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

195 citations of their works from 194 papers of our library (of the 149,439 whose bibliographies we read) · 38 with a page here, the most cited first · [← Yusen Zhang](https://md.research.elamur.ai/free/en/authors/yusen-zhang/)

1. **[UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models](https://md.research.elamur.ai/free/en/papers/xie-2022-unifiedskg-unifying-multi-tasking-structured/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianbao Xie, Chen Henry Wu, Peng Shi, et al.*2022 · 407 citations*
2. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
3. [**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 · 192 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-think-that-much-2-3/)
4. [**Training Language Models to Self-Correct via Reinforcement Learning arXiv:2409.12917**Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2024-training-language-models-self-correct/)
5. **[ProcessBench: Identifying Process Errors in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/zheng-2025-processbench-identifying-process-errors-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chujie Zheng, Zhenru Zhang, Beichen Zhang, et al.*2025 · 116 citations*
6. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 citations*
7. **[Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?](https://md.research.elamur.ai/free/en/papers/zeng-2025-revisiting-test-time-scaling-o1/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.*2025 · 38 citations*
8. **[CompAct: Compressing Retrieved Documents Actively for Question Answering](https://md.research.elamur.ai/free/en/papers/yoon-2024-compact-compressing-retrieved-documents-actively/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chanwoong Yoon, Taewhoo Lee, Hyeon Hwang, et al.*2024 · 34 citations*
9. **[PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides](https://md.research.elamur.ai/free/en/papers/zheng-2025-pptagent-generating-evaluating-presentations-beyond/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Zheng, Xinyan Guan, Hao Kong, et al.*2025 · 30 citations*
10. **[Understanding the Dark Side of LLMs' Intrinsic Self-Correction](https://md.research.elamur.ai/free/en/papers/zhang-2025-understanding-dark-side-llms-intrinsic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingjie Zhang, Di Wang, Haoting Qian, et al.*2025 · 21 citations*
11. **[MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2025-magicore-multi-agent-iterative-coarse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Justin Chen, Archiki Prasad, Swarnadeep Saha, et al.*2025 · 20 citations*
12. [**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/)
13. **[Understanding the Information Propagation Effects of Communication Topologies in LLM-based Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/shen-2025-understanding-information-propagation-effects-communication/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xu Shen, Yixin Liu, Yiwei Dai, et al.*2025 · 15 citations*
14. **[Confidence v.s. Critique: A Decomposition of Self-Correction Capability for LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-confidence-v-s-critique-decomposition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhe Yang, Yichang Zhang, Yudong Wang, et al.*2025 · 11 citations*
15. **[An Empirical Study of LLM-as-a-Judge: How Design Choices Impact Evaluation Reliability](https://md.research.elamur.ai/free/en/papers/yamauchi-2026-empirical-study-llm-as-judge/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Yusuke Yamauchi, Taro Yano, Masafumi Oyamada*2026 · 10 citations*
16. **[AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time](https://md.research.elamur.ai/free/en/papers/zhang-2025-alphaone-reasoning-models-thinking-slow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junyu Zhang, Runpei Dong, Han Wang, et al.*2025 · 10 citations*
17. **[ReAgent: Reversible Multi-Agent Reasoning for Knowledge-Enhanced Multi-Hop QA](https://md.research.elamur.ai/free/en/papers/xinjie-2025-reagent-reversible-multi-agent-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhao Xinjie, Fan Gao, Xingyu Song, et al.*2025 · 8 citations*
18. **[The Validation Gap: A Mechanistic Analysis of How Language Models Compute Arithmetic but Fail to Validate It](https://md.research.elamur.ai/free/en/papers/bertolazzi-2025-validation-gap-mechanistic-analysis-how/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Leonardo Bertolazzi, Philipp Mondorf, Barbara Plank, et al.*2025 · 6 citations*
19. **[Exploring Iterative Controllable Summarization with Large Language Models](https://md.research.elamur.ai/free/en/papers/ryu-2026-exploring-iterative-controllable-summarization-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sangwon Ryu, Heejin Do, Daehui Kim, et al.*2026 · 2 citations*
20. **[From Belief Entrenchment to Robust Reasoning in LLM Agents](https://md.research.elamur.ai/free/en/papers/oh-2026-belief-entrenchment-robust-reasoning-llm/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jihwan Oh, Minchan Jeong, Jongwoo Ko, et al.*2026 · 2 citations*
21. **[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*
22. **[From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-passive-metric-active-signal-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaxin Zhang, Wendi Cui, Zhuohang Li, et al.*2026 · 1 citation*
23. **[KG-MuLQA: A Framework for KG-based Multi-Level QA Extraction and Long-Context LLM Evaluation](https://md.research.elamur.ai/free/en/papers/tatarinov-2026-kg-mulqa-framework-kg-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nikita Tatarinov, Vidhyakshaya Kannan, Haricharana Srinivasa, et al.*2026 · 1 citation*
24. **[ROSCO-Omni: Multimodal LLM-Based Communication Understanding for Non- and Minimally-Speaking Autistic Individuals](https://md.research.elamur.ai/free/en/papers/shah-2026-rosco-omni-multimodal-llm-based/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Siddhant Bikram Shah, Kristina T. Johnson*2026 · 1 citation*
25. **[Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration](https://md.research.elamur.ai/free/en/papers/liu-2026-scaling-external-knowledge-input-beyond/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijun Liu, Zhennan Wan, Peng Li, et al.*2026 · 1 citation*
26. **[Adaptive Planning for Multi-Attribute Controllable Summarization with Monte Carlo Tree Search](https://md.research.elamur.ai/free/en/papers/ryu-2026-adaptive-planning-multi-attribute-controllable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sangwon Ryu, Heejin Do, Yunsu Kim, et al.*2026*
27. **[Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-agent-gwo-collaborative-agents-dynamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xudong Wang, Chaoning Zhang, Chenghao Li, et al.*2026*
28. **[ARCHITECT: Uncertainty-Aware Dynamic Tool Learning via Causal Intervention for Open-World Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-architect-uncertainty-aware-dynamic-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangyi Wang, Jiexiang Xu, Bingnan Yu, et al.*2026*
29. **[Boosting Self-Consistency with Ranking](https://md.research.elamur.ai/free/en/papers/marina-2026-boosting-self-consistency-ranking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maria Marina, Daniil Moskovskiy, Sergey Pletenev, et al.*2026*
30. **[Can LLMs Self-Correct Table Reasoning Errors?](https://md.research.elamur.ai/free/en/papers/shaikh-2026-can-llms-self-correct-table/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Farseen Shaikh*2026*
31. **[CORE: Measuring Multi-Agent LLM Interaction Quality under Game-Theoretic Pressures](https://md.research.elamur.ai/free/en/papers/pandey-2026-core-measuring-multi-agent-llm/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Punya Syon Pandey, Yongjin Yang, Jiarui Liu, et al.*2026*
32. **[Feedback Is The Key for Automated Survey Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-feedback-is-key-automated-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyi Xu, Zhe Zhao, Tianshuo Wei, et al.*2026*
33. **[NeuralFSM: Adaptive Multi-Agent Coordination via Learning Finite-State Execution Policy](https://md.research.elamur.ai/free/en/papers/wang-2026-neuralfsm-adaptive-multi-agent-coordination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiye Wang, Yu Wang, Jianbin Li, et al.*2026*
34. **[PACE: Predictive Adaptive Context Extraction for Long-Horizon LLM Agents](https://md.research.elamur.ai/free/en/papers/wei-2026-pace-predictive-adaptive-context-extraction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Wei, Xiao Peng, Tt, et al.*2026*
35. **[PropGenie: A Multi-Agent Conversational Framework for Real Estate Assistance](https://md.research.elamur.ai/free/en/papers/shen-2026-propgenie-multi-agent-conversational-framework/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chang Shen, Shaozu Yuan, Kuizong Wu, et al.*2026*
36. **[Scaling Performance and Low-Resource Annotation with Many-Shot In-Context Learning for Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/zhang-2026-scaling-performance-low-resource-annotation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qi Zhang, Fangping Lan, Cornelia Caragea, et al.*2026*
37. **[TeachMaster: Generative Teaching via Code](https://md.research.elamur.ai/free/en/papers/wang-2026-teachmaster-generative-teaching-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuheng Wang, Runde Yang, Lin Wu, et al.*2026*
38. **[ThreadSumm: Summarization of Nested Discourse Threads Using Tree of Thoughts](https://md.research.elamur.ai/free/en/papers/olabisi-2026-threadsumm-summarization-nested-discourse-threads/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Olubusayo Olabisi, Ekata Mitra, Ameeta Agrawal*2026*

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

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