---
title: "Who cites Wentong Chen — 124 papers of our library"
description: "124 papers of the Elamur Research library cite the works of Wentong Chen, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/wentong-chen/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/wentong-chen/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Wentong Chen](https://md.research.elamur.ai/free/en/authors/wentong-chen/) / cited by

# Who cites Wentong Chen

124 citations of their works from 124 papers of our library (of the 149,439 whose bibliographies we read) · 36 with a page here, the most cited first · [← Wentong Chen](https://md.research.elamur.ai/free/en/authors/wentong-chen/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
2. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
3. **[Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 208 citations*
4. **[Investigating Data Contamination in Modern Benchmarks for Large Language Models](https://md.research.elamur.ai/free/en/papers/deng-2024-investigating-data-contamination-modern-benchmarks/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.*2024 · 137 citations*
5. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
6. **[Task Contamination: Language Models May Not Be Few-Shot Anymore](https://md.research.elamur.ai/free/en/papers/li-2023-task-contamination-language-models-may/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Changmao Li, Jeffrey Flanigan*2023 · 89 citations*
7. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
8. [**BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval arXiv:2407.12883**Hongjin Su, Howard Yen, Mengzhou Xia, et al.*2024 · 77 citations*](https://md.research.elamur.ai/free/en/papers/su-2024-bright-realistic-challenging-benchmark-reasoning/)
9. [**SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling arXiv:2312.15166**Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-solar-10-7b-scaling-large/)
10. [**Benchmarking Benchmark Leakage in Large Language Models arXiv:2404.18824**Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/)
11. [**AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation arXiv:2311.07397**Junyang Wang, Yuhang Wang, Guohai Xu, et al.*2023 · 67 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-amber-llm-free-multi-dimensional/)
12. **[A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners](https://md.research.elamur.ai/free/en/papers/jiang-2024-peek-into-token-bias-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, et al.*2024 · 64 citations*
13. **[Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?](https://md.research.elamur.ai/free/en/papers/balepur-2024-artifacts-or-abduction-how-do/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger*2024 · 52 citations*
14. [**Kimi Linear: An Expressive, Efficient Attention Architecture arXiv:2510.26692**Kimi Team, Yu Zhang, Zongyu Lin, et al.*2025 · 51 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-linear-expressive-efficient/)
15. [**LV-Eval: A Balanced Long-Context Benchmark with 5 Length Levels Up to 256K arXiv:2402.05136**Tao Yuan, Xuefei Ning, Dong Zhou, et al.*2024 · 41 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2024-lv-eval-balanced-long-context/)
16. **[Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2025-benchmark-self-evolving-multi-agent/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Siyuan Wang, Zhuohan Long, Zhihao Fan, et al.*2025 · 30 citations*
17. **[Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above](https://md.research.elamur.ai/free/en/papers/balepur-2025-which-these-best-describes-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber*2025 · 28 citations*
18. **[TACO: Enhancing Multimodal In-context Learning via Task Mapping-Guided Sequence Configuration](https://md.research.elamur.ai/free/en/papers/li-2025-taco-enhancing-multimodal-context-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yanshu Li, Jianjiang Yang, Tian Yun, et al.*2025 · 22 citations*
19. [**Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluation arXiv:2407.08940**Biqing Qi, Kaiyan Zhang, Kai Tian, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-large-language-models-biomedical-hypothesis/)
20. **[DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph](https://md.research.elamur.ai/free/en/papers/zhang-2024-darg-dynamic-evaluation-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhehao Zhang, Jiaao Chen, Diyi Yang*2024 · 17 citations*
21. [**WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models arXiv:2311.15930**Youssef Benchekroun, Megi Dervishi, Mark Ibrahim, et al.*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/benchekroun-2023-worldsense-synthetic-benchmark-grounded-reasoning/)
22. **[Beyond Math: Stories as a Testbed for Memorization-Constrained Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/jiang-2026-beyond-math-stories-as-testbed/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yuxuan Jiang, Francis Ferraro*2026 · 10 citations*
23. **[Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning](https://md.research.elamur.ai/free/en/papers/dai-2026-psyche-r1-reliable-psychological-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chongyuan Dai, Jinpeng Hu, Hongchang Shi, et al.*2026 · 8 citations*
24. [**MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction arXiv:2604.27393**Junbo Cui, Bokai Xu, Chongyi Wang, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/cui-2026-minicpm-o-4-5/)
25. **[Bit-by-Bit: Progressive QAT Strategy with Outlier Channel Splitting for Stable Low-Bit LLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-bit-bit-progressive-qat-strategy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binxing Xu, Hao Gu, Lujun Li, et al.*2026 · 3 citations*
26. **[How Quantization Shapes Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/marcuzzi-2026-how-quantization-shapes-bias-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Federico Marcuzzi, Xuefei Ning, Roy Schwartz, et al.*2026 · 3 citations*
27. [**Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models arXiv:2605.11887**Boyi Deng, Xu Wang, Yaoning Wang, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/deng-2026-qwen-scope-turning-sparse/)
28. [**MiniCPM-SALA: Hybridizing Sparse and Linear Attention for Efficient Long-Context Modeling arXiv:2602.11761**MiniCPM Team, Wenhao An, Yingfa Chen, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/minicpm-team-2026-minicpm-sala-hybridizing-sparse/)
29. [**MiniMax Sparse Attention arXiv:2606.13392**Xunhao Lai, Weiqi Xu, Yufeng Yang, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/lai-2026-minimax-sparse-attention/)
30. **[When Flores Bloomz Wrong: Cross-Direction Contamination in Machine Translation Evaluation](https://md.research.elamur.ai/free/en/papers/tan-2026-when-flores-bloomz-wrong-cross/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**David Tan, Pinzhen Chen, Josef van Genabith, et al.*2026 · 2 citations*
31. [**GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs? arXiv:2412.10056**Zhikai Lei, Tianyi Liang, Hanglei Hu, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/lei-2024-gaokao-eval-high-scores/)
32. **[BenchNavigator: A Discovery Interface for Comparing LLM Benchmarks](https://md.research.elamur.ai/free/en/papers/sokol-2026-benchnavigator-discovery-interface-comparing-llm/) [Workshop on Evaluating Evaluations (EvalEval)](https://md.research.elamur.ai/free/en/venues/evaleval/)**Anna Sokol, Inge Vejsbjerg, Elizabeth M. Daly, et al.*2026*
33. **[LinguaGame: A Linguistically Grounded Game-Theoretic Paradigm for Multi-Agent Dialogue Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-linguagame-linguistically-grounded-game-theoretic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxiao Ye, Yiming Zhang, Yiran Rex Ma, et al.*2026*
34. **[MMTutorBench: The First Multimodal Benchmark for AI Math Tutoring](https://md.research.elamur.ai/free/en/papers/yang-2026-mmtutorbench-first-multimodal-benchmark-ai/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tengchao Yang, Sichen Guo, Mengzhao Jia, et al.*2026*
35. **[Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models](https://md.research.elamur.ai/free/en/papers/shah-2026-too-nice-tell-truth-quantifying/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arya Shah, Deepali Mishra, Chaklam Silpasuwanchai*2026*
36. [**360Zhinao Technical Report arXiv:2405.13386***2024*](https://md.research.elamur.ai/free/en/papers/360zhinao-team-2024-360zhinao-technical-report/)

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

- [← back to](https://md.research.elamur.ai/free/en/authors/wentong-chen/) — Wentong Chen