---
title: "Who cites Hai-Tao Zheng — 583 papers of our library"
description: "583 papers of the Elamur Research library cite the works of Hai-Tao Zheng, found in their bibliographies; the most cited first."
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---
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# Who cites Hai-Tao Zheng

605 citations of their works from 583 papers of our library (of the 149,439 whose bibliographies we read) · 85 with a page here, the most cited first · [← Hai-Tao Zheng](https://md.research.elamur.ai/free/en/authors/hai-tao-zheng/)

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 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*
3. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
4. **[Instruction Tuning for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 520 citations*
5. **[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*
6. [**Enhancing Chat Language Models by Scaling High-quality Instructional Conversations arXiv:2305.14233**Ning Ding, Yulin Chen, Bokai Xu, et al.*2023 · 402 citations*](https://md.research.elamur.ai/free/en/papers/ding-2023-enhancing-chat-language-models-scaling/)
7. **[Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification](https://md.research.elamur.ai/free/en/papers/hu-2022-knowledgeable-prompt-tuning-incorporating-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shengding Hu, Ning Ding, Huadong Wang, et al.*2022 · 362 citations*
8. **[Few-NERD: A Few-shot Named Entity Recognition Dataset](https://md.research.elamur.ai/free/en/papers/ding-2021-few-nerd-few-shot-named/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ning Ding, Guangwei Xu, Yulin Chen, et al.*2021 · 336 citations*
9. [**ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2107.02137**Yu Sun, Shuohuan Wang, Shikun Feng, et al.*2021 · 332 citations*](https://md.research.elamur.ai/free/en/papers/sun-2021-ernie-3-0-large/)
10. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 320 citations*
11. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
12. **[OpenPrompt: An Open-source Framework for Prompt-learning](https://md.research.elamur.ai/free/en/papers/ding-2022-openprompt-open-source-framework-prompt/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ning Ding, Shengding Hu, Weilin Zhao, et al.*2022 · 279 citations*
13. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone arXiv:2408.01800**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
14. **[MAVEN: A Massive General Domain Event Detection Dataset](https://md.research.elamur.ai/free/en/papers/wang-2020-maven-massive-general-domain-event/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaozhi Wang, Ziqi Wang, Xu Han, et al.*2020 · 261 citations*
15. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
16. [**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/)
17. **[CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning](https://md.research.elamur.ai/free/en/papers/das-2022-container-few-shot-named-entity/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sarkar Snigdha Sarathi Das, Arzoo Katiyar, Rebecca Passonneau, et al.*2022 · 234 citations*
18. [**Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch arXiv:2311.03099**Le Yu, Bowen Yu, Haiyang Yu, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-language-models-super-mario-absorbing/)
19. **[Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yubo Ma, Yixin Cao, Yong Hong, et al.*2023 · 212 citations*
20. **[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*
21. **[Template-free Prompt Tuning for Few-shot NER](https://md.research.elamur.ai/free/en/papers/ma-2022-template-free-prompt-tuning-few/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ruotian Ma, Xin Zhou, Tao Gui, et al.*2022 · 182 citations*
22. **[Prompt-learning for Fine-grained Entity Typing](https://md.research.elamur.ai/free/en/papers/ding-2022-prompt-learning-fine-grained-entity/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ning Ding, Yulin Chen, Xu Han, et al.*2022 · 181 citations*
23. [**Is GPT-3 a Good Data Annotator? arXiv:2212.10450**Bosheng Ding, Chengwei Qin, Linlin Liu, et al.*2022 · 147 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-gpt-3-good-data-annotator/)
24. [**Long-context LLMs Struggle with Long In-context Learning arXiv:2404.02060**Tianle Li, Ge Zhang, Quy Duc Do, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-long-context-llms-struggle-long/)
25. [**LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks arXiv:2412.15204**Yushi Bai, Shangqing Tu, Jiajie Zhang, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longbench-v2-deeper-understanding/)
26. [**FireAct: Toward Language Agent Fine-tuning arXiv:2310.05915**Baian Chen, Chang Shu, Ehsan Shareghi, et al.*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-fireact-toward-language-agent-fine/)
27. [**PromptNER: Prompting For Named Entity Recognition arXiv:2305.15444**Dhananjay Ashok, Zachary C. Lipton*2023 · 86 citations*](https://md.research.elamur.ai/free/en/papers/ashok-2023-promptner-prompting-named-entity-recognition/)
28. [**ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2112.12731**Shuohuan Wang, Yu Sun, Yang Xiang, et al.*2021 · 63 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-ernie-3-0-titan/)
29. [**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/)
30. **[mDPO: Conditional Preference Optimization for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-mdpo-conditional-preference-optimization-multimodal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fei Wang, Wenxuan Zhou, James Y. Huang, et al.*2024 · 50 citations*
31. **[DiscoPrompt: Path Prediction Prompt Tuning for Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/chan-2023-discoprompt-path-prediction-prompt-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chunkit Chan, Xin Liu, Jiayang Cheng, et al.*2023 · 45 citations*
32. [**Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages arXiv:2308.12038**Jinyi Hu, Yuan Yao, Chongyi Wang, et al.*2023 · 43 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-large-multilingual-models-pivot-zero/)
33. **[Facilitating Contrastive Learning of Discourse Relational Senses by Exploiting the Hierarchy of Sense Relations](https://md.research.elamur.ai/free/en/papers/long-2022-facilitating-contrastive-learning-discourse-relational/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wanqiu Long, Bonnie Webber*2022 · 43 citations*
34. [**When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks arXiv:2311.08993**Hao Peng, Xiaozhi Wang, Jianhui Chen, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-context-learning-fall-short-why/)
35. [**InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output arXiv:2407.03320**Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-internlm-xcomposer-2-5/)
36. **[Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench](https://md.research.elamur.ai/free/en/papers/liu-2025-protecting-privacy-multimodal-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zheyuan Liu, Guangyao Dou, Mengzhao Jia, et al.*2025 · 24 citations*
37. **[Cracking the Code of Hallucination in LVLMs with Vision-aware Head Divergence](https://md.research.elamur.ai/free/en/papers/he-2025-cracking-code-hallucination-lvlms-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinghan He, Kuan Zhu, Haiyun Guo, et al.*2025 · 21 citations*
38. [**Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models arXiv:2401.00788**Terry Yue Zhuo, Armel Zebaze, Nitchakarn Suppattarachai, et al.*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-astraios-parameter-efficient-instruction-tuning/)
39. [**Prompting and Fine-Tuning Open-Sourced Large Language Models for Stance Classification arXiv:2309.13734**Iain J. Cruickshank, Lynnette Hui Xian Ng*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/cruickshank-2023-prompting-fine-tuning-open-sourced/)
40. **[EXCGEC: A Benchmark for Edit-Wise Explainable Chinese Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/ye-2024-excgec-benchmark-edit-wise-explainable/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Jingheng Ye, Shang Qin, Yinghui Li, et al.*2024 · 15 citations*
41. [**Evaluating the Capability of Large-scale Language Models on Chinese Grammatical Error Correction Task arXiv:2307.03972**Fanyi Qu, Chenming Tang, Yunfang Wu*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/qu-2023-evaluating-capability-large-scale-language/)
42. **[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*
43. [**ConPET: Continual Parameter-Efficient Tuning for Large Language Models arXiv:2309.14763**Chenyang Song, Xu Han, Zheni Zeng, et al.*2023 · 14 citations*](https://md.research.elamur.ai/free/en/papers/song-2023-conpet-continual-parameter-efficient-tuning/)
44. **[Activation Steering Decoding: Mitigating Hallucination in Large Vision-Language Models through Bidirectional Hidden State Intervention](https://md.research.elamur.ai/free/en/papers/su-2025-activation-steering-decoding-mitigating-hallucination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingran Su, Jingfan Chen, Hongxin Li, et al.*2025 · 12 citations*
45. **[Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-modality-aware-neuron-pruning-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheyuan Liu, Guangyao Dou, Xiangchi Yuan, et al.*2025 · 12 citations*
46. [**CLEVA: Chinese Language Models EVAluation Platform arXiv:2308.04813**Yanyang Li, Jianqiao Zhao, Duo Zheng, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-cleva-chinese-language-models/)
47. **[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*
48. **[Prompt-based Logical Semantics Enhancement for Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/wang-2023-prompt-based-logical-semantics-enhancement/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chenxu Wang, Ping Jian, Mu Huang*2023 · 8 citations*
49. **[Dialect & Sentiment Identification in Nuanced Arabic Tweets Using an Ensemble of Prompt-based, Fine-tuned, and Multitask BERT-Based Models](https://md.research.elamur.ai/free/en/papers/salam-2022-dialect-sentiment-identification-nuanced-arabic/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Reem Abdel-Salam*2022 · 8 citations*
50. **[Multilingual coreference resolution as text generation](https://md.research.elamur.ai/free/en/papers/skachkova-2024-multilingual-coreference-resolution-as-text/) [Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC)](https://md.research.elamur.ai/free/en/venues/crac/)**Natalia Skachkova*2024 · 6 citations*
51. **[Revealing and Enhancing Core Visual Regions: Harnessing Internal Attention Dynamics for Hallucination Mitigation in LVLMs](https://md.research.elamur.ai/free/en/papers/lyu-2026-revealing-enhancing-core-visual-regions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangtao Lyu, Qi Liu, Chenghao Xu, et al.*2026 · 5 citations*
52. **[RRHF-V: Ranking Responses to Mitigate Hallucinations in Multimodal Large Language Models with Human Feedback](https://md.research.elamur.ai/free/en/papers/chen-2025-rrhf-v-ranking-responses-mitigate/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Guoqing Chen, Fu Zhang, Jinghao Lin, et al.*2025 · 5 citations*
53. **[Don't Trust Generative Agents to Mimic Communication on Social Networks Unless You Benchmarked their Empirical Realism](https://md.research.elamur.ai/free/en/papers/munker-2026-don-t-trust-generative-agents/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Simon Münker, Nils Schwager, Achim Rettinger*2026 · 4 citations*
54. **[Improving Classroom Dialogue Act Recognition from Limited Labeled Data with Self-Supervised Contrastive Learning Classifiers](https://md.research.elamur.ai/free/en/papers/kumaran-2023-improving-classroom-dialogue-act-recognition/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Vikram Kumaran, Jonathan Rowe, Bradford Mott, et al.*2023 · 3 citations*
55. **[rematchka at ArAIEval Shared Task: Prefix-Tuning & Prompt-tuning for Improved Detection of Propaganda and Disinformation in Arabic Social Media Content](https://md.research.elamur.ai/free/en/papers/salam-2023-rematchka-araieval-shared-task-prefix/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Reem Abdel-Salam*2023 · 3 citations*
56. **[promptolution: A Unified, Modular Framework for Prompt Optimization](https://md.research.elamur.ai/free/en/papers/zehle-2026-promptolution-unified-modular-framework-prompt/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tom Zehle, Timo Heiß, Moritz Schlager, et al.*2026 · 2 citations*
57. **[Prune as You Generate: Online Rollout Pruning for Faster and Better RLVR](https://md.research.elamur.ai/free/en/papers/xu-2026-prune-as-you-generate-online/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haobo Xu, Sirui Chen, Ruizhong Qiu, et al.*2026 · 2 citations*
58. **[Act2P: LLM-Driven Online Dialogue Act Classification for Power Analysis](https://md.research.elamur.ai/free/en/papers/zhang-2025-act2p-llm-driven-online-dialogue/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenbo Zhang, Yuhan Wang*2025 · 2 citations*
59. [**Can Large Language Models Predict the Outcome of Judicial Decisions? arXiv:2501.09768**Mohamed Bayan Kmainasi, Ali Ezzat Shahroor, Amani Al-Ghraibah*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/kmainasi-2025-large-language-models-predict-outcome/)
60. **[CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards](https://md.research.elamur.ai/free/en/papers/tian-2026-csrp-chain-thought-reasoning-chinese/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Tian, Yuhao Zhou, Man Lan*2026 · 1 citation*
61. **[FLUKE: A Linguistically-Driven and Task-Agnostic Framework for Robustness Evaluation](https://md.research.elamur.ai/free/en/papers/otmakhova-2026-fluke-linguistically-driven-task-agnostic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yulia Otmakhova, Thinh Hung Truong, Rahmad Mahendra, et al.*2026 · 1 citation*
62. **[From Weights to Activations: Is Steering the Next Frontier of Adaptation?](https://md.research.elamur.ai/free/en/papers/ostermann-2026-weights-activations-is-steering-next/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Simon Ostermann, Daniil Gurgurov, Tanja Baeumel, et al.*2026 · 1 citation*
63. **[PromptLab: A Collaborative Platform for Prompt Engineering and Dataset Curation](https://md.research.elamur.ai/free/en/papers/shaibani-2026-promptlab-collaborative-platform-prompt-engineering/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Maged S. Al-shaibani, Zaid Alyafeai, Dania Refai, et al.*2026 · 1 citation*
64. **[Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics](https://md.research.elamur.ai/free/en/papers/xu-2026-why-steering-works-unified-view/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwen Xu, Chenyan WU, Hengyu Sun, et al.*2026 · 1 citation*
65. **[Annotation Entropy Predicts Per-Example Learning Dynamics in LoRA Fine-Tuning](https://md.research.elamur.ai/free/en/papers/steele-2026-annotation-entropy-predicts-per-example/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Brady Steele*2026*
66. [**ArabiGEE: A Hierarchical Taxonomy for Arabic Grammatical Error Explanation arXiv:2606.10765**Khaled Elhady, Omar Kallas, Nizar Habash, et al.*2026*](https://md.research.elamur.ai/free/en/papers/elhady-2026-arabigee-hierarchical-taxonomy-arabic-grammatical/)
67. **[CEBC: Conformal Evidence-Bounded Control for Low-Hallucination Vision–Language Generation](https://md.research.elamur.ai/free/en/papers/mishra-2026-cebc-conformal-evidence-bounded-control/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ashish Mishra, Tarun Kumar, Arpit Shah, et al.*2026*
68. **[Corpora Generation for Urdu Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/ahad-2026-corpora-generation-urdu-grammatical-error/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Syed Ahad, Burhanuddin Aliasghar Ezzi, Muhammad Arsalan Hussain, et al.*2026*
69. **[FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation](https://md.research.elamur.ai/free/en/papers/siddika-2026-fedreft-federated-representation-fine-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fatema Siddika, Md Anwar Hossen, Juan Pablo Munoz, et al.*2026*
70. **[From Latents to Labels: Zero-Shot Named Entity Recognition using Sparse Autoencoder Features](https://md.research.elamur.ai/free/en/papers/vuth-2026-latents-labels-zero-shot-named/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Nakanyseth Vuth, Gilles Sérasset, Didier Schwab*2026*
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85. **[Why LoRA Fails to Forget: Regularized Low-Rank Adaptation Against Backdoors in Language Models](https://md.research.elamur.ai/free/en/papers/luong-2026-why-lora-fails-forget-regularized/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoang-Chau Luong, Lingwei Chen*2026*

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