---
title: "Who cites Haikang Deng — 305 papers of our library"
description: "305 papers of the Elamur Research library cite the works of Haikang Deng, found in their bibliographies; the most cited first."
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---
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# Who cites Haikang Deng

305 citations of their works from 305 papers of our library (of the 149,439 whose bibliographies we read) · 77 with a page here, the most cited first · [← Haikang Deng](https://md.research.elamur.ai/free/en/authors/haikang-deng/)

1. **[Survey of Hallucination in Natural Language Generation](https://md.research.elamur.ai/free/en/papers/ji-2022-survey-hallucination-natural-language-generation/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Ziwei Ji, Nayeon Lee, Rita Frieske, et al.*2022 · 5,974 citations*
2. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
3. **[Lost in the Middle: How Language Models Use Long Contexts](https://md.research.elamur.ai/free/en/papers/liu-2023-lost-middle-language-models-use/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nelson F. Liu, Kevin Lin, John Hewitt, et al.*2023 · 2,584 citations*
4. [**Retrieval-Augmented Generation for Large Language Models: A Survey arXiv:2312.10997**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,663 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/)
5. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
6. **[FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation](https://md.research.elamur.ai/free/en/papers/min-2023-factscore-fine-grained-atomic-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.*2023 · 987 citations*
7. **[Explainability for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhao-2023-explainability-large-language-models-survey/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Haiyan Zhao, Hanjie Chen, Fan Yang, et al.*2023 · 790 citations*
8. [**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/)
9. **[The Power of Noise: Redefining Retrieval for RAG Systems](https://md.research.elamur.ai/free/en/papers/cuconasu-2024-power-noise-redefining-retrieval-rag/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Florin Cuconasu, Giovanni Trappolini, Federico Siciliano, et al.*2024 · 312 citations*
10. [**Retrieval-Augmented Generation for AI-Generated Content: A Survey arXiv:2402.19473**Penghao Zhao, Hailin Zhang, Qinhan Yu, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-retrieval-augmented-generation-ai-generated/)
11. [**Ragas: Automated Evaluation of Retrieval Augmented Generation arXiv:2309.15217**Shahul Es, Jithin James, Luis Espinosa-Anke, et al.*2023 · 283 citations*](https://md.research.elamur.ai/free/en/papers/es-2023-ragas-automated-evaluation-retrieval-augmented/)
12. [**Demystifying Prompts in Language Models via Perplexity Estimation arXiv:2212.04037**Hila Gonen, Srini Iyer, Terra Blevins, et al.*2022 · 213 citations*](https://md.research.elamur.ai/free/en/papers/gonen-2022-demystifying-prompts-language-models-perplexity/)
13. **[Sources of Hallucination by Large Language Models on Inference Tasks](https://md.research.elamur.ai/free/en/papers/mckenna-2023-sources-hallucination-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nick McKenna, Tianyi Li, Liang Cheng, et al.*2023 · 212 citations*
14. **[Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs](https://md.research.elamur.ai/free/en/papers/ovadia-2024-fine-tuning-or-retrieval-comparing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Oded Ovadia, Menachem Brief, Moshik Mishaeli, et al.*2024 · 206 citations*
15. [**RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval arXiv:2401.18059**Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.*2024 · 193 citations*](https://md.research.elamur.ai/free/en/papers/sarthi-2024-raptor-recursive-abstractive-processing-tree/)
16. **[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*
17. [**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/)
18. **[Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4](https://md.research.elamur.ai/free/en/papers/chang-2023-speak-memory-archaeology-books-known/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kent K. Chang, Mackenzie Cramer, Sandeep Soni, et al.*2023 · 169 citations*
19. **[Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/yu-2024-chain-note-enhancing-robustness-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenhao Yu, Hongming Zhang, Xiaoman Pan, et al.*2024 · 149 citations*
20. **[Language Model Behavior: A Comprehensive Survey](https://md.research.elamur.ai/free/en/papers/chang-2024-language-model-behavior-comprehensive-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Tyler A. Chang, Benjamin K. Bergen*2024 · 148 citations*
21. **[Retrieval-based Language Models and Applications](https://md.research.elamur.ai/free/en/papers/asai-2023-retrieval-based-language-models-applications/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Akari Asai, Sewon Min, Zexuan Zhong, et al.*2023 · 141 citations*
22. **[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*
23. **[Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?](https://md.research.elamur.ai/free/en/papers/chen-2023-can-pre-trained-vision-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yang Chen, Hexiang Hu, Yi Luan, et al.*2023 · 111 citations*
24. **[R-Tuning: Instructing Large Language Models to Say ‘I Don't Know'](https://md.research.elamur.ai/free/en/papers/zhang-2024-r-tuning-instructing-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hanning Zhang, Shizhe Diao, Yong Lin, et al.*2024 · 99 citations*
25. [**Rethinking Interpretability in the Era of Large Language Models arXiv:2402.01761**Chandan Singh, Jeevana Priya Inala, Michel Galley, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-rethinking-interpretability-era-large-language/)
26. [**Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models arXiv:2401.06102**Asma Ghandeharioun, Avi Caciularu, Adam Pearce, et al.*2024 · 84 citations*](https://md.research.elamur.ai/free/en/papers/ghandeharioun-2024-patchscopes-unifying-framework-inspecting-hidden/)
27. **[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*
28. [**Tuning Language Models by Proxy arXiv:2401.08565**Alisa Liu, Xiaochuang Han, Yizhong Wang, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-tuning-language-models-proxy/)
29. **[Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps](https://md.research.elamur.ai/free/en/papers/chuang-2024-lookback-lens-detecting-mitigating-contextual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yung-Sung Chuang, Linlu Qiu, Cheng-Yu Hsieh, et al.*2024 · 78 citations*
30. **[TTRL: Test-Time Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zuo-2025-ttrl-test-time-reinforcement-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxin Zuo, Kaiyan Zhang, Li Sheng, et al.*2025 · 76 citations*
31. **[Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training](https://md.research.elamur.ai/free/en/papers/fang-2024-enhancing-noise-robustness-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feiteng Fang, Yuelin Bai, Shiwen Ni, et al.*2024 · 75 citations*
32. **[Tug-of-War between Knowledge: Exploring and Resolving Knowledge Conflicts in Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/jin-2024-tug-war-between-knowledge-exploring/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zhuoran Jin, Pengfei Cao, Yubo Chen, et al.*2024 · 70 citations*
33. [**Improving Language Models via Plug-and-Play Retrieval Feedback arXiv:2305.14002**Wenhao Yu, Zhihan Zhang, Zhenwen Liang, et al.*2023 · 54 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-improving-language-models-plug-play/)
34. [**LLM Internal States Reveal Hallucination Risk Faced With a Query arXiv:2407.03282**Ziwei Ji, Delong Chen, Etsuko Ishii, et al.*2024 · 52 citations*](https://md.research.elamur.ai/free/en/papers/ji-2024-llm-internal-states-reveal-hallucination/)
35. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/)
36. **[Unfamiliar Finetuning Examples Control How Language Models Hallucinate](https://md.research.elamur.ai/free/en/papers/kang-2025-unfamiliar-finetuning-examples-control-how/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Katie Kang, Eric Wallace, Claire Tomlin, et al.*2025 · 47 citations*
37. [**ARGS: Alignment as Reward-Guided Search arXiv:2402.01694**Maxim Khanov, Jirayu Burapacheep, Yixuan Li*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/khanov-2024-args-alignment-reward-guided-search/)
38. **[“According to . . . “: Prompting Language Models Improves Quoting from Pre-Training Data](https://md.research.elamur.ai/free/en/papers/weller-2024-according-prompting-language-models-improves/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Orion Weller, Marc Marone, Nathaniel Weir, et al.*2024 · 46 citations*
39. [**The MiniPile Challenge for Data-Efficient Language Models arXiv:2304.08442**Jean Kaddour*2023 · 41 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-minipile-challenge-data-efficient-language/)
40. **[Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?](https://md.research.elamur.ai/free/en/papers/yona-2024-can-large-language-models-faithfully/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gal Yona, Roee Aharoni, Mor Geva*2024 · 40 citations*
41. **[InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery](https://md.research.elamur.ai/free/en/papers/cao-2025-instructmol-multi-modal-integration-building/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**He Cao, Zijing Liu, Xingyu Lu, et al.*2025 · 38 citations*
42. **[Blinded by Generated Contexts: How Language Models Merge Generated and Retrieved Contexts When Knowledge Conflicts?](https://md.research.elamur.ai/free/en/papers/tan-2024-blinded-generated-contexts-how-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hexiang Tan, Fei Sun, Wanli Yang, et al.*2024 · 37 citations*
43. **[DeAL: Decoding-time Alignment for Large Language Models](https://md.research.elamur.ai/free/en/papers/huang-2025-deal-decoding-time-alignment-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**James Y. Huang, Sailik Sengupta, Daniele Bonadiman, et al.*2025 · 36 citations*
44. [**An Emulator for Fine-Tuning Large Language Models using Small Language Models arXiv:2310.12962**Eric Mitchell, Rafael Rafailov, Archit Sharma, et al.*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/mitchell-2023-emulator-fine-tuning-large-language/)
45. [**Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models arXiv:2305.09955**Shangbin Feng, Weijia Shi, Yuyang Bai, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/feng-2023-knowledge-card-filling-llms-knowledge/)
46. **[Benchmarking Linguistic Diversity of Large Language Models](https://md.research.elamur.ai/free/en/papers/guo-2025-benchmarking-linguistic-diversity-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yanzhu Guo, Guokan Shang, Chloé Clavel*2025 · 32 citations*
47. **[LangBridge: Multilingual Reasoning Without Multilingual Supervision](https://md.research.elamur.ai/free/en/papers/yoon-2024-langbridge-multilingual-reasoning-without-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dongkeun Yoon, Joel Jang, Sungdong Kim, et al.*2024 · 29 citations*
48. **[TC–RAG: Turing–Complete RAG's Case study on Medical LLM Systems](https://md.research.elamur.ai/free/en/papers/jiang-2025-tc-rag-turing-complete-rag/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinke Jiang, Yue Fang, Rihong Qiu, et al.*2025 · 25 citations*
49. **[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*
50. **[Multilingual Retrieval-Augmented Generation for Knowledge-Intensive Task](https://md.research.elamur.ai/free/en/papers/ranaldi-2025-multilingual-retrieval-augmented-generation-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Leonardo Ranaldi, Barry Haddow, Alexandra Birch*2025 · 18 citations*
51. **[Crossing the Threshold: Idiomatic Machine Translation through Retrieval Augmentation and Loss Weighting](https://md.research.elamur.ai/free/en/papers/liu-2023-crossing-threshold-idiomatic-machine-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Emmy Liu, Aditi Chaudhary, Graham Neubig*2023 · 17 citations*
52. **[MMSearch-R1: Incentivizing LMMs to Search](https://md.research.elamur.ai/free/en/papers/wu-2026-mmsearch-r1-incentivizing-lmms-search/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinming Wu, Zihao Deng, Wei Li, et al.*2026 · 16 citations*
53. **[On The Origin of Cultural Biases in Language Models: From Pre-training Data to Linguistic Phenomena](https://md.research.elamur.ai/free/en/papers/naous-2025-origin-cultural-biases-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tarek Naous, Wei Xu*2025 · 15 citations*
54. **[AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters](https://md.research.elamur.ai/free/en/papers/lucy-2024-aboutme-self-descriptions-webpages-document/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Li Lucy, Suchin Gururangan, Luca Soldaini, et al.*2024 · 15 citations*
55. [**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/)
56. [**Distilling LLM Agent into Small Models with Retrieval and Code Tools arXiv:2505.17612**Minki Kang, Jongwon Jeong, Seanie Lee, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/kang-2025-distilling-llm-agent-small-models/)
57. **[Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning](https://md.research.elamur.ai/free/en/papers/li-2026-retrieval-as-generation-unified-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bo Li, Mingda Wang, Gexiang Fang, et al.*2026 · 8 citations*
58. **[Nudging: Inference-time Alignment of LLMs via Guided Decoding](https://md.research.elamur.ai/free/en/papers/fei-2025-nudging-inference-time-alignment-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Fei, Yasaman Razeghi, Sameer Singh*2025 · 8 citations*
59. **[QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/min-2026-quco-rag-quantifying-uncertainty-pre/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dehai Min, Kailin Zhang, Tongtong Wu, et al.*2026 · 2 citations*
60. [**The Hrunting of AI: Where and How to Improve English Dialectal Fairness arXiv:2603.15187**Wei Li, Adrian de Wynter*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/li-2026-hrunting-ai-where-improve-english/)
61. **[Common to Whom? Regional Cultural Commonsense and LLM Bias in India](https://md.research.elamur.ai/free/en/papers/madhusudan-2026-common-whom-regional-cultural-commonsense/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sangmitra Madhusudan, Trush Shashank More, Steph Buongiorno, et al.*2026*
62. [**DialectLLM: A Dialect-Aware Dialogue Generation Framework Beyond Standard American English arXiv:2601.22888**Jio Oh, Paul Vicinanza, Thomas Butler, et al.*2026*](https://md.research.elamur.ai/free/en/papers/oh-2026-dialectllm-dialect-aware-dialog-ue/)
63. **[Do Factual Recall Mechanisms Carry over from Text to Speech in Multimodal Language Models?](https://md.research.elamur.ai/free/en/papers/modica-2026-do-factual-recall-mechanisms-carry/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Luca Modica, Filip Landin, Mehrdad Farahani, et al.*2026*
64. **[How to Train a Real-World Silicon Concierge? Internalizing Complex Business Workflow to Only OneModel](https://md.research.elamur.ai/free/en/papers/tong-2026-how-train-real-world-silicon/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongqi Tong, Xiaoyun Feng, Lyuxin Xue, et al.*2026*
65. **[LCR-RAG: Enhancing Logical Consistency in Retrieval-Augmented Generation via Neuro-symbolic Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zheng-2026-lcr-rag-enhancing-logical-consistency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenxiang Zheng, Guo Tang, Shixin Jiang, et al.*2026*
66. **[LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points](https://md.research.elamur.ai/free/en/papers/zhang-2026-linkqa-synthesizing-diverse-qa-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuemiao Zhang, Can Ren, Chengying Tu, et al.*2026*
67. [**LLMs Silently Correct African American English: Auditing and Mitigating Dialect Bias via Activation Steering arXiv:2607.06845**Huan Wu, Ali Emami, Muhammad Furquan Hassan, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wu-2026-llms-silently-correct-african-american/)
68. **[LongTailQA: Benchmarking LLMs and RAG Models on Disambiguated Long-Tail Entities](https://md.research.elamur.ai/free/en/papers/xion-2026-longtailqa-benchmarking-llms-rag-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**William Xion, Uwe Hadler, Tim Cofala, et al.*2026*
69. **[MCLE-Mol: Empowering LLM with Molecular Comprehension and Low-Cost Continual Evolution for Interpretable Property Prediction](https://md.research.elamur.ai/free/en/papers/pu-2026-mcle-mol-empowering-llm-molecular/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhili Pu, Lantian Zhang, Hao Duan, et al.*2026*
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77. [**An Empirical Study of Chinese Entity Linking Based on Large Language Model (基于大语言模型的中文实体链接实证研究) Acta Automatica Sinica (自动化学报)**Zhengfei Xu (徐正斐), Xin Xin (辛欣)*2025*](https://md.research.elamur.ai/free/en/papers/xu-2025-empirical-study-chinese/)

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