---
title: "Who cites Weiyang Liu — page 3 — 655 papers of our library"
description: "655 papers of the Elamur Research library cite the works of Weiyang Liu, found in their bibliographies · page 3 of 3 · 201–248; the most cited first."
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---
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# Who cites Weiyang Liu

666 citations of their works from 655 papers of our library (of the 149,439 whose bibliographies we read) · 248 with a page here, the most cited first · page 3 of 3 · 201–248 · [← Weiyang Liu](https://md.research.elamur.ai/free/en/authors/weiyang-liu/)

[← prev](https://md.research.elamur.ai/free/en/authors/weiyang-liu/cited-by/page/2/) [1](https://md.research.elamur.ai/free/en/authors/weiyang-liu/cited-by/) [2](https://md.research.elamur.ai/free/en/authors/weiyang-liu/cited-by/page/2/) **3**

201. **[BeamLoRA: Beam-Constraint Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/gu-2025-beamlora-beam-constraint-low-rank/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Naibin Gu, Zhenyu Zhang, Xiyu Liu, et al.*2025 · 6 citations*
202. **[FineReason: Evaluating and Improving LLMs' Deliberate Reasoning through Reflective Puzzle Solving](https://md.research.elamur.ai/free/en/papers/chen-2025-finereason-evaluating-improving-llms-deliberate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guizhen Chen, Weiwen Xu, Hao Zhang, et al.*2025 · 6 citations*
203. **[From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-128k-4m-efficient-training-ultra/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chejian Xu, Wei Ping, Peng Xu, et al.*2026 · 5 citations*
204. [**ProofFlow: A Dependency Graph Approach to Faithful Proof Autoformalization arXiv:2510.15981**Rafael Cabral, Tuan Manh Do, Xuejun Yu, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/cabral-2025-proofflow-dependency-graph-approach-faithful/)
205. **[Select2Reason: Efficient Instruction-Tuning Data Selection for Long-CoT Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2026-select2reason-efficient-instruction-tuning-data/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cehao Yang, Xueyuan Lin, Xiaojun Wu, et al.*2026 · 4 citations*
206. **[What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/jia-2026-what-makes-good-curriculum-disentangling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaning Jia, Chunhui Zhang, Xingjian Diao, et al.*2026 · 4 citations*
207. **[Evaluating Numeracy of Language Models as a Natural Language Inference Task](https://md.research.elamur.ai/free/en/papers/mahendra-2025-evaluating-numeracy-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rahmad Mahendra, Damiano Spina, Lawrence Cavedon, et al.*2025 · 4 citations*
208. [**Less is More: Selective Reflection for Compatible and Efficient Knowledge Distillation in Large Language Models arXiv:2508.06135**Lingyuan Liu, Mengxiang Zhang*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-less-more-selective-reflection-compatible/)
209. **[Beyond Templates: Dynamic Adaptation of Reasoning Demonstrations via Feasibility-Aware Exploration](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-templates-dynamic-adaptation-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yong Wu, Weihang Pan, Ke Li, et al.*2026 · 3 citations*
210. **[LLM-Powered Benchmark Factory: Reliable, Generic, and Efficient](https://md.research.elamur.ai/free/en/papers/yuan-2026-llm-powered-benchmark-factory-reliable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiwen Yuan, Shaoxiong Feng, Yiwei Li, et al.*2026 · 3 citations*
211. **[a1: Steep Test-time Scaling Law via Environment Augmented Generation](https://md.research.elamur.ai/free/en/papers/mei-2026-a1-steep-test-time-scaling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 2 citations*
212. **[Aligning Large Language Models via Fully Self-Synthetic Data](https://md.research.elamur.ai/free/en/papers/yin-2026-aligning-large-language-models-fully/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangjian Yin, Zhepei Wei, Xinyu Zhu, et al.*2026 · 2 citations*
213. **[Bridging the Culture Gap: A Framework for LLM-Driven Socio-Cultural Localization of Math Word Problems in Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/azime-2026-bridging-culture-gap-framework-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Israel Abebe Azime, Tadesse Destaw Belay, Dietrich Klakow, et al.*2026 · 1 citation*
214. **[CoAct: Co-Active LLM Preference Learning with Human-AI Synergy](https://md.research.elamur.ai/free/en/papers/xu-2026-coact-co-active-llm-preference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.*2026 · 1 citation*
215. **[Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training](https://md.research.elamur.ai/free/en/papers/yang-2026-data-mixing-agent-learning-re/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kailai Yang, Xiao Liu, Lei Ji, et al.*2026 · 1 citation*
216. **[From Individual to Common: An Early Exploration of Consensus in Non-verifiable Data for Balanced Preference Optimization](https://md.research.elamur.ai/free/en/papers/yin-2026-individual-common-early-exploration-consensus/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangjian Yin, Zhouxing Shi*2026 · 1 citation*
217. **[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*
218. **[MERLIN: Multi-Stage Curriculum Alignment for Multilingual Encoder-LLM Integration in Cross-Lingual Reasoning](https://md.research.elamur.ai/free/en/papers/uemura-2026-merlin-multi-stage-curriculum-alignment/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kosei Uemura, David Guzmán, Quang Phuoc Nguyen, et al.*2026 · 1 citation*
219. **[Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards](https://md.research.elamur.ai/free/en/papers/pisano-2026-process-reward-models-meet-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Raffaele Pisano, Roberto Navigli*2026 · 1 citation*
220. **[The Bidirectional Process Reward Model](https://md.research.elamur.ai/free/en/papers/zhang-2026-bidirectional-process-reward-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingyin Zhang, Jun Gao, Xiaoxue Ren, et al.*2026 · 1 citation*
221. **[Accelerating LLM Fine-Tuning via Embedding Knowledge Transfer](https://md.research.elamur.ai/free/en/papers/peng-2026-accelerating-llm-fine-tuning-embedding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Meishu Peng, Ziyue Zhang, Yi Zhang, et al.*2026*
222. **[Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-length-scaling-synergizing-breadth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyuan Zhang, Yufei Wang, Tianhe Wu, et al.*2026*
223. **[Calibrated Progressive Distillation: Co-Designing Curriculum and Target Mixing for Knowledge Distillation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-calibrated-progressive-distillation-co-designing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mengxiang Zhang, Lingyuan Liu*2026*
224. **[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*
225. **[FLAIR: Steering LLM Mathematical Problem Solving based on A Fuzzy-Logic-AssIsted Reasoner](https://md.research.elamur.ai/free/en/papers/wu-2026-flair-steering-llm-mathematical-problem/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Wu, Hongru Sun, Wanqing Li, et al.*2026*
226. **[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*
227. **[GALA: Geometric Data Selection with Strategic Prospecting for Large Language Model Self-training](https://md.research.elamur.ai/free/en/papers/xie-2026-gala-geometric-data-selection-strategic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhongwei Xie, Ruihao Liao, Zimo Wang, et al.*2026*
228. **[GenesisFunc: Multi-Agent Data Generation for Accurate and Generalizable Function-Calling](https://md.research.elamur.ai/free/en/papers/xu-2026-genesisfunc-multi-agent-data-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao-Xiang Xu, Chong Deng, Jiaqing Liu, et al.*2026*
229. **[HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs](https://md.research.elamur.ai/free/en/papers/peng-2026-hss-synth-humanities-social-sciences/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ru Peng, Tianyu Zhao, Xijun Gu, et al.*2026*
230. **[Language Models Learn Universal Representations of Numbers and Here's Why You Should Care](https://md.research.elamur.ai/free/en/papers/stefanik-2026-language-models-learn-universal-representations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michal Štefánik, Timothee Mickus, Marek Kadlčík, et al.*2026*
231. **[LeLoRA: Learnable Low-Rank Adaptation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-lelora-learnable-low-rank-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoling Zhou, Mingjie Zhang, Zhemg Lee, et al.*2026*
232. **[MuSe: Multi-Stage Graph Reasoning via Vision-Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-muse-multi-stage-graph-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanyu Wang, Xu Chu, Zhijie Tan, et al.*2026*
233. **[Pause or Fabricate? Training Language Models for Grounded Reasoning](https://md.research.elamur.ai/free/en/papers/qiu-2026-pause-or-fabricate-training-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiwen Qiu, Linjuan Wu, Yizhou Liu, et al.*2026*
234. **[PersonaTrace: Synthesizing Realistic Digital Footprints with LLM Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-personatrace-synthesizing-realistic-digital-footprints/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Minjia Wang, Yunfeng Wang, Xiao Ma, et al.*2026*
235. **[QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/qu-2026-quantumqa-enhancing-scientific-reasoning-physics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Songxin Qu, Tai-Ping Sun, Yun-Jie Wang, et al.*2026*
236. **[RanLoRA: Residual-aware Nonlinear Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/luo-2026-ranlora-residual-aware-nonlinear-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Luo, Yongbin Liu, Chunping Ouyang, et al.*2026*
237. **[ReActR: Reasoning through Error-Activated Reflection for LLM Post-Training](https://md.research.elamur.ai/free/en/papers/sun-2026-reactr-reasoning-through-error-activated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lina Sun*2026*
238. **[Revisiting Self-Play Preference Optimization: On the Role of Prompt Difficulty](https://md.research.elamur.ai/free/en/papers/xiao-2026-revisiting-self-play-preference-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yao Xiao, Jung-jae Kim, Roy Ka-Wei Lee, et al.*2026*
239. **[RouterHGC: Optimized Router for LLM-based Multi-Agent Systems via Heterogeneous Graph Contrastive Learning](https://md.research.elamur.ai/free/en/papers/xiao-2026-routerhgc-optimized-router-llm-based/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yitao Xiao, Shaoyong Guo, Guoming Yang, et al.*2026*
240. **[Routing with Generated Data: Annotation-Free LLM Skill Estimation and Expert Selection](https://md.research.elamur.ai/free/en/papers/niu-2026-routing-generated-data-annotation-free/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyi Niu, Justin Chen, Genta Indra Winata, et al.*2026*
241. **[RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library](https://md.research.elamur.ai/free/en/papers/wang-2026-rv-syn-rational-verifiable-mathematical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiapeng Wang, Jinhao Jiang, Zhiqiang Zhang, et al.*2026*
242. **[Safeguarding LLM Fine-tuning via Push-Pull Distributional Alignment](https://md.research.elamur.ai/free/en/papers/wang-2026-safeguarding-llm-fine-tuning-push/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haozhong Wang, Zhuo Li, Yibo Yang, et al.*2026*
243. **[SDC-LoRA: Singular-Subspace Drift Controlled LoRA to Mitigate Knowledge Forgetting](https://md.research.elamur.ai/free/en/papers/zhang-2026-sdc-lora-singular-subspace-drift/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Geyuan Zhang, Xiaofei Zhou, Shihao Liu, et al.*2026*
244. **[Synthetic Data Generation for Training Diversified Commonsense Reasoning Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-synthetic-data-generation-training-diversified/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianhui Zhang, Bei Peng, Danushka Bollegala*2026*
245. **[Tailored Primitive Initialization is the Secret Key to Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yao-2026-tailored-primitive-initialization-is-secret/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihang Yao, Guangtao Zeng, Raina Wu, et al.*2026*
246. **[Test-Time Training for Zero-Resource Dense Retrieval Reranking](https://md.research.elamur.ai/free/en/papers/liu-2026-test-time-training-zero-resource/) [Workshop on Towards Knowledgeable Foundation Models](https://md.research.elamur.ai/free/en/venues/knowfm/)**Shiyan Liu, Yichen Li*2026*
247. **[WeightLoRA: Keep Only Necessary Adapters](https://md.research.elamur.ai/free/en/papers/veprikov-2026-weightlora-keep-only-necessary-adapters/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Andrey Veprikov, Vladimir Solodkin, Zyl Alexander, et al.*2026*
248. **[WildSci: Advancing Scientific Reasoning from In-the-Wild Literature](https://md.research.elamur.ai/free/en/papers/liu-2026-wildsci-advancing-scientific-reasoning-wild/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengxiao Liu, Deepak Nathani, Zekun Li, et al.*2026*

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