---
title: "Who cites Yinmin Zhong — page 2 — 1,090 papers of our library"
description: "1,090 papers of the Elamur Research library cite the works of Yinmin Zhong, found in their bibliographies · page 2 of 2 · 101–171; the most…"
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---
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# Who cites Yinmin Zhong

1,379 citations of their works from 1,090 papers of our library (of the 149,439 whose bibliographies we read) · 171 with a page here, the most cited first · page 2 of 2 · 101–171 · [← Yinmin Zhong](https://md.research.elamur.ai/free/en/authors/yinmin-zhong/)

[← prev](https://md.research.elamur.ai/free/en/authors/yinmin-zhong/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/yinmin-zhong/cited-by/) **2**

101. **[CAMO: An Agentic Framework for Automated Causal Discovery from Micro Behaviors to Macro Emergence in LLM Agent Simulations](https://md.research.elamur.ai/free/en/papers/yu-2026-camo-agentic-framework-automated-causal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangning Yu, Yuwei Guo, Yuqi Hou, et al.*2026*
102. **[Can AI Revise Research Papers with Human Review Feedback? An Empirical Study and Benchmark](https://md.research.elamur.ai/free/en/papers/luo-2026-can-ai-revise-research-papers/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Luo, Hong Huang, Jianxun Lian, et al.*2026*
103. **[Chaining the Evidence: Robust Reinforcement Learning for Deep Search Agents with Citation-Aware Rubric Rewards](https://md.research.elamur.ai/free/en/papers/zhang-2026-chaining-evidence-robust-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiajie Zhang, Xin Lv, Ling Feng, et al.*2026*
104. **[ChemReason-Bench: Benchmarking Large Language Models for Procedural Reasoning in Experimental Chemistry](https://md.research.elamur.ai/free/en/papers/zhang-2026-chemreason-bench-benchmarking-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinwei Zhang, Xucheng Liang, Yu Zhang, et al.*2026*
105. **[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*
106. **[ComfyFlow: Benchmarking LLMs for AIGC Workflow Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-comfyflow-benchmarking-llms-aigc-workflow/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenran Xu, Yiyu Wang, Yunxin Li, et al.*2026*
107. **[Creating Multilingual Mental Health Dialogue Datasets: Limits of Persona-Based Localization via Nationality and Language](https://md.research.elamur.ai/free/en/papers/xu-2026-creating-multilingual-mental-health-dialogue/) [Workshop on Computational Linguistics and Clinical Psychology](https://md.research.elamur.ai/free/en/venues/clpsych/)**Yunkai Xu, Saeed Abdullah*2026*
108. **[Danger Depends on the Mind: A Theory-of-Mind Grounded Dataset and Model for Context-Dependent Dangerous Speech](https://md.research.elamur.ai/free/en/papers/shi-2026-danger-depends-mind-theory-mind/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanchen Shi, Longyin Zhang, Guodong Zhou, et al.*2026*
109. **[DefGen-Bench: A Benchmark for Chinese Criminal Defence Opinion Generation in LegalAI](https://md.research.elamur.ai/free/en/papers/zhang-2026-defgen-bench-benchmark-chinese-criminal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Senbo Zhang, Qiqi Wang, Fanghao Lou, et al.*2026*
110. **[Detoxification for LLM: From Dataset Itself](https://md.research.elamur.ai/free/en/papers/shao-2026-detoxification-llm-dataset-itself/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Shao, Yihang Wang, Gao yu Zhu, et al.*2026*
111. **[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*
112. **[Distributional Clarity: The Hidden Driver of RL-Friendliness in Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-distributional-clarity-hidden-driver-rl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoning Sun, Mingzhu Cai, Huang He, et al.*2026*
113. **[Dual-Cluster Memory Agent: Resolving Multi-Paradigm Ambiguity in Optimization Problem Solving](https://md.research.elamur.ai/free/en/papers/zhang-2026-dual-cluster-memory-agent-resolving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Zhang, Yuchen Wan, Boxuan Zhang, et al.*2026*
114. **[Efficient KL Divergence Estimation via Truncated Top-K Integration for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-efficient-kl-divergence-estimation-truncated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyuan Wang, Luozhijie Jin, Bo Wang, et al.*2026*
115. **[EfficientTool: A Cost-Effective Aligning Framework for Tool-Conditioned Agents in SME Scenarios](https://md.research.elamur.ai/free/en/papers/mu-2026-efficienttool-cost-effective-aligning-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanqi Mu, Bingfeng Pi, Defei Xia, et al.*2026*
116. **[Enhancing Lexical Relation Mining with Structured Sememe Knowledge](https://md.research.elamur.ai/free/en/papers/wang-2026-enhancing-lexical-relation-mining-structured/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hansi Wang, Qiliang Liang, Yue Wang, et al.*2026*
117. **[Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/wang-2026-enhancing-llm-based-search-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junzhe Wang, Zhiheng Xi, Yajie Yang, et al.*2026*
118. **[Escaping the Sisyphus Dilemma: Experience Replay for Robust Text-to-Optimization Modeling](https://md.research.elamur.ai/free/en/papers/xie-2026-escaping-sisyphus-dilemma-experience-replay/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wantong Xie, Yinghao Chen, Yi-Xiang Hu, et al.*2026*
119. **[FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments](https://md.research.elamur.ai/free/en/papers/saeidi-2026-fama-failure-aware-meta-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Amir Saeidi, Venkatesh Mishra, Souradeep Mukhopadhyay, et al.*2026*
120. **[From Conversation to Evaluation: Benchmarking LLMs on Development Knowledge via SimpleDevQA](https://md.research.elamur.ai/free/en/papers/zhang-2026-conversation-evaluation-benchmarking-llms-development/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Zhang, Lianghong Guo, Yanlin Wang, et al.*2026*
121. **[FTibSuite: A Comprehensive Resource Suite for Tibetan Vision–Language Modeling](https://md.research.elamur.ai/free/en/papers/xu-2026-ftibsuite-comprehensive-resource-suite-tibetan/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guixian Xu, Yide Liang, Zeli Su, et al.*2026*
122. **[Good Reasoning Makes Good Demonstrations: Implicit Reasoning Quality Supervision via In-Context Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mei-2026-good-reasoning-makes-good-demonstrations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tiehua Mei, Minxuan Lv, Leiyu Pan, et al.*2026*
123. **[HearSay Benchmark: Do Audio LLMs Leak What They Hear?](https://md.research.elamur.ai/free/en/papers/wang-2026-hearsay-benchmark-do-audio-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jin Wang, Kaiwen Luo, Liang Lin, et al.*2026*
124. **[How Adversarial Environments Mislead Agentic AI?](https://md.research.elamur.ai/free/en/papers/zhan-2026-how-adversarial-environments-mislead-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhonghao Zhan, Huichi Zhou, Zhenhao Li, et al.*2026*
125. **[HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns](https://md.research.elamur.ai/free/en/papers/wang-2026-humanllm-benchmarking-improving-llm-anthropomorphism/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xintao Wang, Jian Yang, Weiyuan Li, et al.*2026*
126. **[ImpRIF: Stronger Implicit Reasoning Leads to Better Complex Instruction Following](https://md.research.elamur.ai/free/en/papers/yang-2026-imprif-stronger-implicit-reasoning-leads/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuancheng Yang, Lin Yang, Xu Wang, et al.*2026*
127. **[Know Your Place: Diagnosing Implicit Social Adaptation Failures in Chinese Large Language Models](https://md.research.elamur.ai/free/en/papers/tian-2026-know-your-place-diagnosing-implicit/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Tian, Jie Xing, Ziming Li, et al.*2026*
128. **[Latent-Condensed Transformer for Efficient Long Context Modeling](https://md.research.elamur.ai/free/en/papers/you-2026-latent-condensed-transformer-efficient-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zeng You, Yaofo Chen, Qiuwu Chen, et al.*2026*
129. **[Learning from Failures: Error Notebook-guided Secure Code Generation](https://md.research.elamur.ai/free/en/papers/zhong-2026-learning-failures-error-notebook-guided/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyu Zhong, Peng Lan, Zhifang Liao*2026*
130. **[LLMSurgeon: Diagnosing Data Mixture of Large Language Models](https://md.research.elamur.ai/free/en/papers/luo-2026-llmsurgeon-diagnosing-data-mixture-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaxin Luo, Jiacheng Cui, Xiaohan Zhao, et al.*2026*
131. **[Locate and Explain: Joint Multimodal Emotion Cause Extraction and Summarization in Conversation](https://md.research.elamur.ai/free/en/papers/wan-2026-locate-explain-joint-multimodal-emotion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jikun Wan, Chen Gong, Guohong Fu*2026*
132. **[Market-Bench: Benchmarking Large Language Models on Economic and Trade Competition](https://md.research.elamur.ai/free/en/papers/zheng-2026-market-bench-benchmarking-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yushuo Zheng, Huiyu Duan, Zicheng Zhang, et al.*2026*
133. **[MemWeaver: Weaving Hybrid Memories for Traceable Long-Horizon Agentic Reasoning](https://md.research.elamur.ai/free/en/papers/ye-2026-memweaver-weaving-hybrid-memories-traceable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Juexiang Ye, Xue Li, Yang Xinyu, et al.*2026*
134. **[MERIT Feedback Elicits Better Bargaining in LLM Negotiators](https://md.research.elamur.ai/free/en/papers/oh-2026-merit-feedback-elicits-better-bargaining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jihwan Oh, Murad Aghazada, Yooju Shin, et al.*2026*
135. **[MTRouter: Cost-Aware Multi-Turn LLM Routing with History–Model Joint Embeddings](https://md.research.elamur.ai/free/en/papers/zhang-2026-mtrouter-cost-aware-multi-turn/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiqun Zhang, Hao Li, Zihan Wang, et al.*2026*
136. **[NASIMLab at SemEval-2026 Task 9: A Comparative Analysis of Fine-Tuned Small Language Models vs. Generative Large Language Models for Multilingual Polarization Type Detection](https://md.research.elamur.ai/free/en/papers/sabhahit-2026-nasimlab-semeval-2026-task-9/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Neel Sabhahit, Sanjeevan Selvaganapathy, Mehwish Nasim*2026*
137. **[Neo-Classic: A Benchmark for Evaluating Linguistic-Aesthetic Reasoning in Classical Chinese Poetry](https://md.research.elamur.ai/free/en/papers/zhang-2026-neo-classic-benchmark-evaluating-linguistic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Han Zhang, Zihan Gu, Zhiyuan Wang, et al.*2026*
138. **[OptiVerse: A Comprehensive Benchmark towards Optimization Problem Solving](https://md.research.elamur.ai/free/en/papers/zhang-2026-optiverse-comprehensive-benchmark-optimization-problem/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyu Zhang, Boxuan Zhang, Yuchen Wan, et al.*2026*
139. **[PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/shen-2026-pegrl-improving-machine-translation-post/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yunzhi Shen, Hao Zhou, Xin Huang, et al.*2026*
140. **[PersonaArena: Dynamic Simulation for Evaluating and Enhancing Persona-Level Role-Playing in Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-personaarena-dynamic-simulation-evaluating-enhancing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenlong Shi, Jianxun Lian, Mingqi Wu, et al.*2026*
141. **[PrefRAG: Correcting Semantic Errors in Auto-Formalization for Logical Reasoning with Program Preference RAG](https://md.research.elamur.ai/free/en/papers/zhou-2026-prefrag-correcting-semantic-errors-auto/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuyin Zhou, Yongmei Liu*2026*
142. **[PRIME: A Process-Outcome Alignment Benchmark for Verifiable Reasoning in Mathematics and Engineering](https://md.research.elamur.ai/free/en/papers/wang-2026-prime-process-outcome-alignment-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangfeng Wang, Hangyu Guo, Yanlin Lai, et al.*2026*
143. **[Program-of-Thought Reveals LLM Abstraction Ceilings](https://md.research.elamur.ai/free/en/papers/zhou-2026-program-thought-reveals-llm-abstraction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mike Zhou, Fenil Bardoliya, Vivek Gupta, et al.*2026*
144. [**Qwen-AgentWorld: Language World Models for General Agents arXiv:2606.24597**Yuxin Zuo, Zikai Xiao, Li Sheng, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zuo-2026-qwen-agentworld-language-world/)
145. **[RADO: Reasoning Audit-Driven Optimization for Rigorous Reasoning in High-Stakes Domains](https://md.research.elamur.ai/free/en/papers/tan-2026-rado-reasoning-audit-driven-optimization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhijie Tan, Xu Chu, Guanyu Wang, et al.*2026*
146. **[RegTrack: A Fine-Grained Benchmark for Multi-Class Legal Change Detection](https://md.research.elamur.ai/free/en/papers/yu-2026-regtrack-fine-grained-benchmark-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joe Yu, Kevin Chenhao Li, Julian Ostarek*2026*
147. **[Reinforcement Learning with Semantic Rewards Enables Low-Resource Language Expansion without Alignment Tax](https://md.research.elamur.ai/free/en/papers/su-2026-reinforcement-learning-semantic-rewards-enables/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zeli Su, Ziyin Zhang, Zhou Liu, et al.*2026*
148. **[Reinforcement Learning–Guided Adaptive Tuning for Out-of-Distribution Harmful Text Detection](https://md.research.elamur.ai/free/en/papers/xiang-2026-reinforcement-learning-guided-adaptive-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengyu Xiang, Tinghao Chen, Boxu Han, et al.*2026*
149. **[RepoDistill: Distilling Repository Knowledge through Compression-Aware Budget Allocation and Policy Optimization](https://md.research.elamur.ai/free/en/papers/yin-2026-repodistill-distilling-repository-knowledge-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xin Yin, Zixiang Ding, Yiang Zhang, et al.*2026*
150. **[RoadMapper: A Multi-Agent System for Roadmap Generation of Solving Complex Research Problems](https://md.research.elamur.ai/free/en/papers/liu-2026-roadmapper-multi-agent-system-roadmap/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiacheng Liu, Zichen Tang, Zhongjun Yang, et al.*2026*
151. **[RST-Guarder: Enhancing Long-Context Robustness for Safeguards via RST Parsing and Probabilistic Inference](https://md.research.elamur.ai/free/en/papers/zhang-2026-rst-guarder-enhancing-long-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xu Zhang, Xiaojun Wan*2026*
152. **[ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-scalebox-enabling-high-fidelity-scalable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiasheng Zheng, Xin Zheng, Boxi Cao, et al.*2026*
153. **[SciExplore: Evaluating Autonomous Agents from Scientific Navigation to Information Integration](https://md.research.elamur.ai/free/en/papers/tang-2026-sciexplore-evaluating-autonomous-agents-scientific/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yinhao Tang, Youqing Fang, Yanan Sun, et al.*2026*
154. **[SCMAPR: Self-Correcting Multi-Agent Prompt Refinement for Complex-Scenario Text-to-Video Generation](https://md.research.elamur.ai/free/en/papers/yang-2026-scmapr-self-correcting-multi-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chengyi Yang, Pengzhen Li, Jiayin Qi, et al.*2026*
155. **[SearchGym: Bootstrapping Real-World Search Agents via Cost-Effective and High-Fidelity Environment Simulation](https://md.research.elamur.ai/free/en/papers/zhang-2026-searchgym-bootstrapping-real-world-search/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xichen Zhang, Ziyi He, Yinghao Zhu, et al.*2026*
156. **[Seeing Isn't Believing: Mitigating Belief Inertia via Active Intervention in Embodied Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-seeing-isn-t-believing-mitigating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanlin Wang, Chak Tou Leong, Jian Wang, et al.*2026*
157. **[Simplify-Pro: A Two-level and Progressive LLM-based Framework for Auto Long Text Simplification](https://md.research.elamur.ai/free/en/papers/zhou-2026-simplify-pro-two-level-progressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peng Zhou, Guangxin Li, Xiaoying Huang, et al.*2026*
158. **[StratMem-Bench: Evaluating Strategic Memory Use in Virtual Character Conversation Beyond Factual Recall](https://md.research.elamur.ai/free/en/papers/wu-2026-stratmem-bench-evaluating-strategic-memory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yerong Wu, Tianxing Wu, Minghao Zhu, et al.*2026*
159. **[Structured Episodic Event Memory](https://md.research.elamur.ai/free/en/papers/lu-2026-structured-episodic-event-memory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxuan Lu, Dongfang Li, Yukun Shi, et al.*2026*
160. **[Student Guides Teacher: Weak-to-Strong Inference via Spectral Orthogonal Exploration](https://md.research.elamur.ai/free/en/papers/wang-2026-student-guides-teacher-weak-strong/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dayu Wang, Jiaye Yang, Weikang Li, et al.*2026*
161. **[TinyJudge: Unverifiable Constraint Alignment via Lightweight Specialist Ensembles](https://md.research.elamur.ai/free/en/papers/zeng-2026-tinyjudge-unverifiable-constraint-alignment-lightweight/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yirong Zeng, Yufei Liu, Xiao Ding, et al.*2026*
162. **[ToolCPT: Improving Tool Utilization in LLM Agents via Continuous Pre-training](https://md.research.elamur.ai/free/en/papers/yang-2026-toolcpt-improving-tool-utilization-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifan Yang, Jinghui Lu, Evadeng, et al.*2026*
163. **[Towards Trustworthy Smart Contract Synthesis: A Multi-Agent Framework with Lean-Based Verification](https://md.research.elamur.ai/free/en/papers/zhang-2026-trustworthy-smart-contract-synthesis-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bowei Zhang, Hanbing Liu, Qixin Tian, et al.*2026*
164. **[Training-Free Test-Time Contrastive Learning for Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-training-free-test-time-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaiwen Zheng, Kai Zhou, Jinwu Hu, et al.*2026*
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