---
title: "Who cites Piotr Stanczyk — page 4 — 4,506 papers of our library"
description: "4,506 papers of the Elamur Research library cite the works of Piotr Stanczyk, found in their bibliographies · page 4 of 13 · 301–400; the most…"
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---
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# Who cites Piotr Stanczyk

4,822 citations of their works from 4,506 papers of our library (of the 149,439 whose bibliographies we read) · 1,207 with a page here, the most cited first · page 4 of 13 · 301–400 · [← Piotr Stanczyk](https://md.research.elamur.ai/free/en/authors/piotr-stanczyk/)

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301. **[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*
302. [**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/)
303. [**A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems arXiv:2504.09037**Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/ke-2025-survey-frontiers-llm-reasoning-inference/)
304. [**NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model arXiv:2508.14444**NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/basant-2025-nvidia-nemotron-nano-2-accurate/)
305. **[Dual-Space Knowledge Distillation for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-dual-space-knowledge-distillation-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Songming Zhang, Xue Zhang, Zengkui Sun, et al.*2024 · 39 citations*
306. [**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/)
307. [**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/)
308. [**Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models arXiv:2504.03624**NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.*2025 · 38 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-h-family-accurate-efficient/)
309. **[Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?](https://md.research.elamur.ai/free/en/papers/zeng-2025-revisiting-test-time-scaling-o1/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.*2025 · 38 citations*
310. [**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/)
311. [**Self-Distilled RLVR arXiv:2604.03128**Chenxu Yang, Chuanyu Qin, Qingyi Si, et al.*2026 · 37 citations*](https://md.research.elamur.ai/free/en/papers/yang-2026-self-distilled-rlvr/)
312. **[AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling](https://md.research.elamur.ai/free/en/papers/liu-2025-acemath-advancing-frontier-math-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Liu, Yang Chen, Mohammad Shoeybi, et al.*2025 · 37 citations*
313. **[CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklists](https://md.research.elamur.ai/free/en/papers/lee-2025-checkeval-reliable-llm-as-judge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yukyung Lee, JoongHoon Kim, Jaehee Kim, et al.*2025 · 37 citations*
314. **[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*
315. [**MiMo: Unlocking the Reasoning Potential of Language Model — From Pretraining to Posttraining arXiv:2505.07608**LLM-Core Xiaomi, Bingquan Xia, Bowen Shen, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/xiaomi-2025-mimo-unlocking-reasoning-potential-language/)
316. [**On-Policy Context Distillation for Language Models arXiv:2602.12275**Tianzhu Ye, Li Dong, Xun Wu, et al.*2026 · 36 citations*](https://md.research.elamur.ai/free/en/papers/ye-2026-policy-context-distillation-language-models/)
317. **[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*
318. **[KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding](https://md.research.elamur.ai/free/en/papers/xu-2025-kodcode-diverse-challenging-verifiable-synthetic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangchen Xu, Yang Liu, Yueqin Yin, et al.*2025 · 36 citations*
319. [**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/)
320. [**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/)
321. **[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*
322. [**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/)
323. [**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/)
324. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
325. [**Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective arXiv:2412.14135**Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-scaling-search-learning-roadmap-reproduce/)
326. **[Benchmarking Linguistic Diversity of Large Language Models](https://md.research.elamur.ai/free/en/papers/guo-2025-benchmarking-linguistic-diversity-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yanzhu Guo, Guokan Shang, Chloé Clavel*2025 · 32 citations*
327. [**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/)
328. [**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/)
329. **[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*
330. **[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*
331. [**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/)
332. [**Revisiting On-Policy Distillation: Empirical Failure Modes and Simple Fixes arXiv:2603.25562**Yuqian Fu, Haohuan Huang, Kaiwen Jiang, et al.*2026 · 31 citations*](https://md.research.elamur.ai/free/en/papers/fu-2026-revisiting-policy-distillation-empirical-failure/)
333. **[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*
334. [**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/)
335. [**How to Evaluate Reward Models for RLHF arXiv:2410.14872**Evan Frick, Tianle Li, Connor Chen, et al.*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/frick-2024-evaluate-reward-models-rlhf/)
336. **[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*
337. [**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/)
338. **[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*
339. [**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/)
340. **[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*
341. [**RMB: Comprehensively Benchmarking Reward Models in LLM Alignment arXiv:2410.09893**Enyu Zhou, Guodong Zheng, Binghai Wang, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-rmb-comprehensively-benchmarking-reward-models/)
342. **[SEA-LION: Southeast Asian Languages in One Network](https://md.research.elamur.ai/free/en/papers/ng-2025-sea-lion-southeast-asian-languages/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Raymond Ng, Thanh Ngan Nguyen, Huang Yuli, et al.*2025 · 29 citations*
343. [**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/)
344. [**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/)
345. [**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/)
346. **[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*
347. **[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*
348. **[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*
349. **[Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformers](https://md.research.elamur.ai/free/en/papers/dumas-2025-separating-tongue-thought-activation-patching/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Clément Dumas, Chris Wendler, Veniamin Veselovsky, et al.*2025 · 27 citations*
350. **[Towards the Law of Capacity Gap in Distilling Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-law-capacity-gap-distilling-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chen Zhang, Qiuchi Li, Dawei Song, et al.*2025 · 27 citations*
351. [**LearnLM: Improving Gemini for learning**LearnLM Team*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/team-2024-learnlm-improving-gemini-learning/)
352. [**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/)
353. [**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/)
354. **[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*
355. [**Distillation Scaling Laws arXiv:2502.08606**Dan Busbridge, Amitis Shidani, Floris Weers, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/busbridge-2025-distillation-scaling-laws/)
356. **[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*
357. **[OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment](https://md.research.elamur.ai/free/en/papers/liu-2026-openrubrics-scalable-synthetic-rubric-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianci Liu, Ran Xu, Tony Yu, et al.*2026 · 25 citations*
358. **[FuseChat: Knowledge Fusion of Chat Models](https://md.research.elamur.ai/free/en/papers/wan-2025-fusechat-knowledge-fusion-chat-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fanqi Wan, Longguang Zhong, Ziyi Yang, et al.*2025 · 25 citations*
359. [**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/)
360. [**Baichuan-M1: Pushing the Medical Capability of Large Language Models arXiv:2502.12671**Bingning Wang, Haizhou Zhao, Huozhi Zhou, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-baichuan-m1-pushing-medical/)
361. **[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*
362. **[A Survey of Large Language Models for Arabic Language and its Dialects](https://md.research.elamur.ai/free/en/papers/mashaabi-2024-survey-large-language-models-arabic/) [ACM Transactions on Asian and Low-Resource Language Information Processing](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-asian-and-low-resource-language-information-processing/)**Malak Mashaabi, Shahad Al-Khalifa, Hend Al-Khalifa*2024 · 24 citations*
363. [**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/)
364. **[AICD Bench: A Challenging Benchmark for AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/orel-2026-aicd-bench-challenging-benchmark-ai/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 23 citations*
365. **[CBT-Bench: Evaluating Large Language Models on Assisting Cognitive Behavior Therapy](https://md.research.elamur.ai/free/en/papers/zhang-2025-cbt-bench-evaluating-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Mian Zhang, Xianjun Yang, Xinlu Zhang, et al.*2025 · 23 citations*
366. [**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/)
367. [**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/)
368. **[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*
369. **[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*
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373. [**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/)
374. [**Scaling Latent Reasoning via Looped Language Models arXiv:2510.25741**Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-scaling-latent-reasoning-looped-language/)
375. **[The Leaderboard Illusion](https://md.research.elamur.ai/free/en/papers/singh-2025-leaderboard-illusion/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shivalika Singh, Yiyang Nan, Alex Wang, et al.*2025 · 22 citations*
376. **[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*
377. [**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/)
378. **[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*
379. [**CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction arXiv:2502.07316**Junlong Li, Daya Guo, Dejian Yang, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-codei-o-condensing-reasoning/)
380. **[KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding](https://md.research.elamur.ai/free/en/papers/heakl-2025-kitab-bench-comprehensive-multi-domain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ahmed Heakl, Muhammad Abdullah Sohail, Mukul Ranjan, et al.*2025 · 21 citations*
381. **[MMLU-CF: A Contamination-free Multi-task Language Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/zhao-2025-mmlu-cf-contamination-free-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qihao Zhao, Yangyu Huang, Tengchao Lv, et al.*2025 · 21 citations*
382. **[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*
383. **[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*
384. **[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*
385. [**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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387. **[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*
388. [**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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390. [**Self-Improvement in Language Models: The Sharpening Mechanism arXiv:2412.01951**Audrey Huang; Adam Block; Dylan J. Foster; Dhruv Rohatgi; Cyril Zhang; Max Simchowitz; Jordan T. Ash;, Akshay Krishnamurthy*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-self-improvement-language-models-sharpening/)
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392. [**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/)
393. [**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/)
394. [**Scaling Reasoning Efficiently via Relaxed On-Policy Distillation arXiv:2603.11137**Jongwoo Ko, Sara Abdali, Young Jin Kim, et al.*2026 · 18 citations*](https://md.research.elamur.ai/free/en/papers/ko-2026-scaling-reasoning-efficiently-relaxed-policy/)
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398. [**Do Large Language Models Understand Word Senses?**Domenico Meconi, Simone Stirpe, Federico Martelli*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/meconi-2025-llms-word-senses/)
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400. **[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*

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