---
title: "EMNLP 2024 — all papers: 35 in our library, the most cited first"
description: "35 works of EMNLP 2024 in our library, the most cited first. Among them: Large Language Models for Data Annotation and Synthesis: A…"
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# EMNLP 2024: all papers in our library

35 works · the most cited first · [← EMNLP 2024](https://md.research.elamur.ai/free/en/venues/emnlp/2024/)

1. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 259 citations*
2. **[mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2024-mgte-generalized-long-context-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Zhang, Yanzhao Zhang, Dingkun Long, et al.*2024 · 236 citations*
3. **[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*
4. **[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 · 179 citations*
5. **[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 · 159 citations*
6. **[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*
7. **[Dense X Retrieval: What Retrieval Granularity Should We Use?](https://md.research.elamur.ai/free/en/papers/chen-2024-dense-x-retrieval-what-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tong Chen, Hongwei Wang, Sihao Chen, et al.*2024 · 142 citations*
8. **[Humans or LLMs as the Judge? A Study on Judgement Bias](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-or-llms-as-judge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 131 citations*
9. **[EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-2-faster-inference-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 131 citations*
10. **[Towards Measuring and Modeling “Culture” in LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/adilazuarda-2024-measuring-modeling-culture-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania, et al.*2024 · 102 citations*
11. **[Moral Foundations of Large Language Models](https://md.research.elamur.ai/free/en/papers/abdulhai-2024-moral-foundations-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Marwa Abdulhai, Gregory Serapio-García, Clement Crepy, et al.*2024 · 94 citations*
12. **[Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs](https://md.research.elamur.ai/free/en/papers/ong-2024-optimizing-instructions-demonstrations-multi-stage/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, et al.*2024 · 89 citations*
13. **[When Is Multilinguality a Curse? Language Modeling for 250 High- and Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/chang-2024-when-is-multilinguality-curse-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tyler A. Chang, Catherine Arnett, Zhuowen Tu, et al.*2024 · 85 citations*
14. **[Benchmarking Vision Language Models for Cultural Understanding](https://md.research.elamur.ai/free/en/papers/nayak-2024-benchmarking-vision-language-models-cultural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shravan Nayak, Kanishk Jain, Rabiul Awal, et al.*2024 · 85 citations*
15. **[Is LLM-as-a-Judge Robust? Investigating Universal Adversarial Attacks on Zero-shot LLM Assessment](https://md.research.elamur.ai/free/en/papers/raina-2024-is-llm-as-judge-robust/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Vyas Raina, Adian Liusie, Mark Gales*2024 · 85 citations*
16. **[LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-Training](https://md.research.elamur.ai/free/en/papers/zhu-2024-llama-moe-building-mixture-experts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tong Zhu, Xiaoye Qu, Daize Dong, et al.*2024 · 85 citations*
17. **[Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning](https://md.research.elamur.ai/free/en/papers/tan-2024-democratizing-large-language-models-personalized/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, et al.*2024 · 83 citations*
18. **[Mitigating the Alignment Tax of RLHF](https://md.research.elamur.ai/free/en/papers/lin-2024-mitigating-alignment-tax-rlhf/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yong Lin, Hangyu Lin, Wei Xiong, et al.*2024 · 82 citations*
19. **[Chain-of-Dictionary Prompting Elicits Translation in Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2024-chain-dictionary-prompting-elicits-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hongyuan Lu, Haoran Yang, Haoyang Huang, et al.*2024 · 81 citations*
20. **[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 · 76 citations*
21. **[LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing](https://md.research.elamur.ai/free/en/papers/du-2024-llms-assist-nlp-researchers-critique/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiangshu Du, Yibo Wang, Wenting Zhao, et al.*2024 · 71 citations*
22. **[Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA](https://md.research.elamur.ai/free/en/papers/wang-2024-leave-no-document-behind-benchmarking/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Minzheng Wang, Longze Chen, Fu Cheng, et al.*2024 · 71 citations*
23. **[Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue](https://md.research.elamur.ai/free/en/papers/gu-2024-model-editing-harms-general-abilities/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jia-Chen Gu, Hao-Xiang Xu, Jun-Yu Ma, et al.*2024 · 66 citations*
24. **[MT-Eval: A Multi-Turn Capabilities Evaluation Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/kwan-2024-mt-eval-multi-turn-capabilities/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wai-Chung Kwan, Xingshan Zeng, Yuxin Jiang, et al.*2024 · 66 citations*
25. **[Tokenization Is More Than Compression](https://md.research.elamur.ai/free/en/papers/schmidt-2024-tokenization-is-more-than-compression/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Craig W Schmidt, Varshini Reddy, Haoran Zhang, et al.*2024 · 66 citations*
26. **[On the Proper Treatment of Tokenization in Psycholinguistics](https://md.research.elamur.ai/free/en/papers/giulianelli-2024-proper-treatment-tokenization-psycholinguistics/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mario Giulianelli, Luca Malagutti, Juan Luis Gastaldi, et al.*2024 · 23 citations*
27. **[Is Child-Directed Speech Effective Training Data for Language Models?](https://md.research.elamur.ai/free/en/papers/feng-2024-is-child-directed-speech-effective/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Steven Y. Feng, Noah D. Goodman, Michael C. Frank*2024 · 18 citations*
28. [**StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements**Jillian Fisher, Skyler Hallinan, Ximing Lu, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/fisher-2024-styleremix-interpretable-authorship-obfuscation-distillation/)
29. **[Bridging Cultures in the Kitchen: A Framework and Benchmark for Cross-Cultural Recipe Retrieval](https://md.research.elamur.ai/free/en/papers/hu-2024-bridging-cultures-kitchen-framework-benchmark/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianyi Hu, Maria Maistro, Daniel Hershcovich*2024 · 16 citations*
30. **[Rethinking Pragmatics in Large Language Models: Towards Open-Ended Evaluation and Preference Tuning](https://md.research.elamur.ai/free/en/papers/wu-2024-rethinking-pragmatics-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shengguang Wu, Shusheng Yang, Zhenglun Chen, et al.*2024 · 16 citations*
31. [**Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics**Stefano Perrella, Lorenzo Proietti, Pere-Lluís Huguet Cabot, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/perrella-2024-beyond-correlation-interpretable-evaluation-machine/)
32. **[Major Entity Identification: A Generalizable Alternative to Coreference Resolution](https://md.research.elamur.ai/free/en/papers/manikantan-2024-major-entity-identification-generalizable-alternative/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kawshik Manikantan, Shubham Toshniwal, Makarand Tapaswi, et al.*2024 · 13 citations*
33. [**GDTB: Genre Diverse Data for English Shallow Discourse Parsing across Modalities, Text Types, and Domains**Yang Janet Liu, Tatsuya Aoyama, Wesley Scivetti, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-gdtb-genre-diverse-data-english/)
34. [**RSA-Control: A Pragmatics-Grounded Lightweight Controllable Text Generation Framework**Yifan Wang, Vera Demberg*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-rsa-control-pragmatics-grounded-lightweight/)
35. **[Contribution of Linguistic Typology to Universal Dependency Parsing: An Empirical Investigation](https://md.research.elamur.ai/free/en/papers/basirat-2024-contribution-linguistic-typology-universal-dependency/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ali Basirat, Navid Baradaran Hemmati*2024*
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