---
title: "Who cites Ed H. Chi — page 3 — 1,423 papers of our library"
description: "1,423 papers of the Elamur Research library cite the works of Ed H. Chi, found in their bibliographies · page 3 of 4 · 201–300; the most cited first."
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---
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# Who cites Ed H. Chi

1,448 citations of their works from 1,423 papers of our library (of the 149,439 whose bibliographies we read) · 341 with a page here, the most cited first · page 3 of 4 · 201–300 · [← Ed H. Chi](https://md.research.elamur.ai/free/en/authors/ed-h-chi/)

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201. [**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/)
202. [**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/)
203. **[Disentangling Memory and Reasoning Ability in Large Language Models](https://md.research.elamur.ai/free/en/papers/jin-2025-disentangling-memory-reasoning-ability-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingyu Jin, Weidi Luo, Sitao Cheng, et al.*2025 · 45 citations*
204. [**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/)
205. **[Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2023-language-models-improve-event-prediction/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoming Shi, Siqiao Xue, Kangrui Wang, et al.*2023 · 44 citations*
206. **[Improving Chain-of-Thought Reasoning via Quasi-Symbolic Abstractions](https://md.research.elamur.ai/free/en/papers/ranaldi-2025-improving-chain-thought-reasoning-quasi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leonardo Ranaldi, Marco Valentino, Andre Freitas*2025 · 42 citations*
207. [**Transcending Scaling Laws with 0.1% Extra Compute arXiv:2210.11399**Yi Tay, Jason Wei, Hyung Won Chung, et al.*2022 · 42 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-transcending-scaling-laws-0-1/)
208. [**Auxiliary task demands mask the capabilities of smaller language models arXiv:2404.02418**Jennifer Hu, Michael C. Frank*2024 · 41 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-auxiliary-task-demands-mask-capabilities/)
209. **[Do Language Models Enjoy Their Own Stories? Prompting Large Language Models for Automatic Story Evaluation](https://md.research.elamur.ai/free/en/papers/chhun-2024-do-language-models-enjoy-their/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Cyril Chhun, Fabian M. Suchanek, Chloé Clavel*2024 · 41 citations*
210. **[MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks](https://md.research.elamur.ai/free/en/papers/nie-2023-moca-measuring-human-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Allen Nie, Yuhui Zhang, Atharva Amdekar, et al.*2023 · 41 citations*
211. [**Observational Scaling Laws and the Predictability of Language Model Performance arXiv:2405.10938**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
212. **[Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts](https://md.research.elamur.ai/free/en/papers/tan-2024-personalized-pieces-efficient-personalized-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaoxuan Tan, Zheyuan Liu, Meng Jiang*2024 · 40 citations*
213. [**PanGu-{\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing arXiv:2303.10845**Xiaozhe Ren, Pingyi Zhou, Xinfan Meng, et al.*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ren-2023-pangu-sigma-trillion-parameter/)
214. [**Do large language models resemble humans in language use? arXiv:2303.08014**Zhenguang G. Cai, Xufeng Duan, David A. Haslett, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/cai-2023-large-language-models-resemble-humans/)
215. **[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*
216. **[Towards Effective Disambiguation for Machine Translation with Large Language Models](https://md.research.elamur.ai/free/en/papers/iyer-2023-effective-disambiguation-machine-translation-large/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Vivek Iyer, Pinzhen Chen, Alexandra Birch*2023 · 38 citations*
217. **[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*
218. [**An Emulator for Fine-Tuning Large Language Models using Small Language Models arXiv:2310.12962**Eric Mitchell, Rafael Rafailov, Archit Sharma, et al.*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/mitchell-2023-emulator-fine-tuning-large-language/)
219. **[ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios](https://md.research.elamur.ai/free/en/papers/ye-2025-tooleyes-fine-grained-evaluation-tool/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Junjie Ye, Guanyu Li, SongYang Gao, et al.*2025 · 35 citations*
220. [**On the Diversity of Synthetic Data and its Impact on Training Large Language Models arXiv:2410.15226**Hao Chen, Abdul Waheed, Xiang Li, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-diversity-synthetic-data-impact-training/)
221. **[Self-Refine Instruction-Tuning for Aligning Reasoning in Language Models](https://md.research.elamur.ai/free/en/papers/ranaldi-2024-self-refine-instruction-tuning-aligning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Leonardo Ranaldi, Andre Freitas*2024 · 35 citations*
222. [**Through the Lens of Core Competency: Survey on Evaluation of Large Language Models arXiv:2308.07902**Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-through-lens-core-competency-survey/)
223. [**Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation arXiv:2306.05783**Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-xiezhi-ever-updating-benchmark/)
224. [**Augmented Large Language Models with Parametric Knowledge Guiding arXiv:2305.04757**Ziyang Luo, Can Xu, Pu Zhao, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-augmented-large-language-models-parametric/)
225. **[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*
226. [**Towards Reasoning in Large Language Models via Multi-Agent Peer Review Collaboration arXiv:2311.08152**Zhenran Xu, Senbao Shi, Baotian Hu, et al.*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-towards-reasoning-large-language-models/)
227. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/)
228. **[AutoPSV: Automated Process-Supervised Verifier](https://md.research.elamur.ai/free/en/papers/lu-2024-autopsv-automated-process-supervised-verifier/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jianqiao Lu, Zhiyang Dou, Hongru Wang, et al.*2024 · 28 citations*
229. [**Pushing the Limits of ChatGPT on NLP Tasks arXiv:2306.09719**Xiaofei Sun, Linfeng Dong, Xiaoya Li, et al.*2023 · 28 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-pushing-limits-chatgpt-nlp-tasks/)
230. **[L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/ni-2024-l2ceval-evaluating-language-code-generation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ansong Ni, Pengcheng Yin, Yilun Zhao, et al.*2024 · 27 citations*
231. [**Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling arXiv:2408.16737**Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2024-smaller-weaker-yet-better-training/)
232. [**DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning arXiv:2310.02954**Jing Xiong, Zixuan Li, Chuanyang Zheng, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-dq-lore-dual-queries-low/)
233. **[S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/ma-2025-s-2-r-teaching-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruotian Ma, Peisong Wang, Cheng Liu, et al.*2025 · 26 citations*
234. [**Sentiment Analysis through LLM Negotiations arXiv:2311.01876**Xiaofei Sun, Xiaoya Li, Shengyu Zhang, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-sentiment-analysis-through-llm-negotiations/)
235. **[IberoBench: A Benchmark for LLM Evaluation in Iberian Languages](https://md.research.elamur.ai/free/en/papers/baucells-2025-iberobench-benchmark-llm-evaluation-iberian/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Irene Baucells, Javier Aula-Blasco, Iria de-Dios-Flores, et al.*2025 · 24 citations*
236. [**MiMo-Audio: Audio Language Models are Few-Shot Learners arXiv:2512.23808**Xiaomi LLM-Core Team, Dong Zhang, Gang Wang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/)
237. **[DDK: Distilling Domain Knowledge for Efficient Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2024-ddk-distilling-domain-knowledge-efficient/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaheng Liu, Chenchen Zhang, Jinyang Guo, et al.*2024 · 23 citations*
238. **[What is the Role of Small Models in the LLM Era: A Survey](https://md.research.elamur.ai/free/en/papers/chen-2024-role-small-models-llm-era/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Lihu Chen, Gael Varoquaux*2024 · 23 citations*
239. [**MiniCPM4: Ultra-Efficient LLMs on End Devices arXiv:2506.07900**MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/minicpm-team-2025-minicpm4-ultra-efficient-llms/)
240. [**InstructAlign: High-and-Low Resource Language Alignment via Continual Crosslingual Instruction Tuning arXiv:2305.13627**Samuel Cahyawijaya, Holy Lovenia, Tiezheng Yu, et al.*2023 · 22 citations*](https://md.research.elamur.ai/free/en/papers/cahyawijaya-2023-instructalign-high-low-resource-language/)
241. [**Personality Alignment of Large Language Models arXiv:2408.11779**Minjun Zhu, Yixuan Weng, Linyi Yang, et al.*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2024-personality-alignment-large-language-models/)
242. [**Understanding Emergent In-Context Learning from a Kernel Regression Perspective arXiv:2305.12766**Chi Han, Ziqi Wang, Han Zhao, et al.*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/han-2023-understanding-emergent-context-learning-kernel/)
243. **[AGrail: A Lifelong Agent Guardrail with Effective and Adaptive Safety Detection](https://md.research.elamur.ai/free/en/papers/luo-2025-agrail-lifelong-agent-guardrail-effective/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weidi Luo, Shenghong Dai, Xiaogeng Liu, et al.*2025 · 20 citations*
244. **[RARE: Retrieval-Augmented Reasoning Enhancement for Large Language Models](https://md.research.elamur.ai/free/en/papers/tran-2025-rare-retrieval-augmented-reasoning-enhancement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hieu Tran, Zonghai Yao, Zhichao Yang, et al.*2025 · 20 citations*
245. [**GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents arXiv:2406.06613**Anthony Costarelli, Mat Allen, Roman Hauksson, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/costarelli-2024-gamebench-evaluating-strategic-reasoning-abilities/)
246. [**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/)
247. [**sDPO: Don't Use Your Data All at Once arXiv:2403.19270**Dahyun Kim, Yungi Kim, Wonho Song, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-sdpo-don-t-use-data/)
248. [**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/)
249. **[A Survey of Post-Training Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/lai-2025-survey-post-training-scaling-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanyu Lai, Xiao Liu, Junjie Gao, et al.*2025 · 18 citations*
250. **[ARN: Analogical Reasoning on Narratives](https://md.research.elamur.ai/free/en/papers/sourati-2024-arn-analogical-reasoning-narratives/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zhivar Sourati, Filip Ilievski, Pia Sommerauer, et al.*2024 · 17 citations*
251. [**Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models arXiv:2308.00304**Jiaao Chen, Xiaoman Pan, Dian Yu, et al.*2023 · 17 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-skills-context-prompting-unlocking-compositionality/)
252. [**Towards Reasoning Ability of Small Language Models arXiv:2502.11569**Gaurav Srivastava, Shuxiang Cao, Xuan Wang*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2025-towards-reasoning-ability-small-language/)
253. **[Analyzing and Adapting Large Language Models for Few-Shot Multilingual NLU: Are We There Yet?](https://md.research.elamur.ai/free/en/papers/razumovskaia-2025-analyzing-adapting-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Evgeniia Razumovskaia, Ivan Vulić, Anna Korhonen*2025 · 15 citations*
254. **[LLMs Know What They Need: Leveraging a Missing Information Guided Framework to Empower Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2025-llms-know-what-they-need/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Keheng Wang, Feiyu Duan, Peiguang Li, et al.*2025 · 14 citations*
255. [**Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes On arXiv:2407.08348**Liang Zeng, Liangjun Zhong, Liang Zhao, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-skywork-math-data-scaling-laws/)
256. [**TaCo: Enhancing Cross-Lingual Transfer for Low-Resource Languages in LLMs through Translation-Assisted Chain-of-Thought Processes arXiv:2311.10797**Bibek Upadhayay, Vahid Behzadan*2023 · 14 citations*](https://md.research.elamur.ai/free/en/papers/upadhayay-2023-taco-enhancing-cross-lingual-transfer/)
257. **[Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction](https://md.research.elamur.ai/free/en/papers/shi-2026-discovering-gems-early-layers-accelerating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenmei Shi, Yifei Ming, Xuan-Phi Nguyen, et al.*2026 · 13 citations*
258. **[Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation](https://md.research.elamur.ai/free/en/papers/kim-2024-paralinguistics-aware-speech-empowered-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Heeseung Kim, Soonshin Seo, Kyeongseok Jeong, et al.*2024 · 13 citations*
259. **[REARANK: Reasoning Re-ranking Agent via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zhang-2025-rearank-reasoning-re-ranking-agent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Le Zhang, Bo Wang, Xipeng Qiu, et al.*2025 · 12 citations*
260. [**Fanar 2.0: Arabic Generative AI Stack arXiv:2603.16397**FANAR TEAM, Ummar Abbas, Mohammad Shahmeer Ahmad, et al.*2026 · 11 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-fanar-2-0-arabic-generative/)
261. **[Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?](https://md.research.elamur.ai/free/en/papers/pan-2025-can-llm-watermarks-robustly-prevent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leyi Pan, Aiwei Liu, Shiyu Huang, et al.*2025 · 11 citations*
262. **[Do Large Language Models Mirror Cognitive Language Processing?](https://md.research.elamur.ai/free/en/papers/ren-2025-do-large-language-models-mirror/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yuqi Ren, Renren Jin, Tongxuan Zhang, et al.*2025 · 11 citations*
263. [**CLEVA: Chinese Language Models EVAluation Platform arXiv:2308.04813**Yanyang Li, Jianqiao Zhao, Duo Zheng, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-cleva-chinese-language-models/)
264. [**Could Thinking Multilingually Empower LLM Reasoning? arXiv:2504.11833**Changjiang Gao, Xu Huang, Wenhao Zhu, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-could-thinking-multilingually-empower-llm/)
265. **[Factual Dialogue Summarization via Learning from Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2025-factual-dialogue-summarization-learning-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Rongxin Zhu, Jey Han Lau, Jianzhong Qi*2025 · 10 citations*
266. [**PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation arXiv:2312.17276**Yunhe Wang, Hanting Chen, Yehui Tang, et al.*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-pangu-pi-enhancing-language/)
267. **[MTR-Bench: A Comprehensive Benchmark for Multi-Turn Reasoning Evaluation](https://md.research.elamur.ai/free/en/papers/li-2026-mtr-bench-comprehensive-benchmark-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyuan Li, Keqin Bao, Yubo Ma, et al.*2026 · 9 citations*
268. **[A Comprehensive Survey of Contemporary Arabic Sentiment Analysis: Methods, Challenges, and Future Directions](https://md.research.elamur.ai/free/en/papers/shi-2025-comprehensive-survey-contemporary-arabic-sentiment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiqiang Shi, Ruchit Agrawal*2025 · 9 citations*
269. **[ReCreate: Reasoning and Creating Domain Agents Driven by Experience](https://md.research.elamur.ai/free/en/papers/hao-2026-recreate-reasoning-creating-domain-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhezheng Hao, Hong Wang, Jian Luo, et al.*2026 · 8 citations*
270. **[Superficial Self-Improved Reasoners Benefit from Model Merging](https://md.research.elamur.ai/free/en/papers/yuan-2025-superficial-self-improved-reasoners-benefit/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiangchi Yuan, Chunhui Zhang, Zheyuan Liu, et al.*2025 · 8 citations*
271. **[The Nature of NLP: Analyzing Contributions in NLP Papers](https://md.research.elamur.ai/free/en/papers/pramanick-2025-nature-nlp-analyzing-contributions-nlp/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aniket Pramanick, Yufang Hou, Saif M. Mohammad, et al.*2025 · 8 citations*
272. **[Unveiling Language Competence Neurons: A Psycholinguistic Approach to Model Interpretability](https://md.research.elamur.ai/free/en/papers/duan-2025-unveiling-language-competence-neurons-psycholinguistic/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Xufeng Duan, Xinyu Zhou, Bei Xiao, et al.*2025 · 8 citations*
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290. [**Fine-Tashkeel: Finetuning Byte-Level Models for Accurate Arabic Text Diacritization arXiv:2303.14588**Bashar Al-Rfooh, Gheith Abandah, Rami Al-Rfou*2023 · 2 citations*](https://md.research.elamur.ai/free/en/papers/al-rfooh-2023-fine-tashkeel-finetuning-byte-level/)
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