers/meng-2026-arcquant-boosting-nvfp4-quantization-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoqian Meng, Yilun Luo, Yafei Zhao, et al.*2026 · 5 citations*
337. **[Exploring Layer-wise Information Effectiveness for Post-Training Quantization in Small Language Models](https://md.research.elamur.ai/free/en/papers/xiao-2026-exploring-layer-wise-information-effectiveness/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**He Xiao, Qingyao Yang, Dirui Xie, et al.*2026 · 5 citations*
338. **[Is Chain-of-Thought Really Not Explainability? Chain-of-Thought Can Be Faithful without Hint Verbalization](https://md.research.elamur.ai/free/en/papers/zaman-2026-is-chain-thought-really-not/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kerem Zaman, Shashank Srivastava*2026 · 5 citations*
339. **[Paramanu: Compact and Competitive Monolingual Language Models for Low-Resource Morphologically Rich Indian Languages](https://md.research.elamur.ai/free/en/papers/niyogi-2026-paramanu-compact-competitive-monolingual-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mitodru Niyogi, Eric Gaussier, Arnab Bhattacharya*2026 · 5 citations*
340. **[RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates](https://md.research.elamur.ai/free/en/papers/kowsher-2025-rocoft-efficient-finetuning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Md Kowsher, Tara Esmaeilbeig, Chun-Nam Yu, et al.*2025 · 5 citations*
341. **[SubLIME: Subset Selection via Rank Correlation Prediction for Data-Efficient LLM Evaluation](https://md.research.elamur.ai/free/en/papers/saranathan-2025-sublime-subset-selection-rank-correlation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gayathri Saranathan, Cong Xu, Mahammad Parwez Alam, et al.*2025 · 5 citations*
342. **[Aleph-Alpha-GermanWeb: Improving German-language LLM pre-training with model-based data curation and synthetic data generation](https://md.research.elamur.ai/free/en/papers/burns-2026-aleph-alpha-germanweb-improving-german/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Thomas F Burns, Letitia Parcalabescu, Stephan Waeldchen, et al.*2026 · 4 citations*
343. **[ProFit: Leveraging High-Value Signals in SFT via Probability-Guided Token Selection](https://md.research.elamur.ai/free/en/papers/liu-2026-profit-leveraging-high-value-signals/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tao Liu, Taiqiang Wu, Runming Yang, et al.*2026 · 4 citations*
344. **[CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation Backdoor](https://md.research.elamur.ai/free/en/papers/xu-2025-ctcc-robust-stealthy-fingerprinting-framework/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenhua Xu, Xixiang Zhao, Xubin Yue, et al.*2025 · 4 citations*
345. [**Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs arXiv:2503.05139**Ling Team; Binwei Zeng; Chao Huang; Chao Zhang; Changxin Tian; Cong Chen; Dingnan Jin; Feng Yu; Feng Zhu; Feng Yuan; Fakang Wang; Gangshan Wang; Guangyao Zhai; Haitao Zhang; Huizhong Li; Jun Zhou; Jia Liu; Junpeng Fang; Junjie Ou; Jun Hu; Ji Luo; Ji Zhang; Jian Liu; Jian Sha; Jianxue Qian; Jiewei Wu; Junping Zhao; Jianguo Li; Jubao Feng; Jingchao Di; Junming Xu; Jinghua Yao; Kuan Xu; Kewei Du; Longfei Li; Lei Liang; Lu Yu; Li Tang; Lin Ju; Peng Xu; Qing Cui; Song Liu; Shicheng Li; Shun Song; Song Yan; Tengwei Cai; Tianyi Chen; Ting Guo; Ting Huang; Tao Feng; Tao Wu; Wei Wu; Xiaolu Zhang; Xueming Yang; Xin Zhao; Xiaobo Hu; Xin Lin; Yao Zhao; Yilong Wang; Yongzhen Guo; Yuanyuan Wang; Yue Yang; Yang Cao; Yuhao Fu; Yi Xiong; Yanzhe Li; Zhe Li; Zhiqiang Zhang; Ziqi Liu; Zhaoxin Huan; Zujie Wen; Zhenhang Sun; Zhuoxuan Du;, Zhengyu He*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/ling-team-2025-every-flop-counts-scaling/)
346. [**Llama-GENBA-10B: A Trilingual Large Language Model for German, English and Bavarian arXiv:2509.05668**Michael Hoffmann, Jophin John, Stefan Schweter, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/hoffmann-2025-llama-genba-10b-trilingual-large/)
347. [**GemmAr: Enhancing LLMs Through Arabic Instruction-Tuning arXiv:2407.02147**Hasna Chouikhi, Manel Aloui, Cyrine Ben Hammou, et al.*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/chouikhi-2024-gemmar-enhancing-llms-through-arabic/)
348. **[Balancing Fidelity and Plasticity: Aligning Mixed-Precision Fine-Tuning with Linguistic Hierarchies](https://md.research.elamur.ai/free/en/papers/zhou-2026-balancing-fidelity-plasticity-aligning-mixed/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Changhai Zhou, Shiyang Zhang, Yuhua Zhou, et al.*2026 · 3 citations*
349. **[J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/xu-2026-j4r-learning-judge-equivalent-initial/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Austin Xu, Yilun Zhou, Xuan-Phi Nguyen, et al.*2026 · 3 citations*
350. **[Learning While Staying Curious: Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/wang-2026-learning-while-staying-curious-entropy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Wang, Hao Gu, Hongming Piao, et al.*2026 · 3 citations*
351. **[Not All Directions Matter: Towards Structured and Task-Aware Low-Rank Model Adaptation](https://md.research.elamur.ai/free/en/papers/xiao-2026-not-all-directions-matter-structured/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xi Xiao, Chenrui Ma, Yunbei Zhang, et al.*2026 · 3 citations*
352. **[REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once](https://md.research.elamur.ai/free/en/papers/pan-2026-rest-stress-testing-large-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhuoshi Pan, Qizhi Pei, Yu Li, et al.*2026 · 3 citations*
353. **[Rethinking Prompt Optimizers: From Prompt Merits to Optimization](https://md.research.elamur.ai/free/en/papers/zhu-2026-rethinking-prompt-optimizers-prompt-merits/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zixiao Zhu, Hanzhang Zhou, Zijian Feng, et al.*2026 · 3 citations*
354. **[Sparse Brains are Also Adaptive Brains: Cognitive-Load-Aware Dynamic Activation for LLMs](https://md.research.elamur.ai/free/en/papers/yang-2026-sparse-brains-are-also-adaptive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiheng Yang, Yujie Wang, Chi Ma, et al.*2026 · 3 citations*
355. **[Trans-EnV: A Framework for Evaluating the Linguistic Robustness of LLMs Against English Varieties](https://md.research.elamur.ai/free/en/papers/lee-2025-trans-env-framework-evaluating-linguistic/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiyoung Lee, Seungho Kim, Jieun Han, et al.*2025 · 3 citations*
356. [**A Sovereign, Open-Source Foundation Model for German and English arXiv:2607.09424**Soofi-Team: Benedikt Droste, David Fitzek, Ruben Harle, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/droste-2026-sovereign-open-source-foundation-model/)
357. [**Dicta-LM 3.0: Advancing The Frontier of Hebrew Sovereign LLMs**Shaltiel Shmidman, Avi Shmidman, Amir DN Cohen, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2026-dicta-lm-3-0-advancing/)
358. **[From 2:4 to 8:16 sparsity patterns in LLMs for Outliers and Weights with Variance Correction](https://md.research.elamur.ai/free/en/papers/maximov-2026-2-4-8-16-sparsity/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Egor Maximov, Yulia Kuzkina, Egor Shvetsov, et al.*2026 · 2 citations*
359. **[Improving Romanian LLM Pretraining Data using Diversity and Quality Filtering](https://md.research.elamur.ai/free/en/papers/negoita-2026-improving-romanian-llm-pretraining-data/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Vlad-Andrei Negoiță, Mihai Masala, Traian Rebedea*2026 · 2 citations*
360. **[Lizard: An Efficient Linearization Framework for Large Language Models](https://md.research.elamur.ai/free/en/papers/nguyen-2026-lizard-efficient-linearization-framework-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chien Van Nguyen, Huy Huu Nguyen, Ruiyi Zhang, et al.*2026 · 2 citations*
361. [**MiniMax Sparse Attention arXiv:2606.13392**Xunhao Lai, Weiqi Xu, Yufeng Yang, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/lai-2026-minimax-sparse-attention/)
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