---
title: "Who cites Kaitao Song"
description: "1,225 papers of the Elamur Research library cite the works of Kaitao Song, found in their bibliographies; the most cited first."
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---
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# Who cites Kaitao Song

1,237 citations of their works from 1,225 papers of our library (of the 140,884 whose bibliographies we read) · 95 with a page here, the most cited first · [← Kaitao Song](https://md.research.elamur.ai/free/en/authors/kaitao-song/)

1. [**BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension**Mike Lewis, Yinhan Liu, Naman Goyal, et al.*2020 · 12,752 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2020-bart-denoising-sequence-sequence-pre/)
2. [**Language Models are Few-Shot Learners**Tom B. Brown, Benjamin Mann, Nick Ryder, et al.*2020 · 10,782 citations*](https://md.research.elamur.ai/free/en/papers/brown-2020-language-models-few-shot-learners/)
3. [**Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer**Colin Raffel, Noam Shazeer, Adam Roberts, et al.*2019 · 7,433 citations*](https://md.research.elamur.ai/free/en/papers/raffel-2019-exploring-limits-transfer-learning-unified/)
4. [**Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing**Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al.*2021 · 5,375 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-pre-train-prompt-predict-systematic/)
5. [**A Survey on Evaluation of Large Language Models**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,640 citations*](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/)
6. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
7. [**PaLM: Scaling Language Modeling with Pathways**Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.*2022 · 2,603 citations*](https://md.research.elamur.ai/free/en/papers/chowdhery-2022-palm-scaling-language-modeling-pathways/)
8. [**SpanBERT: Improving Pre-training by Representing and Predicting Spans**Mandar Joshi, Danqi Chen, Yinhan Liu, et al.*2019 · 2,580 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2019-spanbert-improving-pre-training-representing/)
9. [**Reflexion: Language Agents with Verbal Reinforcement Learning**Noah Shinn, Federico Cassano, Edward Berman, et al.*2023 · 2,202 citations*](https://md.research.elamur.ai/free/en/papers/shinn-2023-reflexion-language-agents-verbal-reinforcement/)
10. [**PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization**Jingqing Zhang, Yao Zhao, Mohammad Saleh, et al.*2019 · 1,806 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-pegasus-pre-training-extracted-gap/)
11. [**Pre-trained Models for Natural Language Processing: A Survey**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,740 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
12. [**BERTopic: Neural topic modeling with a class-based TF-IDF procedure**Maarten Grootendorst*2022 · 1,729 citations*](https://md.research.elamur.ai/free/en/papers/grootendorst-2022-bertopic-neural-topic-modeling-class/)
13. [**Qwen Technical Report**Jinze Bai, Shuai Bai, Yunfei Chu, et al.*2023 · 1,643 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/)
14. [**GLM: General Language Model Pretraining with Autoregressive Blank Infilling**Zhengxiao Du, Yujie Qian, Xiao Liu, et al.*2022 · 1,449 citations*](https://md.research.elamur.ai/free/en/papers/du-2022-glm-general-language-model-pretraining/)
15. [**Unified Language Model Pre-training for Natural Language Understanding and Generation**Li Dong, Nan Yang, Wenhui Wang, et al.*2019 · 1,389 citations*](https://md.research.elamur.ai/free/en/papers/dong-2019-unified-language-model-pre-training/)
16. [**A Comprehensive Overview of Large Language Models**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/)
17. [**The Rise and Potential of Large Language Model Based Agents: A Survey**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,262 citations*](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/)
18. [**MTEB: Massive Text Embedding Benchmark**Niklas Muennighoff, Nouamane Tazi, Loïc Magne, et al.*2022 · 1,021 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-mteb-massive-text-embedding-benchmark/)
19. [**MPNet: Masked and Permuted Pre-training for Language Understanding**Kaitao Song, Xu Tan, Tao Qin, et al.*2020 · 944 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-mpnet-masked-permuted-pre-training/)
20. [**Findings of the 2019 Conference on Machine Translation (WMT19)**Loïc Barrault, Ondřej Bojar, Marta R. Costa-jussà, et al.*2019 · 839 citations*](https://md.research.elamur.ai/free/en/papers/barrault-2019-findings-2019-conference-machine-translation/)
21. [**Mask-Predict: Parallel Decoding of Conditional Masked Language Models**Marjan Ghazvininejad, Omer Levy, Yinhan Liu, et al.*2019 · 671 citations*](https://md.research.elamur.ai/free/en/papers/ghazvininejad-2019-mask-predict-parallel-decoding-conditional/)
22. [**Video-LLaVA: Learning United Visual Representation by Alignment Before Projection**Bin Lin, Yang Ye, Bin Zhu, et al.*2023 · 614 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-video-llava-learning-united-visual/)
23. [**Leveraging Pre-trained Checkpoints for Sequence Generation Tasks**Sascha Rothe, Shashi Narayan, Aliaksei Severyn*2019 · 562 citations*](https://md.research.elamur.ai/free/en/papers/rothe-2019-leveraging-pre-trained-checkpoints-sequence/)
24. [**Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges**Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.*2019 · 555 citations*](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-massively-multilingual-neural-machine-translation/)
25. [**Document Ranking with a Pretrained Sequence-to-Sequence Model**Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, et al.*2020 · 538 citations*](https://md.research.elamur.ai/free/en/papers/nogueira-2020-document-ranking-pretrained-sequence-sequence/)
26. [**MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models**Chaoyou Fu, Peixian Chen, Yunhang Shen, et al.*2023 · 529 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-mme-comprehensive-evaluation-benchmark-multimodal/)
27. [**Gorilla: Large Language Model Connected with Massive APIs**Shishir G. Patil, Tianjun Zhang, Xin Wang, et al.*2023 · 527 citations*](https://md.research.elamur.ai/free/en/papers/patil-2023-gorilla-large-language-model-connected/)
28. [**Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation**Dawei Gao, Haibin Wang, Yaliang Li, et al.*2023 · 461 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-text-sql-empowered-large-language/)
29. [**OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework**Peng Wang, An Yang, Rui Men, et al.*2022 · 452 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-ofa-unifying-architectures-tasks-modalities/)
30. [**ProphetNet: Predicting Future N-gram for Sequence-to-SequencePre-training**Weizhen Qi, Yu Yan, Yeyun Gong, et al.*2020 · 451 citations*](https://md.research.elamur.ai/free/en/papers/qi-2020-prophetnet-predicting-future-n-gram/)
31. [**MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts**Pan Lu, Hritik Bansal, Tony Xia, et al.*2023 · 441 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/)
32. [**mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality**Qinghao Ye, Haiyang Xu, Guohai Xu, et al.*2023 · 410 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-mplug-owl-modularization-empowers-large/)
33. [**InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks**Zhe Chen, Jiannan Wu, Wenhai Wang, et al.*2023 · 409 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-internvl-scaling-up-vision/)
34. [**LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models**Zhiqiang Hu, Lei Wang, Yihuai Lan, et al.*2023 · 398 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-llm-adapters-adapter-family-parameter/)
35. [**A Unified Generative Framework for Aspect-based Sentiment Analysis**Hang Yan, Junqi Dai, Tuo Ji, et al.*2021 · 396 citations*](https://md.research.elamur.ai/free/en/papers/yan-2021-unified-generative-framework-aspect-based/)
36. [**A Unified Generative Framework for Various NER Subtasks**Hang Yan, Tao Gui, Junqi Dai, et al.*2021 · 392 citations*](https://md.research.elamur.ai/free/en/papers/yan-2021-unified-generative-framework-various-ner/)
37. [**Large Language Models as Optimizers**Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.*2023 · 388 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-large-language-models-optimizers/)
38. [**Query Rewriting in Retrieval-Augmented Large Language Models**Xinbei Ma, Yeyun Gong, Pengcheng He, et al.*2023 · 383 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-query-rewriting-retrieval-augmented-large/)
39. [**UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training**Hangbo Bao, Li Dong, Furu Wei, et al.*2020 · 380 citations*](https://md.research.elamur.ai/free/en/papers/bao-2020-unilmv2-pseudo-masked-language-models/)
40. [**Mind2Web: Towards a Generalist Agent for the Web**Xiang Deng, Yu Gu, Boyuan Zheng, et al.*2023 · 376 citations*](https://md.research.elamur.ai/free/en/papers/deng-2023-mind2web-towards-generalist-agent-web/)
41. [**Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning**Liangming Pan, Alon Albalak, Xinyi Wang, et al.*2023 · 370 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-logic-lm-empowering-large-language/)
42. [**VideoChat: Chat-Centric Video Understanding**KunChang Li, Yinan He, Yi Wang, et al.*2023 · 351 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-videochat-chat-centric-video-understanding/)
43. [**MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities**Weihao Yu, Zhengyuan Yang, Linjie Li, et al.*2023 · 328 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-mm-vet-evaluating-large-multimodal/)
44. [**Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models**Pan Lu, Baolin Peng, Hao Cheng, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-chameleon-plug-play-compositional-reasoning/)
45. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 303 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/)
46. [**OpenPrompt: An Open-source Framework for Prompt-learning**Ning Ding, Shengding Hu, Weilin Zhao, et al.*2022 · 278 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-openprompt-open-source-framework-prompt/)
47. [**InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training**Zewen Chi, Li Dong, Furu Wei, et al.*2020 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chi-2020-infoxlm-information-theoretic-framework-cross/)
48. [**DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines**Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.*2023 · 261 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2023-dspy-compiling-declarative-language-model/)
49. [**Contrastive Learning for Many-to-many Multilingual Neural Machine Translation**Xiao Pan, Mingxuan Wang, Liwei Wu, et al.*2021 · 256 citations*](https://md.research.elamur.ai/free/en/papers/pan-2021-contrastive-learning-many-many-multilingual/)
50. [**Survey of Low-Resource Machine Translation**Barry Haddow, Rachel Bawden, Antonio Valerio Miceli Barone, et al.*2022 · 251 citations*](https://md.research.elamur.ai/free/en/papers/haddow-2022-survey-low-resource-machine-translation/)
51. [**Knowledge-Grounded Dialogue Generation with Pre-trained Language Models**Xueliang Zhao, Wei Wu, Can Xu, et al.*2020 · 244 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2020-knowledge-grounded-dialogue-generation-pre/)
52. [**Automatic Detection of Machine Generated Text: A Critical Survey**Ganesh Jawahar, Muhammad Abdul-Mageed, Laks Lakshmanan V.S.*2020 · 243 citations*](https://md.research.elamur.ai/free/en/papers/jawahar-2020-automatic-detection-machine-generated-text/)
53. [**On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey**Lin Long, Rui Wang, Ruixuan Xiao, et al.*2024 · 236 citations*](https://md.research.elamur.ai/free/en/papers/long-2024-llms-driven-synthetic-data-generation/)
54. [**Multilingual Translation from Denoising Pre-Training**Yuqing Tang, Chau Tran, Xian Li, et al.*2021 · 219 citations*](https://md.research.elamur.ai/free/en/papers/tang-2021-multilingual-translation-denoising-pre-training/)
55. [**Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding**Hang Zhang, Xin Li, Lidong Bing*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-video-llama-instruction-tuned-audio/)
56. [**GAIA: a benchmark for General AI Assistants**Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.*2023 · 211 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-gaia-benchmark-general-ai-assistants/)
57. [**MADLAD-400: A Multilingual And Document-Level Large Audited Dataset**Sneha Kudugunta, Isaac Caswell, Biao Zhang, et al.*2023 · 211 citations*](https://md.research.elamur.ai/free/en/papers/kudugunta-2023-madlad-400-multilingual-document-level/)
58. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 187 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
59. [**Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models**Yunfei Chu, Jin Xu, Xiaohuan Zhou, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-qwen-audio-advancing-universal/)
60. [**Planning with Learned Entity Prompts for Abstractive Summarization**Shashi Narayan, Yao Zhao, Joshua Maynez, et al.*2021 · 180 citations*](https://md.research.elamur.ai/free/en/papers/narayan-2021-planning-learned-entity-prompts-abstractive/)
61. [**ToolQA: A Dataset for LLM Question Answering with External Tools**Yuchen Zhuang, Yue Yu, Kuan Wang, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-toolqa-dataset-llm-question-answering/)
62. [**Pre-training Multilingual Neural Machine Translation by Leveraging Alignment Information**Zehui Lin, Xiao Pan, Mingxuan Wang, et al.*2020 · 177 citations*](https://md.research.elamur.ai/free/en/papers/lin-2020-pre-training-multilingual-neural-machine/)
63. [**ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases**Qiaoyu Tang, Ziliang Deng, Hongyu Lin, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-toolalpaca-generalized-tool-learning-language/)
64. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
65. [**LooGLE: Can Long-Context Language Models Understand Long Contexts?**Jiaqi Li, Mengmeng Wang, Zilong Zheng, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-loogle-long-context-language-models/)
66. [**LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression**Huiqiang Jiang, Qianhui Wu, Xufang Luo, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-longllmlingua-accelerating-enhancing-llms-long/)
67. [**Unsupervised Translation of Programming Languages**Marie-Anne Lachaux, Baptiste Roziere, Lowik Chanussot, et al.*2020 · 156 citations*](https://md.research.elamur.ai/free/en/papers/lachaux-2020-unsupervised-translation-programming-languages/)
68. [**HyperTree Proof Search for Neural Theorem Proving**Guillaume Lample, Marie-Anne Lachaux, Thibaut Lavril, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/lample-2022-hypertree-proof-search-neural-theorem/)
69. [**How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition**Guanting Dong, Hongyi Yuan, Keming Lu, et al.*2024 · 145 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-how-abilities-large-language-models/)
70. [**Executable Code Actions Elicit Better LLM Agents**Xingyao Wang, Yangyi Chen, Lifan Yuan, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-executable-code-actions-elicit-better/)
71. [**ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings**Shibo Hao, Tianyang Liu, Zhen Wang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/hao-2023-toolkengpt-augmenting-frozen-language-models/)
72. [**The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning**Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-unlocking-spell-base-llms-rethinking/)
73. [**Efficient Training of Language Models to Fill in the Middle**Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.*2022 · 137 citations*](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/)
74. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/)
75. [**From Persona to Personalization: A Survey on Role-Playing Language Agents**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
76. [**RestGPT: Connecting Large Language Models with Real-World RESTful APIs**Yifan Song, Weimin Xiong, Dawei Zhu, et al.*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/song-2023-restgpt-connecting-large-language-models/)
77. [**LegalAgentBench: Evaluating LLM Agents in Legal Domain**Haitao Li, Junjie Chen, Jingli Yang, et al.*2025 · 60 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-legalagentbench-evaluating-llm-agents-legal/)
78. [**ChatGPT vs Human-authored Text: Insights into Controllable Text Summarization and Sentence Style Transfer**Dongqi Liu, Vera Demberg*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-chatgpt-vs-human-authored-text/)
79. [**Automatic Evaluation and Analysis of Idioms in Neural Machine Translation**Christos Baziotis, Prashant Mathur, Eva Hasler*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/baziotis-2023-automatic-evaluation-analysis-idioms-neural/)
80. [**Can we obtain significant success in RST discourse parsing by using Large Language Models?**Aru Maekawa, Tsutomu Hirao, Hidetaka Kamigaito, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/maekawa-2024-can-we-obtain-significant-success/)
81. [**Bridging Cultures in the Kitchen: A Framework and Benchmark for Cross-Cultural Recipe Retrieval**Tianyi Hu, Maria Maistro, Daniel Hershcovich*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-bridging-cultures-kitchen-framework-benchmark/)
82. [**AIN: The Arabic INclusive Large Multimodal Model**Ahmed Heakl, Sara Ghaboura, Omkar Thawkar, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/heakl-2025-ain-arabic-inclusive-large-multimodal/)
83. [**Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering**Neha Srikanth, Rupak Sarkar, Heran Mane, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/srikanth-2024-pregnant-questions-importance-pragmatic-awareness/)
84. [**Character Coreference Resolution in Movie Screenplays**Sabyasachee Baruah, Shrikanth Narayanan*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/baruah-2023-character-coreference-resolution-movie-screenplays/)
85. [**TATA: Stance Detection via Topic-Agnostic and Topic-Aware Embeddings**Hans Hanley, Zakir Durumeric*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/hanley-2023-tata-stance-detection-topic-agnostic/)
86. [**An Extreme Multi-label Text Classification (XMTC) Library Dataset: What If We Took “Use of Practical AI in Digital Libraries” Seriously?**Jennifer D'Souza, Sameer Sadruddin, Maximilian Kaehler, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/souza-2026-extreme-multi-label-text-classification/)
87. [**A Massive Scale Semantic Similarity Dataset of Historical English**Emily Silcock, Melissa Dell*2023 · 2 citations*](https://md.research.elamur.ai/free/en/papers/silcock-2023-massive-scale-semantic-similarity-dataset/)
88. [**Intertextual Parallel Detection in Biblical Hebrew: A Transformer-Based Benchmark**David M. Smiley*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/smiley-2025-intertextual-parallel-detection-biblical-hebrew/)
89. [**Assessing and Improving Punctuation Robustness in English-Marathi Machine Translation**Kaustubh Shivshankar Shejole, Sourabh Deoghare, Pushpak Bhattacharyya*2026*](https://md.research.elamur.ai/free/en/papers/shejole-2026-assessing-improving-punctuation-robustness-english/)
90. [**Evaluating Hierarchical Aggregation and LLM-Based Matching for Synset Selection in Ancient Greek**Luca Brigada Villa, Marco Passarotti, Chiara Zanchi, et al.*2026*](https://md.research.elamur.ai/free/en/papers/villa-2026-evaluating-hierarchical-aggregation-llm-based/)
91. [**One Word Is Not Enough: Simple Prompts Improve Word Embeddings**Rajeev Ranjan*2026*](https://md.research.elamur.ai/free/en/papers/ranjan-2026-one-word-is-not-enough/)
92. [**Push and Pull: Training Sentence Encoders with Contrastive Losses for Distance-Based Multi-Label Text Classification**Jens Van Nooten, Andriy Kosar*2026*](https://md.research.elamur.ai/free/en/papers/nooten-2026-push-pull-training-sentence-encoders/)
93. [**To Write or to Automate Linguistic Prompts, That Is the Question**Marina Sánchez-Torrón, Daria Akselrod, Jason Rauchwerk*2026*](https://md.research.elamur.ai/free/en/papers/torron-2026-write-or-automate-linguistic-prompts/)
94. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)
95. [**Survey on Vision-language Pre-training (视觉语言预训练综述)**Jiong Yin (殷炯), Zhedong Zhang (张哲东), Yuhan Gao (高宇涵), et al.*2022*](https://md.research.elamur.ai/free/en/papers/yin-2022-vision-language-pre/)

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