---
title: "Who cites Nick Haber — 194 papers of our library"
description: "194 papers of the Elamur Research library cite the works of Nick Haber, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/nick-haber/cited-by/"
---
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# Who cites Nick Haber

198 citations of their works from 194 papers of our library (of the 149,439 whose bibliographies we read) · 80 with a page here, the most cited first · [← Nick Haber](https://md.research.elamur.ai/free/en/authors/nick-haber/)

1. **[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 · 608 citations*
2. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
3. **[SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering](https://md.research.elamur.ai/free/en/papers/yang-2024-swe-agent-agent-computer-interfaces/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Carlos E. Jimenez, Alexander Wettig, et al.*2024 · 552 citations*
4. **[Self-collaboration Code Generation via ChatGPT](https://md.research.elamur.ai/free/en/papers/dong-2023-self-collaboration-code-generation/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Yihong Dong; Xue Jiang; Zhi Jin;, Ge Li*2023 · 319 citations*
5. [**LIMO: Less is More for Reasoning arXiv:2502.03387**Yixin Ye, Zhen Huang, Yang Xiao, et al.*2025 · 209 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-limo-less-more-reasoning/)
6. **[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 · 176 citations*
7. **[Can Language Models Solve Graph Problems in Natural Language?](https://md.research.elamur.ai/free/en/papers/wang-2023-language-models-solve-graph-problems/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Heng Wang, Shangbin Feng, Tianxing He, et al.*2023 · 124 citations*
8. [**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 · 123 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-cognitive-behaviors-that-enable-self/)
9. [**Quiet-STaR: Language models can teach themselves to think before speaking***2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/al-2024-quiet-star-language-models-teach/)
10. [**Large Language Models as General Pattern Machines arXiv:2307.04721**Suvir Mirchandani, Fei Xia, Pete Florence, et al.*2023 · 88 citations*](https://md.research.elamur.ai/free/en/papers/mirchandani-2023-large-language-models-general-pattern/)
11. **[Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond](https://md.research.elamur.ai/free/en/papers/wen-2025-light-r1-curriculum-sft-dpo/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liang Wen, Yunke Cai, Fenrui Xiao, et al.*2025 · 84 citations*
12. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/)
13. [**DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning arXiv:2504.11456**Zhiwei He, Tian Liang, Jiahao Xu, et al.*2025 · 78 citations*](https://md.research.elamur.ai/free/en/papers/he-2025-deepmath-103k-large-scale-challenging/)
14. [**Large Language Models as Analogical Reasoners arXiv:2310.01714**Michihiro Yasunaga, Xinyun Chen, Yujia Li, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/yasunaga-2023-large-language-models-analogical-reasoners/)
15. [**Kevin: Multi-Turn RL for Generating CUDA Kernels arXiv 2025**Carlo Baronio, Pietro Marsella, Ben Pan, et al.*2025 · 69 citations*](https://md.research.elamur.ai/free/en/papers/baronio-2025-kevin-multi-turn-rl-generating/)
16. [**Evaluation of OpenAI o1: Opportunities and Challenges of AGI arXiv:2409.18486**Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.*2024 · 64 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-evaluation-openai-o1-opportunities-challenges/)
17. **[Absolute Zero: Reinforced Self-play Reasoning with Zero Data](https://md.research.elamur.ai/free/en/papers/zhao-2025-absolute-zero-reinforced-self-play/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Andrew Zhao, Yiran Wu, Yang Yue, et al.*2025 · 57 citations*
18. **[Clover: Closed-Loop Verifiable Code Generation](https://md.research.elamur.ai/free/en/papers/sun-2024-clover-closed-loop-verifiable-code/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Chuyue Sun, Ying Sheng, Oded Padon, et al.*2024 · 56 citations*
19. **[DeepReview: Improving LLM-based Paper Review with Human-like Deep Thinking Process](https://md.research.elamur.ai/free/en/papers/zhu-2025-deepreview-improving-llm-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minjun Zhu, Yixuan Weng, Linyi Yang, et al.*2025 · 52 citations*
20. [**Formal Mathematical Reasoning: A New Frontier in AI arXiv:2412.16075**Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.*2024 · 49 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-formal-mathematical-reasoning-new-frontier/)
21. [**DeepSeek-R1 Thoughtology: Let's think about LLM Reasoning arXiv:2504.07128**Sara Vera Marjanovic, Arkil Patel, Vaibhav Adlakha, et al.*2025 · 47 citations*](https://md.research.elamur.ai/free/en/papers/marjanovic-2025-deepseek-r1-thoughtology-let-s/)
22. [**Seed-Prover: Deep and Broad Reasoning for Automated Theorem Proving arXiv:2507.23726**Luoxin Chen, Jinming Gu, Liankai Huang, et al.*2025 · 46 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-seed-prover-deep-broad-reasoning/)
23. [**A Survey on Deep Learning for Theorem Proving arXiv:2404.09939**Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-survey-deep-learning-theorem-proving/)
24. [**Learning to Reason without External Rewards arXiv:2505.19590**Xuandong Zhao, Zhewei Kang, Aosong Feng, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-learning-reason-external-rewards/)
25. [**Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models arXiv:2502.17387**Alon Albalak, Duy Phung, Nathan Lile, et al.*2025 · 43 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2025-big-math-large-scale-high/)
26. [**STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving arXiv:2502.00212**Kefan Dong, Tengyu Ma*2025 · 43 citations*](https://md.research.elamur.ai/free/en/papers/dong-2025-stp-self-play-llm-theorem/)
27. **[Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2025-towards-thinking-optimal-scaling-test/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wenkai Yang, Shuming Ma, Yankai Lin, et al.*2025 · 43 citations*
28. [**Evaluating Language Models for Mathematics through Interactions arXiv:2306.01694**Katherine M. Collins, Albert Q. Jiang, Simon Frieder, et al.*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/collins-2023-evaluating-language-models-mathematics-through/)
29. [**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/)
30. [**A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence arXiv:2507.21046**Huan-ang Gao, Jiayi Geng, Wenyue Hua, et al.*2025 · 36 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-survey-self-evolving-agents-where/)
31. [**OpenCodeReasoning: Advancing Data Distillation for Competitive Coding arXiv:2504.01943**Wasi Uddin Ahmad, Sean Narenthiran, Somshubra Majumdar, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/ahmad-2025-opencodereasoning-advancing-data-distillation-competitive/)
32. [**Can Language Models Solve Olympiad Programming? arXiv:2404.10952**Quan Shi, Michael Tang, Karthik Narasimhan, et al.*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/shi-2024-language-models-solve-olympiad-programming/)
33. [**Scaling Test-Time Compute Without Verification or RL is Suboptimal arXiv:2502.12118**Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/setlur-2025-scaling-test-time-compute-verification/)
34. **[Linguistic Generalizability of Test-Time Scaling in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/son-2025-linguistic-generalizability-test-time-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guijin Son, Jiwoo Hong, Hyunwoo Ko, et al.*2025 · 24 citations*
35. **[Symbolic Regression with a Learned Concept Library](https://md.research.elamur.ai/free/en/papers/grayeli-2024-symbolic-regression-learned-concept-library/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Arya Grayeli, Atharva Sehgal, Omar Costilla-Reyes, et al.*2024 · 23 citations*
36. **[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*
37. [**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/)
38. **[From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/jianu-2025-problem-solving-teaching-problem-solving/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**David Dinucu-Jianu, Jakub Macina, Nico Daheim, et al.*2025 · 19 citations*
39. [**Seed-Prover 1.5: Mastering Undergraduate-Level Theorem Proving via Learning from Experience arXiv:2512.17260**Jiangjie Chen, Wenxiang Chen, Jiacheng Du, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-seed-prover-1-5/)
40. [**The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas arXiv:2506.20803**Chenglei Si, Tatsunori Hashimoto, Diyi Yang*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/si-2025-ideation-execution-gap-execution/)
41. **[Think Silently, Think Fast: Dynamic Latent Compression of LLM Reasoning Chains](https://md.research.elamur.ai/free/en/papers/tan-2025-think-silently-think-fast-dynamic/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wenhui Tan, Jiaze Li, Jianzhong Ju, et al.*2025 · 19 citations*
42. [**Evaluating statistical language models as pragmatic reasoners arXiv:2305.01020**Benjamin Lipkin, Lionel Wong, Gabriel Grand, et al.*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/lipkin-2023-evaluating-statistical-language-models-pragmatic/)
43. [**LLM-Assisted Code Cleaning For Training Accurate Code Generators arXiv:2311.14904**Naman Jain, Tianjun Zhang, Wei-Lin Chiang, et al.*2023 · 17 citations*](https://md.research.elamur.ai/free/en/papers/jain-2023-llm-assisted-code-cleaning-training/)
44. [**Can Large Reasoning Models Self-Train? arXiv:2505.21444**Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/shafayat-2025-large-reasoning-models-self-train/)
45. **[From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging](https://md.research.elamur.ai/free/en/papers/shi-2024-code-correctness-closing-last-mile/) [IEEE/ACM International Conference on Software Engineering (ICSE)](https://md.research.elamur.ai/free/en/venues/ieee-acm-international-conference-on-software-engineering-icse/)**Yuling Shi, Songsong Wang, Chengcheng Wan, et al.*2024 · 15 citations*
46. [**Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search arXiv:2405.15383**Nicola Dainese, Matteo Merler, Minttu Alakuijala, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/dainese-2024-generating-code-world-models/)
47. [**CodeR: Issue Resolving with Multi-Agent and Task Graphs arXiv:2406.01304**Dong Chen, Shaoxin Lin, Muhan Zeng, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-coder-issue-resolving-multi-agent/)
48. [**Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models arXiv:2407.15645**Joy He-Yueya, Wanjing Anya Ma, Kanishk Gandhi, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/he-yueya-2024-psychometric-alignment-capturing-human-knowledge/)
49. [**The Open Proof Corpus: A Large-Scale Study of LLM-Generated Mathematical Proofs arXiv:2506.21621**Jasper Dekoninck, Ivo Petrov, Kristian Minchev, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/dekoninck-2025-open-proof-corpus-large-scale/)
50. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
51. [**CodeS: Natural Language to Code Repository via Multi-Layer Sketch arXiv:2403.16443**Daoguang Zan, Ailun Yu, Wei Liu, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zan-2024-codes-natural-language-code-repository/)
52. [**Brains vs. Bytes: Evaluating LLM Proficiency in Olympiad Mathematics arXiv:2504.01995**Hamed Mahdavi, Alireza Hashemi, Majid Daliri, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/mahdavi-2025-brains-vs-bytes-evaluating-llm/)
53. [**ReForm: Reflective Autoformalization with Prospective Bounded Sequence Optimization arXiv:2510.24592**Guoxin Chen, Jing Wu, Xinjie Chen, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-reform-reflective-autoformalization-prospective-bounded/)
54. [**Evaluating and Optimizing Educational Content with Large Language Model Judgments arXiv:2403.02795**Joy He-Yueya, Noah D. Goodman, Emma Brunskill*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/he-yueya-2024-evaluating-optimizing-educational-content-large/)
55. **[Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models](https://md.research.elamur.ai/free/en/papers/chae-2024-language-models-as-compilers-simulating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hyungjoo Chae, Yeonghyeon Kim, Seungone Kim, et al.*2024 · 7 citations*
56. [**InnovatorBench: Evaluating Agents' Ability to Conduct Innovative LLM Research arXiv:2510.27598**Yunze Wu, Dayuan Fu, Weiye Si, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-innovatorbench-evaluating-agents-ability-conduct/)
57. [**Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation arXiv:2502.01694**Juno Kim, Denny Wu, Jason Lee, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/kim-2025-metastable-dynamics-chain-thought-reasoning/)
58. [**AI for Auto-Research: Roadmap & User Guide arXiv:2605.18661**Lingdong Kong, Xian Sun, Wei Chow, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/kong-2026-ai-auto-research-roadmap-user/)
59. **[PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated Reasoning](https://md.research.elamur.ai/free/en/papers/hu-2026-pacore-learning-scale-test-time/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingcheng Hu, Yinmin Zhang, Shijie Shang, et al.*2026 · 5 citations*
60. [**Ring-lite: Scalable Reasoning via C3PO-Stabilized Reinforcement Learning for LLMs arXiv:2506.14731**Ling Team, Bin Hu, Cai Chen, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/ling-team-2025-ring-lite-scalable-reasoning/)
61. **[EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving](https://md.research.elamur.ai/free/en/papers/zhou-2026-engibench-benchmark-evaluating-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiyuan Zhou, Xinlei Wang, Yirui He, et al.*2026 · 3 citations*
62. **[SHAPE: Unifying Safety, Helpfulness and Pedagogy for Educational LLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-shape-unifying-safety-helpfulness-pedagogy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sihang Zhao, Kangrui Yu, Youliang Yuan, et al.*2026 · 2 citations*
63. [**Training AI Scientists to Replicate Research arXiv:2608.13331**Damon Falck, Samer Sabri, Anja Surina, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/falck-2026-training-ai-scientists-replicate/)
64. **[Distillation Traps and Guards: A Calibration Knob for LLM Distillability](https://md.research.elamur.ai/free/en/papers/zhan-2026-distillation-traps-guards-calibration-knob/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weixiao Zhan, Yongcheng Jing, Leszek Rutkowski, et al.*2026 · 1 citation*
65. **[Evaluating Answer Leakage Robustness of LLM Tutors against Adversarial Student Attacks](https://md.research.elamur.ai/free/en/papers/zhao-2026-evaluating-answer-leakage-robustness-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jin Zhao, Marta Knežević, Tanja Käser*2026 · 1 citation*
66. **[Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-render-thought-rendering-textual-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifan Wang, Shiyu Li, Peiming Li, et al.*2026 · 1 citation*
67. **[Consistency of LLMs to Comparative Statements in Mathematical Reasoning Tasks](https://md.research.elamur.ai/free/en/papers/san-2026-consistency-llms-comparative-statements-mathematical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aidan W. San, Daniel Juyoung Son, Xiaodong Liu, et al.*2026*
68. **[Contract-Coding: Towards Repo-Level Generation via Structured Symbolic Paradigm](https://md.research.elamur.ai/free/en/papers/yilin-2026-contract-coding-repo-level-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yilin, Lujin Zhao, Yijie Shi*2026*
69. **[Entropy Scheduling in Reinforcement Learning for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-entropy-scheduling-reinforcement-learning-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingjin Wang, Howe Tissue, Lu Wang, et al.*2026*
70. **[GR1: Reinforcement-Enhanced LLM for Geoscience Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2026-gr1-reinforcement-enhanced-llm-geoscience/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yule Xie, Jiaxin Ding, Cheng Deng, et al.*2026*
71. **[MMSciCode: Real-world Evaluation of Multilingual Multi-Discipline Scientific Research Coding](https://md.research.elamur.ai/free/en/papers/xia-2026-mmscicode-real-world-evaluation-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xue Xia, Zheyuan Yang, Arman Cohan, et al.*2026*
72. **[Model-Based Imaginative Planning for Embodied Agents](https://md.research.elamur.ai/free/en/papers/song-2026-model-based-imaginative-planning-embodied/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junru Song, Hengzhe Jin, Yucong Huang, et al.*2026*
73. **[RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-routemoa-dynamic-routing-without-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jize Wang, Han Wu, Zhiyuan You, et al.*2026*
74. **[SD-E2: Semantic Exploration for Reasoning Under Token Budgets](https://md.research.elamur.ai/free/en/papers/mishra-2026-sd-e2-semantic-exploration-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kshitij Mishra, Nils Lukas, Salem Lahlou*2026*
75. **[Social Welfare Function Leaderboard: On the Emergence of LLM Agents as the Welfare Dictator](https://md.research.elamur.ai/free/en/papers/shi-2026-social-welfare-function-leaderboard-emergence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengliang Shi, Ruotian Ma, Jen-tse Huang, et al.*2026*
76. **[STCOR: A Trilevel Syllogism-Driven Reasoning Framework](https://md.research.elamur.ai/free/en/papers/yang-2026-stcor-trilevel-syllogism-driven-reasoning/) [Workshop on Argument Mining](https://md.research.elamur.ai/free/en/venues/argmining/)**Keying Yang, Hao Wang, Chengtao Jian, et al.*2026*
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