---
title: "Who cites Arnaud Doucet — 292 papers of our library"
description: "292 papers of the Elamur Research library cite the works of Arnaud Doucet, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/arnaud-doucet/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/arnaud-doucet/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Arnaud Doucet](https://md.research.elamur.ai/free/en/authors/arnaud-doucet/) / cited by

# Who cites Arnaud Doucet

293 citations of their works from 292 papers of our library (of the 149,439 whose bibliographies we read) · 69 with a page here, the most cited first · [← Arnaud Doucet](https://md.research.elamur.ai/free/en/authors/arnaud-doucet/)

1. [**Kimi k1.5: Scaling Reinforcement Learning with LLMs arXiv:2501.12599**Kimi Team, Angang Du, Bofei Gao, et al.*2025 · 431 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k1-5-scaling-reinforcement/)
2. **[xCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detection](https://md.research.elamur.ai/free/en/papers/guerreiro-2024-xcomet-transparent-machine-translation-evaluation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nuno M. Guerreiro, Ricardo Rei, Daan van Stigt, et al.*2024 · 333 citations*
3. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 262 citations*
4. [**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/)
5. [**Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2 arXiv:2311.10702**Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/ivison-2023-camels-changing-climate-enhancing-lm/)
6. **[ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search](https://md.research.elamur.ai/free/en/papers/zhang-2024-rest-mcts-llm-self-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.*2024 · 200 citations*
7. **[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 · 178 citations*
8. **[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*
9. **[When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 161 citations*
10. **[Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/wang-2024-interpretable-preferences-multi-objective-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoxiang Wang, Wei Xiong, Tengyang Xie, et al.*2024 · 153 citations*
11. **[Iterative Reasoning Preference Optimization](https://md.research.elamur.ai/free/en/papers/pang-2024-iterative-reasoning-preference-optimization/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.*2024 · 153 citations*
12. **[Simple and Effective Masked Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/sahoo-2024-simple-effective-masked-diffusion-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, et al.*2024 · 152 citations*
13. [**Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models arXiv:2312.06585**Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/singh-2023-human-data-scaling-self-training/)
14. **[Many-Shot In-Context Learning](https://md.research.elamur.ai/free/en/papers/agarwal-2024-many-shot-context-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.*2024 · 142 citations*
15. **[ReFT: Reasoning with Reinforced Fine-Tuning](https://md.research.elamur.ai/free/en/papers/trung-2024-reft-reasoning-reinforced-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luong Trung, Xinbo Zhang, Zhanming Jie, et al.*2024 · 134 citations*
16. [**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/)
17. [**Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models arXiv:2501.09686**Fengli Xu, Qianyue Hao, Zefang Zong, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-towards-large-reasoning-models-survey/)
18. [**Demystifying Long Chain-of-Thought Reasoning in LLMs arXiv:2502.03373**Edward Yeo, Yuxuan Tong, Morry Niu, et al.*2025 · 119 citations*](https://md.research.elamur.ai/free/en/papers/yeo-2025-demystifying-long-chain-thought-reasoning/)
19. [**V-STaR: Training Verifiers for Self-Taught Reasoners arXiv:2402.06457**Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2024-v-star-training-verifiers-self/)
20. [**RLHF Workflow: From Reward Modeling to Online RLHF arXiv:2405.07863**Hanze Dong, Wei Xiong, Bo Pang, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-rlhf-workflow-reward-modeling-online/)
21. [**Statistical Rejection Sampling Improves Preference Optimization arXiv:2309.06657**Tianqi Liu, Yao Zhao, Rishabh Joshi, et al.*2023 · 105 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-statistical-rejection-sampling-improves-preference/)
22. [**Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint arXiv:2312.11456**Wei Xiong, Hanze Dong, Chenlu Ye, et al.*2023 · 100 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-iterative-preference-learning-human-feedback/)
23. [**Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models arXiv:2601.18734**Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.*2026 · 97 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2026-self-distilled-reasoner-policy-self/)
24. **[A Survey of Reinforcement Learning from Human Feedback](https://md.research.elamur.ai/free/en/papers/kaufmann-2023-survey-reinforcement-learning-human-feedback/) [Transactions on Machine Learning Research](https://md.research.elamur.ai/free/en/venues/transactions-on-machine-learning-research/)**Timo Kaufmann, Paul Weng, Viktor Bengs, et al.*2023 · 92 citations*
25. [**Dream 7B: Diffusion Large Language Models arXiv:2508.15487**Jiacheng Ye; Zhihui Xie; Lin Zheng; Jiahui Gao; Zirui Wu; Xin Jiang; Zhenguo Li;, Lingpeng Kong*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-dream-7b-diffusion-large-language/)
26. **[Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement](https://md.research.elamur.ai/free/en/papers/xu-2024-pride-prejudice-llm-amplifies-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenda Xu, Guanglei Zhu, Xuandong Zhao, et al.*2024 · 88 citations*
27. **[Mitigating the Alignment Tax of RLHF](https://md.research.elamur.ai/free/en/papers/lin-2024-mitigating-alignment-tax-rlhf/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yong Lin, Hangyu Lin, Wei Xiong, et al.*2024 · 83 citations*
28. [**DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving arXiv:2407.13690**Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.*2024 · 81 citations*](https://md.research.elamur.ai/free/en/papers/tong-2024-dart-math-difficulty-aware-rejection/)
29. **[Aligner: Efficient Alignment by Learning to Correct](https://md.research.elamur.ai/free/en/papers/ji-2024-aligner-efficient-alignment-learning-correct/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaming Ji, Boyuan Chen, Hantao Lou, et al.*2024 · 69 citations*
30. [**Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents arXiv:2408.07199**Pranav Putta, Edmund Mills, Naman Garg, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/putta-2024-agent-q-advanced-reasoning-learning/)
31. **[Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards](https://md.research.elamur.ai/free/en/papers/wang-2024-arithmetic-control-llms-diverse-user/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoxiang Wang, Yong Lin, Wei Xiong, et al.*2024 · 68 citations*
32. **[Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration](https://md.research.elamur.ai/free/en/papers/feng-2024-modular-pluralism-pluralistic-alignment-multi/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shangbin Feng, Taylor Sorensen, Yuhan Liu, et al.*2024 · 68 citations*
33. **[Small Models Struggle to Learn from Strong Reasoners](https://md.research.elamur.ai/free/en/papers/li-2025-small-models-struggle-learn-strong/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuetai Li, Xiang Yue, Zhangchen Xu, et al.*2025 · 61 citations*
34. [**Teaching Large Language Models to Reason with Reinforcement Learning arXiv:2403.04642**Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-teaching-large-language-models-reason/)
35. **[Trial and Error: Exploration-Based Trajectory Optimization of LLM Agents](https://md.research.elamur.ai/free/en/papers/song-2024-trial-error-exploration-based-trajectory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifan Song, Da Yin, Xiang Yue, et al.*2024 · 53 citations*
36. **[LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models](https://md.research.elamur.ai/free/en/papers/zhu-2026-llada-1-5-variance-reduced/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fengqi Zhu, Rongzhen Wang, Shen Nie, et al.*2026 · 49 citations*
37. [**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/)
38. [**SALMON: Self-Alignment with Instructable Reward Models arXiv:2310.05910**Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.*2023 · 41 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-salmon-self-alignment-instructable-reward/)
39. **[Vision-Language Models Can Self-Improve Reasoning via Reflection](https://md.research.elamur.ai/free/en/papers/cheng-2025-vision-language-models-can-self/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kanzhi Cheng, Li YanTao, Fangzhi Xu, et al.*2025 · 35 citations*
40. [**MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods arXiv:2309.10966**Mara Finkelstein; Subhajit Naskar; Mehdi Mirzazadeh; Apurva Shah;, Markus Freitag*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/finkelstein-2023-mbr-qe-finetuning-training-time/)
41. [**Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference arXiv:2508.02193**Yuxuan Song, Zheng Zhang, Cheng Luo, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-seed-diffusion-large-scale/)
42. [**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/)
43. [**West-of-N: Synthetic Preferences for Self-Improving Reward Models arXiv:2401.12086**Alizee Pace, Jonathan Mallinson, Eric Malmi, et al.*2024 · 22 citations*](https://md.research.elamur.ai/free/en/papers/pace-2024-west-n-synthetic-preferences-self/)
44. **[STaR-SQL: Self-Taught Reasoner for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/he-2025-star-sql-self-taught-reasoner/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingqian He, Yongliang Shen, Wenqi Zhang, et al.*2025 · 17 citations*
45. [**Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models arXiv:2503.24377**Rui Wang, Hongru Wang, Boyang Xue, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-harnessing-reasoning-economy-survey-efficient/)
46. [**A Survey on Latent Reasoning arXiv:2507.06203**Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-survey-latent-reasoning/)
47. **[Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2025-interactive-evolution-neural-symbolic-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangzhi Xu, Qiushi Sun, Kanzhi Cheng, et al.*2025 · 15 citations*
48. [**Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics**Stefano Perrella, Lorenzo Proietti, Pere-Lluís Huguet Cabot, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/perrella-2024-beyond-correlation-interpretable-evaluation-machine/)
49. **[Tailoring Self-Rationalizers with Multi-Reward Distillation](https://md.research.elamur.ai/free/en/papers/ramnath-2023-tailoring-self-rationalizers-multi-reward/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Sahana Ramnath, Brihi Joshi, Skyler Hallinan, et al.*2023 · 14 citations*
50. **[NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neurons](https://md.research.elamur.ai/free/en/papers/dong-2026-neureasoner-explainable-controllable-unified-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haonan Dong, Kehan Jiang, Haoran Ye, et al.*2026 · 13 citations*
51. **[POSITION BIAS MITIGATES POSITION BIAS: Mitigate Position Bias Through Inter-Position Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/wang-2025-position-bias-mitigates-position-bias/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yifei Wang, Feng Xiong, Yong Wang, et al.*2025 · 13 citations*
52. **[Condor: Enhance LLM Alignment with Knowledge-Driven Data Synthesis and Refinement](https://md.research.elamur.ai/free/en/papers/cao-2025-condor-enhance-llm-alignment-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maosong Cao, Taolin Zhang, Mo Li, et al.*2025 · 11 citations*
53. **[HS-STaR: Hierarchical Sampling for Self-Taught Reasoners via Difficulty Estimation and Budget Reallocation](https://md.research.elamur.ai/free/en/papers/xiong-2025-hs-star-hierarchical-sampling-self/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Feng Xiong, Hongling Xu, Yifei Wang, et al.*2025 · 9 citations*
54. **[Superficial Self-Improved Reasoners Benefit from Model Merging](https://md.research.elamur.ai/free/en/papers/yuan-2025-superficial-self-improved-reasoners-benefit/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiangchi Yuan, Chunhui Zhang, Zheyuan Liu, et al.*2025 · 8 citations*
55. **[dLLM: Simple Diffusion Language Modeling](https://md.research.elamur.ai/free/en/papers/zhou-2026-dllm-simple-diffusion-language-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhanhui Zhou, Lingjie Chen, Hanghang Tong, et al.*2026 · 3 citations*
56. **[Learning Multilingual Agentic Policy to Control Sycophancy](https://md.research.elamur.ai/free/en/papers/ranaldi-2026-learning-multilingual-agentic-policy-control/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Leonardo Ranaldi, Giulia Pucci*2026 · 2 citations*
57. **[On-Policy Self-Distillation for Efficient Diffusion Language Models with Early-Stage Calibration](https://md.research.elamur.ai/free/en/papers/zhu-2026-policy-self-distillation-efficient-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Huaisheng Zhu, MingYu Liu, Junze Liu, et al.*2026 · 2 citations*
58. **[One Refiner to Unlock Them All: Inference-Time Reasoning Elicitation via Reinforcement Query Refinement](https://md.research.elamur.ai/free/en/papers/zhou-2026-one-refiner-unlock-them-all/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixiao Zhou, Dongzhou Cheng, Zhiliang wu, et al.*2026 · 2 citations*
59. **[Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration](https://md.research.elamur.ai/free/en/papers/zhong-2026-efficient-self-evaluation-diffusion-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linhao Zhong, Linyu Wu, Wen Wang, et al.*2026 · 1 citation*
60. **[Energy Matching based Preference Learning for Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/shankar-2026-energy-matching-based-preference-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Shiv Shankar*2026 · 1 citation*
61. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026*
62. **[Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models](https://md.research.elamur.ai/free/en/papers/zou-2026-breaking-block-boundaries-anchor-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shun Zou, Yong Wang, Zehui Chen, et al.*2026*
63. **[CoEvolve: Training LLM Agents via Agent-Data Mutual Evolution](https://md.research.elamur.ai/free/en/papers/yang-2026-coevolve-training-llm-agents-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shidong Yang, Ziyu Ma, Tongwen Huang, et al.*2026*
64. **[DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-diffa-2-practical-diffusion-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaming Zhou, Xuxin Cheng, Shiwan Zhao, et al.*2026*
65. **[DOS: Dependency-Oriented Sampler for Masked Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-dos-dependency-oriented-sampler-masked/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xueyu Zhou, Yangrong Hu, Jian Huang*2026*
66. **[DuIVRS-2: An LLM-based Interactive Voice Response System for Large-scale POI Attribute Acquisition](https://md.research.elamur.ai/free/en/papers/zhang-2026-duivrs-2-llm-based-interactive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Le Zhang, Shengming Zhang, Rui Zha, et al.*2026*
67. **[EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/yeom-2026-epicar-knowing-what-you-don/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jewon Yeom, Jaewon Sok, Seonghyeon Park, et al.*2026*
68. **[PURE: Post-hoc Unlocking and REfinement for Discrete Diffusion Decoding](https://md.research.elamur.ai/free/en/papers/park-2026-pure-post-hoc-unlocking-refinement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangryeol Park, Kunhui Lee, Hanback Choi, et al.*2026*
69. **[SERM: Self-Evolving Relevance Model with Agent-Driven Learning from Massive Query Streams](https://md.research.elamur.ai/free/en/papers/wang-2026-serm-self-evolving-relevance-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenglong Wang, Canjia Li, Xingzhao Zhu, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/arnaud-doucet/) — Arnaud Doucet