---
title: "Who cites Swarat Chaudhuri — 401 papers of our library"
description: "401 papers of the Elamur Research library cite the works of Swarat Chaudhuri, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/swarat-chaudhuri/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/swarat-chaudhuri/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Swarat Chaudhuri](https://md.research.elamur.ai/free/en/authors/swarat-chaudhuri/) / cited by

# Who cites Swarat Chaudhuri

449 citations of their works from 401 papers of our library (of the 149,439 whose bibliographies we read) · 69 with a page here, the most cited first · [← Swarat Chaudhuri](https://md.research.elamur.ai/free/en/authors/swarat-chaudhuri/)

1. **[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*
2. **[Humanity's Last Exam](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 256 citations*
3. [**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 · 216 citations*](https://md.research.elamur.ai/free/en/papers/yue-2025-reinforcement-learning-really-incentivize-reasoning/)
4. [**AlphaEvolve: A coding agent for scientific and algorithmic discovery arXiv:2506.13131**Alexander Novikov, Ngân Vũ, Marvin Eisenberger, et al.*2025 · 202 citations*](https://md.research.elamur.ai/free/en/papers/novikov-2025-alphaevolve-coding-agent-scientific-algorithmic/)
5. **[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*
6. **[A Survey of Machine Learning for Big Code and Naturalness](https://md.research.elamur.ai/free/en/papers/allamanis-2017-survey-machine-learning-big-code/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, et al.*2017 · 167 citations*
7. [**Unsupervised Translation of Programming Languages arXiv:2006.03511**Marie-Anne Lachaux, Baptiste Roziere, Lowik Chanussot, et al.*2020 · 160 citations*](https://md.research.elamur.ai/free/en/papers/lachaux-2020-unsupervised-translation-programming-languages/)
8. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
9. [**DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence arXiv:2606.19348**DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.*2026 · 122 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-highly-efficient/)
10. [**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 · 122 citations*](https://md.research.elamur.ai/free/en/papers/ren-2025-deepseek-prover-v2-advancing-formal/)
11. [**DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data arXiv:2405.14333**Huajian Xin, Daya Guo, Zhihong Shao, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-advancing-theorem-proving/)
12. **[MathArena: Evaluating LLMs on Uncontaminated Math Competitions](https://md.research.elamur.ai/free/en/papers/balunovic-2025-matharena-evaluating-llms-uncontaminated-math/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Mislav Balunović, Jasper Dekoninck, Ivo Petrov, et al.*2025 · 99 citations*
13. [**FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI arXiv:2411.04872**Elliot Glazer, Ege Erdil, Tamay Besiroglu, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/glazer-2024-frontiermath-benchmark-evaluating-advanced-mathematical/)
14. **[PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition](https://md.research.elamur.ai/free/en/papers/tsoukalas-2024-putnambench-evaluating-neural-theorem-provers/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**George Tsoukalas, Jasper Lee, John Jennings, et al.*2024 · 93 citations*
15. [**Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning arXiv:2504.11354**Haiming Wang, Mert Unsal, Xiaohan Lin, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-kimina-prover-preview-large-formal/)
16. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
17. [**Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving arXiv:2502.07640**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 84 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-frontier-model-open/)
18. [**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/)
19. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/)
20. [**Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction arXiv:2508.03613**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-v2-scaling-formal/)
21. [**EuroLLM-9B: Technical Report arXiv:2506.04079**Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.*2025 · 45 citations*](https://md.research.elamur.ai/free/en/papers/martins-2025-eurollm-9b-technical-report/)
22. **[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*
23. **[An AI system to help scientists write expert-level empirical software](https://md.research.elamur.ai/free/en/papers/aygun-2025-ai-system-help-scientists/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**Eser Aygün, Anastasiya Belyaeva, Gheorghe Comanici, et al.*2025 · 27 citations*
24. **[Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-challenging-boundaries-reasoning-olympiad-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoxiang Sun, Yingqian Min, Zhipeng Chen, et al.*2026 · 25 citations*
25. **[ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection](https://md.research.elamur.ai/free/en/papers/yan-2026-errorradar-benchmarking-complex-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Shen Wang, Jiahao Huo, et al.*2026 · 23 citations*
26. **[How Likely Do LLMs with CoT Mimic Human Reasoning?](https://md.research.elamur.ai/free/en/papers/bao-2025-how-likely-do-llms-cot/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Guangsheng Bao, Hongbo Zhang, Cunxiang Wang, et al.*2025 · 22 citations*
27. **[A Survey on Evaluation of LLM-based Agents](https://md.research.elamur.ai/free/en/papers/yehudai-2026-survey-evaluation-llm-based-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaf Yehudai, Lilach Eden, Alan Li, et al.*2026 · 21 citations*
28. **[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*
29. **[“Give Me BF16 or Give Me Death”? Accuracy-Performance Trade-Offs in LLM Quantization](https://md.research.elamur.ai/free/en/papers/kurtic-2025-give-me-bf16-or-give/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eldar Kurtic, Alexandre Noll Marques, Shubhra Pandit, et al.*2025 · 21 citations*
30. [**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/)
31. **[Command R7B Arabic: a small, enterprise-focused, multilingual, and culturally aware Arabic LLM](https://md.research.elamur.ai/free/en/papers/alnumay-2025-command-r7b-arabic-small-enterprise/) [Workshop on African Natural Language Processing](https://md.research.elamur.ai/free/en/venues/africanlp/)**Yazeed Alnumay, Alexandre Barbet, Anna Bialas, et al.*2025 · 18 citations*
32. [**MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving arXiv:2503.03205**Ruida Wang, Rui Pan, Yuxin Li, et al.*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-ma-lot-model-collaboration-lean/)
33. **[ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of Data](https://md.research.elamur.ai/free/en/papers/liu-2025-atlas-autoformalizing-theorems-through-lifting/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang, et al.*2025 · 16 citations*
34. **[Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening](https://md.research.elamur.ai/free/en/papers/he-2025-rewarding-unlikely-lifting-grpo-beyond/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Andre Wang He, Daniel Fried, Sean Welleck*2025 · 15 citations*
35. **[CoMAT: Chain of Mathematically Annotated Thought Improves Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/leang-2025-comat-chain-mathematically-annotated-thought/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Ong Jun Leang, Aryo Pradipta Gema, Shay B. Cohen*2025 · 14 citations*
36. **[CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization](https://md.research.elamur.ai/free/en/papers/peng-2026-criticlean-critic-guided-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyuan Peng, Yifan Yao, Kaijing Ma, et al.*2026 · 12 citations*
37. [**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/)
38. [**JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models arXiv:2501.14851**Michael K. Chen, Xikun Zhang, Dacheng Tao*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-justlogic-comprehensive-benchmark-evaluating-deductive/)
39. **[Theorem Prover as a Judge for Synthetic Data Generation](https://md.research.elamur.ai/free/en/papers/leang-2025-theorem-prover-as-judge-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joshua Ong Jun Leang, Giwon Hong, Wenda Li, et al.*2025 · 9 citations*
40. **[Reinforcement Learning for Self-Improving Agent with Skill Library](https://md.research.elamur.ai/free/en/papers/wang-2026-reinforcement-learning-self-improving-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiongxiao Wang, Qiaojing Yan, Yawei Wang, et al.*2026 · 8 citations*
41. [**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/)
42. [**StepFun-Formalizer: Unlocking the Autoformalization Potential of LLMs through Knowledge-Reasoning Fusion arXiv:2508.04440**Yutong Wu, Di Huang, Ruosi Wan, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-stepfun-formalizer-unlocking-autoformalization/)
43. **[CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges](https://md.research.elamur.ai/free/en/papers/wang-2026-creativebench-benchmarking-enhancing-machine-creativity/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Wang, Lam Nguyen, Zhengyang Zhao, et al.*2026 · 6 citations*
44. [**Explain in Your Own Words: Improving Reasoning via Token-Selective Dual Knowledge Distillation arXiv:2603.13260**Minsang Kim, Seung Jun Baek*2026 · 6 citations*](https://md.research.elamur.ai/free/en/papers/kim-2026-explain-own-words-improving-reasoning/)
45. [**AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model Discovery arXiv:2604.05550**Yu Li, Chenyang Shao, Xinyang Liu, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/li-2026-autosota-end-end-automated-research/)
46. **[Analysing Chain of Thought Dynamics: Active Guidance or Unfaithful Post-hoc Rationalisation?](https://md.research.elamur.ai/free/en/papers/lim-2025-analysing-chain-thought-dynamics-active/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Samuel Lewis-Lim, Xingwei Tan, Zhixue Zhao, et al.*2025 · 5 citations*
47. **[The DISRPT 2025 Shared Task on Elementary Discourse Unit Segmentation, Connective Detection, and Relation Classification](https://md.research.elamur.ai/free/en/papers/braud-2025-disrpt-2025-shared-task-elementary/) [Shared Task on Discourse Relation Parsing and Treebanking](https://md.research.elamur.ai/free/en/venues/disrpt/)**Chloé Braud, Amir Zeldes, Chuyuan Li, et al.*2025 · 5 citations*
48. **[Do Not Step Into the Same River Twice: Learning to Reason from Trial and Error](https://md.research.elamur.ai/free/en/papers/tang-2026-do-not-step-into-same/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenming Tang, Hsiu-Yuan Huang, Weijie Liu, et al.*2026 · 3 citations*
49. **[Can We Predict Before Executing Machine Learning Agents?](https://md.research.elamur.ai/free/en/papers/zheng-2026-can-we-predict-before-executing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingsheng Zheng, Jintian Zhang, Yujie Luo, et al.*2026 · 2 citations*
50. **[A Survey of Deep Learning for Geometry Problem Solving](https://md.research.elamur.ai/free/en/papers/ma-2026-survey-deep-learning-geometry-problem/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianzhe Ma, Wenxuan Wang, Qin Jin*2026 · 1 citation*
51. **[Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future](https://md.research.elamur.ai/free/en/papers/wu-2026-can-ai-be-good-peer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sihong Wu, Owen Jiang, Yilun Zhao, et al.*2026 · 1 citation*
52. **[LitVISTA: A Benchmark for Narrative Orchestration in Literary Text](https://md.research.elamur.ai/free/en/papers/lu-2026-litvista-benchmark-narrative-orchestration-literary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingzhe Lu, Yiwen Wang, Yanbing Liu, et al.*2026 · 1 citation*
53. **[Logic Haystacks: Probing LLMs' Long-Context Logical Reasoning (Without Easily Identifiable Unrelated Padding)](https://md.research.elamur.ai/free/en/papers/sileo-2026-logic-haystacks-probing-llms-long/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Damien Sileo*2026 · 1 citation*
54. **[What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary Search](https://md.research.elamur.ai/free/en/papers/zhang-2026-what-makes-llm-good-optimizer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinhao Zhang, Xi Chen, François Portet, et al.*2026 · 1 citation*
55. **[A Survey of Multimodal Mathematical Reasoning: From Perception, Alignment to Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2026-survey-multimodal-mathematical-reasoning-perception/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Yang, Sihong Wu, Yilun Zhao, et al.*2026*
56. **[AdaptEvolve: Improving Efficiency of Evolutionary AI Agents through Adaptive Model Selection](https://md.research.elamur.ai/free/en/papers/ray-2026-adaptevolve-improving-efficiency-evolutionary-ai/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pretam Ray, Pratik Prabhanjan Brahma, Zicheng Liu, et al.*2026*
57. **[AgentFactory: A Self-Evolving Framework Through Executable Subagent Accumulation and Reuse](https://md.research.elamur.ai/free/en/papers/zhang-2026-agentfactory-self-evolving-framework-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhang Zhang, Shuqi Lu, Hongjin Qian, et al.*2026*
58. **[AlphaContext: An Evolutionary Tree-based Psychometric Context Generator for Creativity Assessment](https://md.research.elamur.ai/free/en/papers/wang-2026-alphacontext-evolutionary-tree-based-psychometric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixuan Wang, Yue Huang, Hong Qian, et al.*2026*
59. **[Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers](https://md.research.elamur.ai/free/en/papers/zhao-2026-are-my-optimized-prompts-compromised/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Andrew Zhao, Reshmi Ghosh, Vitor R. Carvalho, et al.*2026*
60. [**Auditing Discovery Claims: A Two-Sided Criterion for Agentic Science, with the Negative Side Decidable arXiv:2608.00981**Wenhui Chen, Jianlin Chen, Ziyao Lin, et al.*2026*](https://md.research.elamur.ai/free/en/papers/chen-2026-auditing-discovery-claims-two/)
61. **[Beyond the Singular: Revealing the Value of Multiple Generations in Benchmark Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-singular-revealing-value-multiple/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenbo Zhang, Hengrui Cai, Wenyu Chen*2026*
62. **[Demystify the Role of Memory in Machine Learning Engineering Agents](https://md.research.elamur.ai/free/en/papers/zhao-2026-demystify-role-memory-machine-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyu Zhao, Junpeng Wang, Yuzhong Chen, et al.*2026*
63. **[Evolutionary Search for Automated Design of Uncertainty Quantification Methods](https://md.research.elamur.ai/free/en/papers/seleznyov-2026-evolutionary-search-automated-design-uncertainty/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mikhail Seleznyov, Daniil Korbut, Viktor Moskvoretskii, et al.*2026*
64. **[FormalScience: Scalable Human-in-the-Loop Autoformalisation of Science with Agentic Code Generation in Lean](https://md.research.elamur.ai/free/en/papers/meadows-2026-formalscience-scalable-human-loop-autoformalisation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jordan Meadows, Lan Zhang, Andre Freitas*2026*
65. **[Open Problems Solved by LLMs? A Survey of Verifiable Mathematical Discovery](https://md.research.elamur.ai/free/en/papers/tzachristas-2026-open-problems-solved-llms-survey/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Ioannis Tzachristas, Georgios Tzachristas, Aifen Sui*2026*
66. **[Output-Space Search: Targeting LLM Generations in a Frozen Encoder-Defined Output Space](https://md.research.elamur.ai/free/en/papers/materzok-2026-output-space-search-targeting-llm/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Tobias Materzok*2026*
67. **[Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow](https://md.research.elamur.ai/free/en/papers/zhong-2026-parallelism-generation-order-masked-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangyang Zhong, Yanmei Gu, Zhengqing Zang, et al.*2026*
68. **[Preference Optimization for Review Question Generation Improves Writing Quality](https://md.research.elamur.ai/free/en/papers/sharma-2026-preference-optimization-review-question-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Karun Sharma, Vidushee Vats, Shengzhi LI, et al.*2026*
69. **[PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language Models](https://md.research.elamur.ai/free/en/papers/ouyang-2026-pyramathbench-evaluating-improving-mathematical-capability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zetian Ouyang, Linlin Wang, Gerard de Melo, et al.*2026*

332 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/swarat-chaudhuri/) — Swarat Chaudhuri