---
title: "Who cites Haotian Wang — 852 papers of our library"
description: "852 papers of the Elamur Research library cite the works of Haotian Wang, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/haotian-wang/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/haotian-wang/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Haotian Wang](https://md.research.elamur.ai/free/en/authors/haotian-wang/) / cited by

# Who cites Haotian Wang

852 citations of their works from 852 papers of our library (of the 149,439 whose bibliographies we read) · 172 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Haotian Wang](https://md.research.elamur.ai/free/en/authors/haotian-wang/)

**1** [2](https://md.research.elamur.ai/free/en/authors/haotian-wang/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/haotian-wang/cited-by/page/2/)

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. [**Hallucination is Inevitable: An Innate Limitation of Large Language Models arXiv:2401.11817**Ziwei Xu, Sanjay Jain, Mohan Kankanhalli*2024 · 312 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-hallucination-inevitable-innate-limitation-large/)
3. [**Large Language Model based Multi-Agents: A Survey of Progress and Challenges arXiv:2402.01680**Taicheng Guo, Xiuying Chen, Yaqi Wang, et al.*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/guo-2024-large-language-model-based/)
4. **[Graph Retrieval-Augmented Generation: A Survey](https://md.research.elamur.ai/free/en/papers/peng-2024-graph-retrieval-augmented-generation-survey/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Boci Peng, Yun Zhu, Yongchao Liu, et al.*2024 · 276 citations*
5. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
6. **[G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering](https://md.research.elamur.ai/free/en/papers/he-2024-g-retriever-retrieval-augmented-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoxin He, Yijun Tian, Yifei Sun, et al.*2024 · 236 citations*
7. [**AlphaEvolve: A coding agent for scientific and algorithmic discovery arXiv:2506.13131**Alexander Novikov, Ngân Vũ, Marvin Eisenberger, et al.*2025 · 202 citations*](https://md.research.elamur.ai/free/en/papers/novikov-2025-alphaevolve-coding-agent-scientific-algorithmic/)
8. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
9. **[Knowledge Conflicts for LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 182 citations*
10. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
11. **[MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents](https://md.research.elamur.ai/free/en/papers/tang-2024-minicheck-efficient-fact-checking-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Liyan Tang, Philippe Laban, Greg Durrett*2024 · 166 citations*
12. **[Long-form factuality in large language models](https://md.research.elamur.ai/free/en/papers/wei-2024-long-form-factuality-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jerry Wei, Chengrun Yang, Xinying Song, et al.*2024 · 165 citations*
13. **[The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-dawn-after-dark-empirical-study/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyi Li, Jie Chen, Ruiyang Ren, et al.*2024 · 153 citations*
14. **[Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models](https://md.research.elamur.ai/free/en/papers/shao-2024-assisting-writing-wikipedia-like-articles/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yijia Shao, Yucheng Jiang, Theodore Kanell, et al.*2024 · 131 citations*
15. [**Fine-grained Hallucination Detection and Editing for Language Models arXiv:2401.06855**Abhika Mishra, Akari Asai, Vidhisha Balachandran, et al.*2024 · 100 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2024-fine-grained-hallucination-detection-editing/)
16. **[HalluLens: LLM Hallucination Benchmark](https://md.research.elamur.ai/free/en/papers/bang-2025-hallulens-llm-hallucination-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yejin Bang, Ziwei Ji, Alan Schelten, et al.*2025 · 82 citations*
17. **[Factuality of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/wang-2024-factuality-large-language-models-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuxia Wang, Minghan Wang, Muhammad Arslan Manzoor, et al.*2024 · 77 citations*
18. **[VeriScore: Evaluating the factuality of verifiable claims in long-form text generation](https://md.research.elamur.ai/free/en/papers/song-2024-veriscore-evaluating-factuality-verifiable-claims/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yixiao Song, Yekyung Kim, Mohit Iyyer*2024 · 72 citations*
19. **[Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2024-self-alignment-factuality-mitigating-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoying Zhang, Baolin Peng, Ye Tian, et al.*2024 · 69 citations*
20. [**MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark arXiv:2402.04788**Dongping Chen, Ruoxi Chen, Shilin Zhang, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-mllm-judge-assessing-multimodal-llm/)
21. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
22. **[PlanGenLLMs: A Modern Survey of LLM Planning Capabilities](https://md.research.elamur.ai/free/en/papers/wei-2025-plangenllms-modern-survey-llm-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Wei, Zihao Zhang, Shenghua He, et al.*2025 · 55 citations*
23. **[Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System](https://md.research.elamur.ai/free/en/papers/su-2025-many-heads-are-better-than/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoyang Su, Renqi Chen, Shixiang Tang, et al.*2025 · 40 citations*
24. [**Introducing v0.5 of the AI Safety Benchmark from MLCommons arXiv:2404.12241**Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2024-introducing-v0-5-ai-safety/)
25. [**A Survey of Small Language Models arXiv:2410.20011**Chien Van Nguyen, Xuan Shen, Ryan Aponte, et al.*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2024-survey-small-language-models/)
26. **[Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing](https://md.research.elamur.ai/free/en/papers/jiao-2024-learning-planning-based-reasoning-trajectories/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, et al.*2024 · 31 citations*
27. **[Knowledge Boundary of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/li-2025-knowledge-boundary-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Moxin Li, Yong Zhao, Wenxuan Zhang, et al.*2025 · 30 citations*
28. **[Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling](https://md.research.elamur.ai/free/en/papers/wan-2025-reasoning-aware-self-consistency-leveraging/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guangya Wan, Yuqi Wu, Jie Chen, et al.*2025 · 29 citations*
29. **[FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhang-2025-faithfulrag-fact-level-conflict-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qinggang Zhang, Zhishang Xiang, Yilin Xiao, et al.*2025 · 27 citations*
30. [**LLM-as-a-Judge & Reward Model: What They Can and Cannot Do arXiv:2409.11239**Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/son-2024-llm-judge-reward-model-they/)
31. **[Hierarchical Document Refinement for Long-context Retrieval-augmented Generation](https://md.research.elamur.ai/free/en/papers/jin-2025-hierarchical-document-refinement-long-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiajie Jin, Xiaoxi Li, Guanting Dong, et al.*2025 · 25 citations*
32. **[Removal of Hallucination on Hallucination: Debate-Augmented RAG](https://md.research.elamur.ai/free/en/papers/hu-2025-removal-hallucination-hallucination-debate-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wentao Hu, Wengyu Zhang, Yiyang Jiang, et al.*2025 · 25 citations*
33. **[What is the Role of Small Models in the LLM Era: A Survey](https://md.research.elamur.ai/free/en/papers/chen-2024-role-small-models-llm-era/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Lihu Chen, Gael Varoquaux*2024 · 23 citations*
34. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
35. **[LongReward: Improving Long-context Large Language Models with AI Feedback](https://md.research.elamur.ai/free/en/papers/zhang-2025-longreward-improving-long-context-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiajie Zhang, Zhongni Hou, Xin Lv, et al.*2025 · 21 citations*
36. **[SLAM: Towards Efficient Multilingual Reasoning via Selective Language Alignment](https://md.research.elamur.ai/free/en/papers/fan-2025-slam-efficient-multilingual-reasoning-selective/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yuchun Fan, Yongyu Mu, YiLin Wang, et al.*2025 · 20 citations*
37. **[Towards Effective Extraction and Evaluation of Factual Claims](https://md.research.elamur.ai/free/en/papers/metropolitansky-2025-effective-extraction-evaluation-factual-claims/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dasha Metropolitansky, Jonathan Larson*2025 · 20 citations*
38. **[Pandora's Box or Aladdin's Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2025-pandora-s-box-or-aladdin/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinyang Wu, Shuai Zhang, Feihu Che, et al.*2025 · 19 citations*
39. **[RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation](https://md.research.elamur.ai/free/en/papers/li-2025-retrollm-empowering-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoxi Li, Jiajie Jin, Yujia Zhou, et al.*2025 · 19 citations*
40. **[Hallucination Detection in LLMs Using Spectral Features of Attention Maps](https://md.research.elamur.ai/free/en/papers/binkowski-2025-hallucination-detection-llms-spectral-features/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jakub Binkowski, Denis Janiak, Albert Sawczyn, et al.*2025 · 18 citations*
41. [**Comparing Hallucination Detection Metrics for Multilingual Generation arXiv:2402.10496**Haoqiang Kang, Terra Blevins, Luke Zettlemoyer*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/kang-2024-comparing-hallucination-detection-metrics-multilingual/)
42. [**Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs arXiv:2507.09477**Yangning Li, Weizhi Zhang, Yuyao Yang, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-towards-agentic-rag-deep-reasoning/)
43. **[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*
44. **[Can Knowledge Graphs Make Large Language Models More Trustworthy? An Empirical Study Over Open-ended Question Answering](https://md.research.elamur.ai/free/en/papers/sui-2025-can-knowledge-graphs-make-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuan Sui, Yufei He, Zifeng Ding, et al.*2025 · 16 citations*
45. **[FactBench: A Dynamic Benchmark for In-the-Wild Language Model Factuality Evaluation](https://md.research.elamur.ai/free/en/papers/bayat-2025-factbench-dynamic-benchmark-wild-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Farima Fatahi Bayat, Lechen Zhang, Sheza Munir, et al.*2025 · 16 citations*
46. [**Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models arXiv:2411.02382**Guangzhi Xiong, Eric Xie, Amir Hassan Shariatmadari, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2024-improving-scientific-hypothesis-generation-knowledge/)
47. **[What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective](https://md.research.elamur.ai/free/en/papers/li-2025-what-happened-llms-layers-when/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ming Li, Yanhong Li, Tianyi Zhou*2025 · 15 citations*
48. **[Evaluating Large Language Models for Health-related Queries with Presuppositions](https://md.research.elamur.ai/free/en/papers/kaur-2024-evaluating-large-language-models-health/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Navreet Kaur, Monojit Choudhury, Danish Pruthi*2024 · 15 citations*
49. **[ICR Probe: Tracking Hidden State Dynamics for Reliable Hallucination Detection in LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2025-icr-probe-tracking-hidden-state/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenliang Zhang, Xinyu Hu, Huixuan Zhang, et al.*2025 · 14 citations*
50. **[LLMs Know What They Need: Leveraging a Missing Information Guided Framework to Empower Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2025-llms-know-what-they-need/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Keheng Wang, Feiyu Duan, Peiguang Li, et al.*2025 · 14 citations*
51. [**MA-RAG: Multi-Agent Retrieval-Augmented Generation via Collaborative Chain-of-Thought Reasoning arXiv:2505.20096**Thang Nguyen, Peter Chin, Yu-Wing Tai*2025 · 14 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2025-ma-rag-multi-agent-retrieval/)
52. **[Shallow Focus, Deep Fixes: Enhancing Shallow Layers Vision Attention Sinks to Alleviate Hallucination in LVLMs](https://md.research.elamur.ai/free/en/papers/zhang-2025-shallow-focus-deep-fixes-enhancing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaofeng Zhang, Yihao Quan, Chen Shen, et al.*2025 · 14 citations*
53. **[Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging Tasks](https://md.research.elamur.ai/free/en/papers/li-2025-can-we-further-elicit-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingxuan Li, Weiwen Xu, Ruochen Zhao, et al.*2025 · 13 citations*
54. [**Evaluating LLMs' Divergent Thinking Capabilities for Scientific Idea Generation with Minimal Context arXiv:2412.17596**Kai Ruan, Xuan Wang, Jixiang Hong, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-evaluating-llms-divergent-thinking-capabilities/)
55. [**How Much Can RAG Help the Reasoning of LLM? arXiv:2410.02338**Jingyu Liu, Jiaen Lin, Yong Liu*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-much-rag-help-reasoning-llm/)
56. **[A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation](https://md.research.elamur.ai/free/en/papers/hou-2025-probabilistic-framework-llm-hallucination-detection/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bairu Hou, Yang Zhang, Jacob Andreas, et al.*2025 · 12 citations*
57. **[Empowering GraphRAG with Knowledge Filtering and Integration](https://md.research.elamur.ai/free/en/papers/guo-2025-empowering-graphrag-knowledge-filtering-integration/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kai Guo, Harry Shomer, Shenglai Zeng, et al.*2025 · 12 citations*
58. **[Too Consistent to Detect: A Study of Self-Consistent Errors in LLMs](https://md.research.elamur.ai/free/en/papers/tan-2025-too-consistent-detect-study-self/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hexiang Tan, Fei Sun, Sha Liu, et al.*2025 · 12 citations*
59. **[Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data Filtering](https://md.research.elamur.ai/free/en/papers/si-2025-aligning-large-language-models-follow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuzheng Si, Haozhe Zhao, Gang Chen, et al.*2025 · 11 citations*
60. **[Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization](https://md.research.elamur.ai/free/en/papers/huang-2025-improving-contextual-faithfulness-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Huang, Xiaocheng Feng, Weitao Ma, et al.*2025 · 11 citations*
61. **[SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence](https://md.research.elamur.ai/free/en/papers/liu-2025-selfelicit-your-language-model-secretly/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhining Liu, Rana Ali Amjad, Ravinarayana Adkathimar, et al.*2025 · 11 citations*
62. [**EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language Models arXiv:2402.11430**Jun Gao, Huan Zhao, Wei Wang, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-eventrl-enhancing-event-extraction-outcome/)
63. **[Knowing When to Abstain: Medical LLMs Under Clinical Uncertainty](https://md.research.elamur.ai/free/en/papers/machcha-2026-knowing-when-abstain-medical-llms/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sravanthi Machcha, Sushrita Yerra, Sahil Gupta, et al.*2026 · 9 citations*
64. **[AraHalluEval: A Fine-grained Hallucination Evaluation Framework for Arabic LLMs](https://md.research.elamur.ai/free/en/papers/alansari-2025-arahallueval-fine-grained-hallucination-evaluation/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Aisha Alansari, Hamzah Luqman*2025 · 9 citations*
65. **[BELLE: A Bi-Level Multi-Agent Reasoning Framework for Multi-Hop Question Answering](https://md.research.elamur.ai/free/en/papers/zhang-2025-belle-bi-level-multi-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taolin Zhang, Dongyang Li, Qizhou Chen, et al.*2025 · 9 citations*
66. **[Position: LLMs Can be Good Tutors in English Education](https://md.research.elamur.ai/free/en/papers/ye-2025-position-llms-can-be-good/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jingheng Ye, Shen Wang, Deqing Zou, et al.*2025 · 9 citations*
67. [**You Don't Need Pre-built Graphs for RAG: Retrieval Augmented Generation with Adaptive Reasoning Structures arXiv:2508.06105**Shengyuan Chen, Chuang Zhou, Zheng Yuan, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-don-t-need-pre-built/)
68. **[Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/hu-2025-context-reasoner-incentivizing-reasoning-capability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenbin Hu, Haoran Li, Huihao Jing, et al.*2025 · 7 citations*
69. **[NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2025-nover-incentive-training-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wei Liu, Siya Qi, Xinyu Wang, et al.*2025 · 7 citations*
70. [**Shared Imagination: LLMs Hallucinate Alike arXiv:2407.16604**Yilun Zhou, Caiming Xiong, Silvio Savarese, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-shared-imagination-llms-hallucinate-alike/)
71. **[Analyzing Dialectical Biases in LLMs for Knowledge and Reasoning Benchmarks](https://md.research.elamur.ai/free/en/papers/pan-2025-analyzing-dialectical-biases-llms-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Eileen Pan, Anna Seo Gyeong Choi, Maartje Ter Hoeve, et al.*2025 · 6 citations*
72. [**Comparing human and LLM politeness strategies in free production**Haoran Zhao, Robert D. Hawkins*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-comparing-human-llm-politeness-strategies/)
73. **[Insight Over Sight: Exploring the Vision-Knowledge Conflicts in Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-insight-over-sight-exploring-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyuan Liu, Wenxuan Wang, Youliang Yuan, et al.*2025 · 6 citations*
74. **[MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-metafaith-faithful-natural-language-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.*2025 · 6 citations*
75. **[Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results](https://md.research.elamur.ai/free/en/papers/santilli-2025-revisiting-uncertainty-quantification-evaluation-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Andrea Santilli, Adam Golinski, Michael Kirchhof, et al.*2025 · 6 citations*
76. **[MAVEN-FACT: A Large-scale Event Factuality Detection Dataset](https://md.research.elamur.ai/free/en/papers/li-2024-maven-fact-large-scale-event/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chunyang Li, Hao Peng, Xiaozhi Wang, et al.*2024 · 6 citations*
77. **[Can LLMs Automate Fact-Checking Article Writing?](https://md.research.elamur.ai/free/en/papers/sahnan-2026-can-llms-automate-fact-checking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Dhruv Sahnan, David Corney, Irene Larraz, et al.*2026 · 5 citations*
78. **[KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality](https://md.research.elamur.ai/free/en/papers/ren-2026-knowrl-exploring-knowledgeable-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Baochang Ren, Shuofei Qiao, Ningyu Zhang, et al.*2026 · 5 citations*
79. **[Reducing Hallucinations in Language Model-based SPARQL Query Generation Using Post-Generation Memory Retrieval](https://md.research.elamur.ai/free/en/papers/sharma-2026-reducing-hallucinations-language-model-based/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Aditya Sharma, Christopher Pal, Amal Zouaq*2026 · 5 citations*
80. **[AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction](https://md.research.elamur.ai/free/en/papers/tsang-2026-autograph-r1-end-end-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hong Ting Tsang, Jiaxin Bai, Haoyu Huang, et al.*2026 · 4 citations*
81. **[LLM Agents in Law: Taxonomy, Applications, and Challenges](https://md.research.elamur.ai/free/en/papers/liu-2026-llm-agents-law-taxonomy-applications/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuang Liu, Ruijia Zhang, Ruoyun Ma, et al.*2026 · 4 citations*
82. **[Spotlight Your Instructions: Instruction-following with Dynamic Attention Steering](https://md.research.elamur.ai/free/en/papers/venkateswaran-2026-spotlight-your-instructions-instruction-following/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Praveen Venkateswaran, Danish Contractor*2026 · 4 citations*
83. **[UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities](https://md.research.elamur.ai/free/en/papers/yeo-2026-universalrag-retrieval-augmented-generation-over/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Woongyeong Yeo, Kangsan Kim, Soyeong Jeong, et al.*2026 · 4 citations*
84. [**Read Your Own Mind: Reasoning Helps Surface Self-Confidence Signals in LLMs arXiv:2505.23845 · UncertaiNLP Workshop at Empirical Methods in Natural Language Processing 2025 (EMNLP 2025)**Jakub Podolak, Rajeev Verma*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/podolak-2025-read-own-mind-reasoning-helps/)
85. **[WikiQA-IS: Assisted Benchmark Generation and Automated Evaluation of Icelandic Cultural Knowledge in LLMs](https://md.research.elamur.ai/free/en/papers/arnardottir-2025-wikiqa-is-assisted-benchmark-generation/) [Workshop on the Role of Resources in the Age of Large Language Models](https://md.research.elamur.ai/free/en/venues/resourceful/)**Þórunn Arnardóttir, Elías Bjartur Einarsson, Garðar Ingvarsson Juto, et al.*2025 · 4 citations*
86. [**HalluScore: Large Language Model Hallucination Question Answering Benchmark arXiv:2605.17007**Aisha Alansari, Hamzah Luqman*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/alansari-2026-halluscore-large-language-model-hallucination/)
87. [**HalluTruthQA: A Fine-Grained Benchmark for Hallucination Detection, Localization, and Explanation in Arabic Question Answering arXiv:2607.20219**Abdessalam Bouchekif; Mohammed-En-Nadhir Zighem; Salah Eddine Bekhouche; Hichem Telli; Somaya Eltanbouly; Shahd Gaben; Heba Sbahi; Samer Rashwani; Mutaz Al-Khatib; Emad Mohamed; Mohammed Ghaly;, Abdenour Hadid*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/bouchekif-2026-hallutruthqa-fine-grained-benchmark-hallucination/)
88. **[Stress Testing Factual Consistency Metrics for Long-Document Summarization](https://md.research.elamur.ai/free/en/papers/mujahid-2026-stress-testing-factual-consistency-metrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zain Muhammad Mujahid, Dustin Wright, Isabelle Augenstein*2026 · 3 citations*
89. **[TCE at IslamicEval 2025: Retrieval-Augmented LLMs for Quranic and Hadith Content Identification and Verification](https://md.research.elamur.ai/free/en/papers/elkoumy-2025-tce-islamiceval-2025-retrieval-augmented/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Mohammed ElKoumy, Khalid Allam, Ahmad Tamer, et al.*2025 · 3 citations*
90. **[CCD: Mitigating Hallucinations in Radiology MLLMs via Clinical Contrastive Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-ccd-mitigating-hallucinations-radiology-mllms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xi Zhang, Zaiqiao Meng, Jake Lever, et al.*2026 · 2 citations*
91. **[Comparing Human and Large Language Model Interpretation of Implicit Information](https://md.research.elamur.ai/free/en/papers/santis-2026-comparing-human-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Antonio De Santis, Tommaso Bonetti, Andrea Tocchetti, et al.*2026 · 2 citations*
92. **[Do Images Speak Louder than Words? Investigating the Effect of Textual Misinformation in VLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-do-images-speak-louder-than/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chi Zhang, Wenxuan Ding, Jiale Liu, et al.*2026 · 2 citations*
93. **[Mechanisms of Prompt-Induced Hallucination in Vision–Language Models](https://md.research.elamur.ai/free/en/papers/rudman-2026-mechanisms-prompt-induced-hallucination-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**William Rudman, Michal Golovanevsky, Dana Arad, et al.*2026 · 2 citations*
94. **[RefusalBench: Generative Evaluation of Selective Refusal in Grounded Language Models](https://md.research.elamur.ai/free/en/papers/muhamed-2026-refusalbench-generative-evaluation-selective-refusal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Aashiq Muhamed, Leonardo F. R. Ribeiro, Markus Dreyer, et al.*2026 · 2 citations*
95. **[The Unintended Trade-off of AI Alignment: Balancing Hallucination Mitigation and Safety in LLMs](https://md.research.elamur.ai/free/en/papers/mahmoud-2026-unintended-trade-off-ai-alignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Omar Mahmoud, Ali Khalil, Thommen George Karimpanal, et al.*2026 · 2 citations*
96. **[Adapting Falcon3-7B Language Model for Arabic: Methods, Challenges, and Outcomes](https://md.research.elamur.ai/free/en/papers/boussaha-2025-adapting-falcon3-7b-language-model/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Basma El Amel Boussaha, Mohammed Alyafeai, Ahmed Alzubaidi, et al.*2025 · 2 citations*
97. **[A Review of Incorporating Psychological Theories in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2026-review-incorporating-psychological-theories-llms/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zizhou Liu, Ziwei Gong, Lin Ai, et al.*2026 · 1 citation*
98. **[ART: Adaptive Reasoning Trees for Explainable Claim Verification](https://md.research.elamur.ai/free/en/papers/wadhwa-2026-art-adaptive-reasoning-trees-explainable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sahil Wadhwa, Himanshu Kumar, Guanqun Yang, et al.*2026 · 1 citation*
99. **[Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/schreieder-2026-attribution-citation-quotation-survey-evidence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tobias Schreieder, Tim Schopf, Michael Färber*2026 · 1 citation*
100. **[Automated Creativity Evaluation of Language Models Across Open-Ended Tasks](https://md.research.elamur.ai/free/en/papers/sen-2026-automated-creativity-evaluation-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tan Min Sen, Zachary Choy Kit Chun, Syed Ali Redha Alsagoff, et al.*2026 · 1 citation*

**1** [2](https://md.research.elamur.ai/free/en/authors/haotian-wang/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/haotian-wang/cited-by/page/2/)

- [← back to](https://md.research.elamur.ai/free/en/authors/haotian-wang/) — Haotian Wang