---
title: "Who cites Lingjun Liu — 3,707 papers of our library"
description: "3,707 papers of the Elamur Research library cite the works of Lingjun Liu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/lingjun-liu/cited-by/"
---
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# Who cites Lingjun Liu

4,260 citations of their works from 3,707 papers of our library (of the 141,840 whose bibliographies we read) · 98 with a page here, the most cited first · [← Lingjun Liu](https://md.research.elamur.ai/free/en/authors/lingjun-liu/)

1. [**Qwen3 Technical Report arXiv:2505.09388**An Yang, Anfeng Li, Baosong Yang, et al.*2025 · 3,276 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-qwen3-technical-report/)
2. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,863 citations*
3. [**DAPO: An Open-Source LLM Reinforcement Learning System at Scale arXiv:2503.14476**Qiying Yu, Zheng Zhang, Ruofei Zhu, et al.*2025 · 634 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-dapo-open-source-llm-reinforcement/)
4. **[s1: Simple test-time scaling](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.*2025 · 584 citations*
5. **[Instruction Tuning for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 517 citations*
6. **[Large Language Models for Information Retrieval: A Survey](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 335 citations*
7. [**Kimi K2: Open Agentic Intelligence arXiv:2507.20534**Kimi Team, Yifan Bai, Yiping Bao, et al.*2025 · 331 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k2-open-agentic/)
8. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning arXiv:2503.09516**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 303 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
9. [**Understanding R1-Zero-Like Training: A Critical Perspective arXiv:2503.20783**Zichen Liu, Changyu Chen, Wenjun Li, et al.*2025 · 266 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-understanding-r1-zero-like-training/)
10. **[Search-o1: Agentic Search-Enhanced Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/li-2025-search-o1-agentic-search-enhanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.*2025 · 205 citations*
11. [**LIMO: Less is More for Reasoning arXiv:2502.03387**Yixin Ye, Zhen Huang, Yang Xiao, et al.*2025 · 204 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-limo-less-more-reasoning/)
12. [**Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paper**Yang Yue, Zhiqi Chen, Rui Lu, et al.*2025 · 196 citations*](https://md.research.elamur.ai/free/en/papers/yue-2025-reinforcement-learning-really-incentivize-reasoning/)
13. [**Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs arXiv:2412.21187**Xingyu Chen, Jiahao Xu, Tian Liang, et al.*2024 · 188 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-think-that-much-2-3/)
14. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 174 citations*
15. **[A-MEM: Agentic Memory for LLM Agents](https://md.research.elamur.ai/free/en/papers/xu-2025-mem-agentic-memory-llm-agents/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wujiang Xu, Zujie Liang, Kai Mei, et al.*2025 · 171 citations*
16. [**Group Sequence Policy Optimization arXiv:2507.18071**Chujie Zheng, Shixuan Liu, Mingze Li, et al.*2025 · 166 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2025-group-sequence-policy-optimization/)
17. **[Large Language Diffusion Models](https://md.research.elamur.ai/free/en/papers/nie-2025-large-language-diffusion-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shen Nie, Fengqi Zhu, Zebin You, et al.*2025 · 164 citations*
18. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 159 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
19. [**GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models arXiv:2508.06471**Aohan Zeng, Xin Lv, Qinkai Zheng, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-4-glm-4-5-agentic/)
20. [**Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models arXiv:2503.16419**Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.*2025 · 153 citations*](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)
21. [**SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild arXiv:2503.18892**Weihao Zeng, Yuzhen Huang, Qian Liu, et al.*2025 · 148 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2025-simplerl-zoo-investigating-taming-zero/)
22. [**Process Reinforcement through Implicit Rewards arXiv:2502.01456**Ganqu Cui, Lifan Yuan, Zefan Wang, et al.*2025 · 147 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-process-reinforcement-through-implicit-rewards/)
23. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs arXiv:2503.01743**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 145 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
24. **[Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-80-20-rule-high-entropy/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shenzhi Wang, Le Yu, Chang Gao, et al.*2025 · 142 citations*
25. [**R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning arXiv:2503.05592**Huatong Song, Jinhao Jiang, Yingqian Min, et al.*2025 · 137 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-r1-searcher-incentivizing-search/)
26. [**Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention arXiv:2502.11089**Jingyang Yuan, Huazuo Gao, Damai Dai, et al.*2025 · 135 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2025-native-sparse-attention-hardware/)
27. [**Token-Budget-Aware LLM Reasoning arXiv:2412.18547**Tingxu Han, Zhenting Wang, Chunrong Fang, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-token-budget-aware-llm-reasoning/)
28. [**OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework arXiv:2405.11143**Jian Hu, Xibin Wu, Wei Shen, et al.*2024 · 132 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-openrlhf-easy-use-scalable/)
29. **[Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model](https://md.research.elamur.ai/free/en/papers/hu-2025-open-reasoner-zero-open-source/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jingcheng Hu, Yinmin Zhang, Qi Han, et al.*2025 · 121 citations*
30. [**DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition arXiv:2504.21801**Z. Z. Ren, Zhihong Shao, Junxiao Song, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/ren-2025-deepseek-prover-v2-advancing-formal/)
31. [**L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning arXiv:2503.04697**Pranjal Aggarwal, Sean Welleck*2025 · 119 citations*](https://md.research.elamur.ai/free/en/papers/aggarwal-2025-l1-controlling-long-reasoning-model/)
32. [**DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence arXiv:2606.19348**DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.*2026 · 117 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-highly-efficient/)
33. [**Demystifying Long Chain-of-Thought Reasoning in LLMs arXiv:2502.03373**Edward Yeo, Yuxuan Tong, Morry Niu, et al.*2025 · 113 citations*](https://md.research.elamur.ai/free/en/papers/yeo-2025-demystifying-long-chain-thought-reasoning/)
34. [**OpenThoughts: Data Recipes for Reasoning Models arXiv:2506.04178**Etash Guha, Ryan Marten, Sedrick Keh, et al.*2025 · 113 citations*](https://md.research.elamur.ai/free/en/papers/guha-2025-openthoughts-data-recipes-reasoning-models/)
35. [**Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs arXiv:2503.01307**Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.*2025 · 110 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-cognitive-behaviors-that-enable-self/)
36. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 109 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
37. **[DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments](https://md.research.elamur.ai/free/en/papers/zheng-2025-deepresearcher-scaling-deep-research-reinforcement/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuxiang Zheng, Dayuan Fu, Xiangkun Hu, et al.*2025 · 108 citations*
38. **[TokenSkip: Controllable Chain-of-Thought Compression in LLMs](https://md.research.elamur.ai/free/en/papers/xia-2025-tokenskip-controllable-chain-thought-compression/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Heming Xia, Chak Tou Leong, Wenjie Wang, et al.*2025 · 105 citations*
39. [**Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning arXiv:2502.14768**Tian Xie, Zitian Gao, Qingnan Ren, et al.*2025 · 103 citations*](https://md.research.elamur.ai/free/en/papers/xie-2025-logic-rl-unleashing-llm/)
40. [**GLM-5: from Vibe Coding to Agentic Engineering arXiv:2602.15763**Aohan Zeng, Xin Lv, Zhenyu Hou, et al.*2026 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-5-glm-5-vibe-coding/)
41. **[OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models](https://md.research.elamur.ai/free/en/papers/huang-2025-opencoder-open-cookbook-top-tier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siming Huang, Tianhao Cheng, Jason Klein Liu, et al.*2025 · 81 citations*
42. [**GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning arXiv:2507.01006**GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-v-glm-4-5v-glm/)
43. [**LLMs Get Lost In Multi-Turn Conversation arXiv:2505.06120**Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, et al.*2025 · 77 citations*](https://md.research.elamur.ai/free/en/papers/laban-2025-llms-get-lost-multi-turn/)
44. [**Llama-Nemotron: Efficient Reasoning Models arXiv:2505.00949**Akhiad Bercovich, Itay Levy, Izik Golan, et al.*2025 · 75 citations*](https://md.research.elamur.ai/free/en/papers/bercovich-2025-llama-nemotron-efficient-reasoning-models/)
45. **[MoBA: Mixture of Block Attention for Long-Context LLMs](https://md.research.elamur.ai/free/en/papers/lu-2025-moba-mixture-block-attention/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Enzhe Lu, Zhejun Jiang, Jingyuan Liu, et al.*2025 · 75 citations*
46. **[MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation](https://md.research.elamur.ai/free/en/papers/xuan-2025-mmlu-prox-multilingual-benchmark-advanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Xuan, Rui Yang, Heli Qi, et al.*2025 · 74 citations*
47. [**Kimi-VL Technical Report arXiv:2504.07491**Kimi Team, Angang Du, Bohong Yin, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-vl-technical-report/)
48. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
49. **[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*
50. [**Inference-Time Scaling for Generalist Reward Modeling arXiv:2504.02495**Zijun Liu, Peiyi Wang, Runxin Xu, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-inference-time-scaling-generalist/)
51. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
52. [**ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning arXiv:2504.01296**Bairu Hou, Yang Zhang, Jiabao Ji, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/hou-2025-thinkprune-pruning-long-chain-thought/)
53. [**Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning arXiv:2504.13914**ByteDance Seed, Jiaze Chen, Tiantian Fan, et al.*2025 · 61 citations*](https://md.research.elamur.ai/free/en/papers/bytedance-seed-2025-seed1-5-thinking-advancing/)
54. [**MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention arXiv:2506.13585**MiniMax, Aili Chen, Aonian Li, et al.*2025 · 58 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-m1-scaling-test/)
55. [**Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling arXiv:2502.06703**Runze Liu, Junqi Gao, Jian Zhao, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-1b-llm-surpass-405b-llm/)
56. **[New Trends for Modern Machine Translation with Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-new-trends-modern-machine-translation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sinuo Liu, Chenyang Lyu, Minghao Wu, et al.*2026 · 16 citations*
57. [**When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning arXiv:2504.01005**Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/)
58. **[Can LLMs Evaluate What They Cannot Annotate? Revisiting LLM Reliability in Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/piot-2026-can-llms-evaluate-what-they/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Paloma Piot, David Otero, Patricia Martin-Rodilla, et al.*2026 · 5 citations*
59. **[ARB: A Comprehensive Arabic Multimodal Reasoning Benchmark](https://md.research.elamur.ai/free/en/papers/ghaboura-2026-arb-comprehensive-arabic-multimodal-reasoning/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sara Ghaboura, Shubham Patle, Ketan More, et al.*2026 · 3 citations*
60. **[Culture-Aware Machine Translation in Large Language Models: Benchmarking and Investigation](https://md.research.elamur.ai/free/en/papers/yuan-2026-culture-aware-machine-translation-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zekun Yuan, Yangfan Ye, Xiaocheng Feng, et al.*2026 · 2 citations*
61. [**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/)
62. **[The Riddle of Reflection: Evaluating Reasoning and Self-Awareness in Multilingual LLMs Using Indian Riddles](https://md.research.elamur.ai/free/en/papers/m-2026-riddle-reflection-evaluating-reasoning-self/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Abhinav P M, Ojasva Saxena, Oswald C, et al.*2026 · 2 citations*
63. **[UrBLiMP: A Benchmark for Evaluating the Linguistic Competence of Large Language Models in Urdu](https://md.research.elamur.ai/free/en/papers/adeeba-2026-urblimp-benchmark-evaluating-linguistic-competence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Farah Adeeba, Brian Dillon, Hassan Sajjad, et al.*2026 · 2 citations*
64. **[Can LLMs Translate Italy's Language Varieties?](https://md.research.elamur.ai/free/en/papers/signoroni-2026-can-llms-translate-italy-s/) [Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT)](https://md.research.elamur.ai/free/en/venues/loresmt/)**Edoardo Signoroni, Pavel Rychlý*2026 · 1 citation*
65. **[Conversational Assistants to Support Patients with Heart Failure: Comparing a Neurosymbolic Architecture with GPT](https://md.research.elamur.ai/free/en/papers/tayal-2026-conversational-assistants-support-patients-heart/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Anuja Tayal, Devika Salunke, Barbara Di Eugenio, et al.*2026 · 1 citation*
66. **[Datasets for Verb Alternations across Languages: BLM Templates and Data Augmentation Strategies](https://md.research.elamur.ai/free/en/papers/samo-2026-datasets-verb-alternations-across-languages/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Giuseppe Samo, Paola Merlo*2026 · 1 citation*
67. **[GIL-Zaragoza at SemEval 2026 Task 11: Comparing Classification, Autoformalization, and Ontologies for Formal Reasoning Capabilities](https://md.research.elamur.ai/free/en/papers/ponce-2026-gil-zaragoza-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Francisco Lopez-Ponce, Lucia Pitarch, Iván Saavedra Martínez, et al.*2026 · 1 citation*
68. **[Is This Idea Novel? An Automated Benchmark for Judgment of Research Ideas](https://md.research.elamur.ai/free/en/papers/schopf-2026-is-this-idea-novel-automated/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tim Schopf, Michael Färber*2026 · 1 citation*
69. **[Reformulate and Create, Don't Translate: Creating Natural Prompts for Underserved Languages](https://md.research.elamur.ai/free/en/papers/simonsen-2026-reformulate-create-don-t-translate/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Annika Simonsen, Mathias Stenlund, Lars Bungum, et al.*2026 · 1 citation*
70. **[Symbolic Grounding Reveals Representational Bottlenecks in Abstract Visual Reasoning](https://md.research.elamur.ai/free/en/papers/vaishnav-2026-symbolic-grounding-reveals-representational-bottlenecks/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Mohit Vaishnav, Tanel Tammet*2026 · 1 citation*
71. **[Synthetic Function Demonstrations Improve Generation in Low-Resource Programming Languages](https://md.research.elamur.ai/free/en/papers/mckenna-2026-synthetic-function-demonstrations-improve-generation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Nick McKenna, Xinnuo Xu, Jack Williams, et al.*2026 · 1 citation*
72. **[Babies Learn to Look Ahead: Multi-Token Prediction in Small LMs](https://md.research.elamur.ai/free/en/papers/aynetdinov-2025-babies-learn-look-ahead-multi/) [BabyLM Workshop](https://md.research.elamur.ai/free/en/venues/babylm/)**Ansar Aynetdinov, Alan Akbik*2025 · 1 citation*
73. [**HAMSA: Hijacking Aligned Compact Models via Stealthy Automation arXiv:2508.16484**Alexey Krylov, Iskander Vagizov, Dmitrii Korzh, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/krylov-2025-hamsa-hijacking-aligned-compact-models/)
74. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/)
75. **[AmDi - Ambiguous Words Diachronic Dataset](https://md.research.elamur.ai/free/en/papers/thielen-2026-amdi-ambiguous-words-diachronic-dataset/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Felix Thielen, Kai Kugler*2026*
76. [**AraDynFact: Dynamic Evaluation of Factual Knowledge in Arabic arXiv:2609.35461**Ignacio Iacobacci, Faroq Altam, Zhaozhi Qian, et al.*2026*](https://md.research.elamur.ai/free/en/papers/iacobacci-2026-aradynfact-dynamic-evaluation-factual-knowledge/)
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78. **[DeepICD-R1: Medical Reasoning through Hierarchical Rewards and Unsupervised Distillation](https://md.research.elamur.ai/free/en/papers/rohr-2026-deepicd-r1-medical-reasoning-through/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tom Röhr, Thomas Maximilian Josef Steffek, Roman Teucher, et al.*2026*
79. **[Do Multimodal LLMs Understand Order? Measuring the Fragility of Multimodal Reasoning under Input Order Perturbations](https://md.research.elamur.ai/free/en/papers/wei-2026-do-multimodal-llms-understand-order/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sheng-Lun Wei, Yu-Ling Liao, Hen-Hsen Huang, et al.*2026*
80. **[E-CONAN (Entailment, CONtradition And Neutral) Benchmarks: Arabic Textual Entailment and Natural Inference Datasets](https://md.research.elamur.ai/free/en/papers/jallad-2026-e-conan-entailment-contradition-neutral-benchmarks/) [IEEE Access](https://md.research.elamur.ai/free/en/venues/ieee-access/)**Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi*2026*
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82. [**Harm or Humor: A Multimodal, Multilingual Benchmark for Overt and Covert Harmful Humor arXiv:2603.17759**Ahmed Sharshar, Hosam Elgendy, Saad El Dine Ahmed, et al.*2026*](https://md.research.elamur.ai/free/en/papers/sharshar-2026-harm-humor-multimodal-multilingual-benchmark/)
83. **[Hindsight Quality Prediction Experiments in Multi-Candidate Human-Post-Edited Machine Translation](https://md.research.elamur.ai/free/en/papers/marmonier-2026-hindsight-quality-prediction-experiments-multi/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Malik Marmonier, Benoît Sagot, Rachel Bawden*2026*
84. **[ID10M-JAM: Stress-Testing Idiom Identification Under Challenging Context](https://md.research.elamur.ai/free/en/papers/hashiloni-2026-id10m-jam-stress-testing-idiom/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Golan Hashiloni, Lior Livyatan, Ofri Hefetz, et al.*2026*
85. [**Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages**Noam Dahan, Omer Kidron, Gabriel Stanovsky*2026*](https://md.research.elamur.ai/free/en/papers/dahan-2026-leveraging-digitized-newspapers-collect-summarization/)
86. [**Meaning Over Morphology: A Multi-Metric Benchmark of LLMs for Bangla Dialect Translation Proceedings of the First Workshop on Dialects in NLP –- A Resource Perspective**Soumik Deb Niloy, Subhey Sadi Rahman, Mahbub E Sobhani, et al.*2026*](https://md.research.elamur.ai/free/en/papers/niloy-2026-meaning-over-morphology-multi-metric/)
87. **[mSCoRe: A Multilingual and Scalable Benchmark for Skill-based Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/ngo-2026-mscore-multilingual-scalable-benchmark-skill/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Nghia Trung Ngo, Franck Dernoncourt, Thien Huu Nguyen*2026*
88. **[Multi-Agent Debate for Machine Translation: A Case Study on English-Japanese Translation](https://md.research.elamur.ai/free/en/papers/shen-2026-multi-agent-debate-machine-translation/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Zhan Shen, Jason Naradowsky, Xiaotian Wang, et al.*2026*
89. **[Multimodal LLMs Do Not Compose Skills Optimally across Modalities](https://md.research.elamur.ai/free/en/papers/ontalvilla-2026-multimodal-llms-do-not-compose/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune*2026*
90. **[Quantifying Metric and Model Agreement in Bias Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/asgari-2026-quantifying-metric-model-agreement-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arash Asgari, Huan Wu, Amirreza Naziri, et al.*2026*
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92. **[SPARTA: Evaluating Reasoning Segmentation Robustness through Black-Box Adversarial Paraphrasing in Text Autoencoder Latent Space](https://md.research.elamur.ai/free/en/papers/zinkovich-2026-sparta-evaluating-reasoning-segmentation-robustness/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Viktoriia Zinkovich, Anton Antonov, Andrei Spiridonov, et al.*2026*
93. **[Stands to Reason: Investigating the Effect of Reasoning on Idiomaticity Detection](https://md.research.elamur.ai/free/en/papers/phelps-2026-stands-reason-investigating-effect-reasoning/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Dylan Phelps, Rodrigo Wilkens, Edward Gow-Smith, et al.*2026*
94. **[STRUDEL: Unrolling a Benchmark for Evaluating Vision-Language Models on Structured Diagram Understanding across Domains](https://md.research.elamur.ai/free/en/papers/steinigen-2026-strudel-unrolling-benchmark-evaluating-vision/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Daniel Steinigen, Lucie Flek, Sebastian Houben*2026*
95. [**The Surge of Anti-Semitism in German Social Media following the October 7 Attacks arXiv:2609.36290**Gregor Wiedemann, Daniel Wehrend*2026*](https://md.research.elamur.ai/free/en/papers/wiedemann-2026-surge-anti-semitism-german-social/)
96. **[Uncovering Hidden Violent Tendencies in LLMs: A Demographic Analysis via Behavioral Vignettes](https://md.research.elamur.ai/free/en/papers/myers-2026-uncovering-hidden-violent-tendencies-llms/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Quintin Myers, Yanjun Gao*2026*
97. **[When the Database Fails: Prompting LLM Dialogue Agents for Safe Recovery in Task-Oriented Dialogue](https://md.research.elamur.ai/free/en/papers/shalmani-2026-when-database-fails-prompting-llm/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Mohammad Alijanpour Shalmani, Alale Rezvani Boroujeni, Jiann S. Yuan*2026*
98. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述) Acta Automatica Sinica (自动化学报)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)

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