---
title: "Who cites Yantao Liu — 92 papers of our library"
description: "92 papers of the Elamur Research library cite the works of Yantao Liu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yantao-liu/cited-by/"
---
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# Who cites Yantao Liu

93 citations of their works from 92 papers of our library (of the 149,439 whose bibliographies we read) · 33 with a page here, the most cited first · [← Yantao Liu](https://md.research.elamur.ai/free/en/authors/yantao-liu/)

1. **[Large Language Models for Generative Information Extraction: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2023-large-language-models-generative-information/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Derong Xu, Wei Chen, Wenjun Peng, et al.*2023 · 406 citations*
2. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
3. [**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/)
4. **[PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models](https://md.research.elamur.ai/free/en/papers/song-2025-prmbench-fine-grained-challenging-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingyang Song, Zhaochen Su, Xiaoye Qu, et al.*2025 · 63 citations*
5. [**RM-R1: Reward Modeling as Reasoning arXiv:2505.02387**Xiusi Chen, Gaotang Li, Ziqi Wang, et al.*2025 · 49 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-rm-r1-reward-modeling-reasoning/)
6. [**Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy arXiv:2507.01352**Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.*2025 · 48 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-skywork-reward-v2-scaling/)
7. [**Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning arXiv:2512.20848**NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.*2025 · 27 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-3-nano-open-efficient/)
8. **[OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment](https://md.research.elamur.ai/free/en/papers/liu-2026-openrubrics-scalable-synthetic-rubric-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianci Liu, Ran Xu, Tony Yu, et al.*2026 · 25 citations*
9. **[JuStRank: Benchmarking LLM Judges for System Ranking](https://md.research.elamur.ai/free/en/papers/gera-2025-justrank-benchmarking-llm-judges-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ariel Gera, Odellia Boni, Yotam Perlitz, et al.*2025 · 15 citations*
10. [**Constituency Parsing using LLMs arXiv:2310.19462**Xuefeng Bai, Jialong Wu, Yulong Chen, et al.*2023 · 14 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-constituency-parsing-using-llms/)
11. **[CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks](https://md.research.elamur.ai/free/en/papers/jiang-2026-codejudgebench-benchmarking-llm-as-judge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongchao Jiang, Yiming Chen, Yushi Cao, et al.*2026 · 13 citations*
12. **[Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/yang-2025-beyond-boundaries-learning-universal-entity/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yuming Yang, Wantong Zhao, Caishuang Huang, et al.*2025 · 11 citations*
13. **[ViLBench: A Suite for Vision-Language Process Reward Modeling](https://md.research.elamur.ai/free/en/papers/tu-2025-vilbench-suite-vision-language-process/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Haoqin Tu, Weitao Feng, Hardy Chen, et al.*2025 · 9 citations*
14. **[Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty](https://md.research.elamur.ai/free/en/papers/xue-2026-reason-only-when-needed-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 8 citations*
15. **[J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/xu-2026-j4r-learning-judge-equivalent-initial/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Austin Xu, Yilun Zhou, Xuan-Phi Nguyen, et al.*2026 · 3 citations*
16. **[Outcome Accuracy is Not Enough: Aligning the Reasoning Process of Reward Models](https://md.research.elamur.ai/free/en/papers/wang-2026-outcome-accuracy-is-not-enough/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binghai Wang, Yantao Liu, Yuxuan Liu, et al.*2026 · 3 citations*
17. **[RubricBench: Aligning Model-Generated Rubrics with Human Standards](https://md.research.elamur.ai/free/en/papers/zhou-2026-rubricbench-aligning-model-generated-rubrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyi Zhou, Qiyuan Zhang, Yufei Wang, et al.*2026 · 3 citations*
18. **[OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-opengenalign-preference-dataset-benchmark-trustworthy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanning Zhang, Juntong Song, Juno Zhu, et al.*2026 · 2 citations*
19. **[AdaJudge: Adaptive Multi-Perspective Judging for Reward Modeling](https://md.research.elamur.ai/free/en/papers/miao-2026-adajudge-adaptive-multi-perspective-judging/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongliang Miao, Yangyang Liang, Mengnan Du*2026*
20. **[AJ-Bench: Benchmarking Agent-as-a-Judge for Environment-Aware Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-aj-bench-benchmarking-agent-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wentao Shi, Yu Wang, Yuyang Zhao, et al.*2026*
21. **[Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling](https://md.research.elamur.ai/free/en/papers/wang-2026-aligning-agents-planning-benchmark-trajectory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaxuan Wang, Yulan Hu, Wenjin Yang, et al.*2026*
22. **[AnchorAlign: A Novel Anchor Alignment-enhanced Generative Method for Joint Named Entity Recognition and Relation Extraction](https://md.research.elamur.ai/free/en/papers/weng-2026-anchoralign-novel-anchor-alignment-enhanced/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaolong Weng, Yuanyun Zhou, Boyu Qiu, et al.*2026*
23. **[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*
24. **[Capability Decomposition for Unified Information Extraction via Hierarchical Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/zhou-2026-capability-decomposition-unified-information-extraction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jing Zhou, Peng Wang, Wenjun Ke, et al.*2026*
25. **[Contrastively Pre-trained Event Embeddings with Schema-free LLM Annotations](https://md.research.elamur.ai/free/en/papers/mtumbuka-2026-contrastively-pre-trained-event-embeddings/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Frank Mtumbuka, Steven Schockaert*2026*
26. **[Debiasing Reward Models via Causally Motivated Inference-Time Intervention](https://md.research.elamur.ai/free/en/papers/shinoda-2026-debiasing-reward-models-causally-motivated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kazutoshi Shinoda, Kosuke Nishida, Kyosuke Nishida*2026*
27. **[EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain](https://md.research.elamur.ai/free/en/papers/lu-2026-exceeds-extracting-complex-events-nugget/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi-Fan Lu, Xian-Ling Mao, Bo Wang, et al.*2026*
28. **[MMUIE: Massive Multi-Domain Universal Information Extraction for Long Documents](https://md.research.elamur.ai/free/en/papers/zhang-2026-mmuie-massive-multi-domain-universal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuyi Zhang, Zhenbin Chen, Shuting Li, et al.*2026*
29. **[PRISM: Probabilistic Reward Model with Inherent Structural Modeling](https://md.research.elamur.ai/free/en/papers/zhou-2026-prism-probabilistic-reward-model-inherent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhang Zhou, Yixin Cao, Yuchen Ni, et al.*2026*
30. **[ProUIE: A Macro-to-Micro Progressive Learning Method for LLM-based Universal Information Extraction](https://md.research.elamur.ai/free/en/papers/liu-2026-prouie-macro-micro-progressive-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenda Liu, Song Zhigang, Shuai Nie, et al.*2026*
31. **[ReflectRM: Boosting Generative Reward Models via Self-Reflection within a Unified Judgment Framework](https://md.research.elamur.ai/free/en/papers/qin-2026-reflectrm-boosting-generative-reward-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Qin, Liangxin Liu, Yu Liang, et al.*2026*
32. **[SDiaReward: Modeling and Benchmarking Spoken Dialogue Rewards with Modality and Colloquialness](https://md.research.elamur.ai/free/en/papers/lu-2026-sdiareward-modeling-benchmarking-spoken-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyu Lu, Yuhan Wang, Fan Zhuo, et al.*2026*
33. **[WildReward: Learning Reward Models from In-the-Wild Human Interactions](https://md.research.elamur.ai/free/en/papers/peng-2026-wildreward-learning-reward-models-wild/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2026*

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

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