🧑‍🔬 Who cites Chitwan Saharia

478 citations of their works from 475 papers of our library (of the 141,840 whose bibliographies we read) · 21 with a page here, the most cited first · ← Chitwan Saharia

Language Models as Knowledge Bases?Conference on Empirical Methods in Natural Language Processing (EMNLP)Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, et al.2019 · 2,992 citations
Scalable Diffusion Models with TransformersIEEE/CVF International Conference on Computer Vision (ICCV)William Peebles, Saining Xie2022 · 2,595 citations
1. Visual Instruction TuningarXiv:2304.08485Haotian Liu, Chunyuan Li, Qingyang Wu, et al.2023 · 2,491 citations
2. LAION-5B: An open large-scale dataset for training next generation image-text modelsarXiv:2210.08402Christoph Schuhmann, Romain Beaumont, Richard Vencu, et al.2022 · 1,403 citations
   MTEB: Massive Text Embedding BenchmarkConference of the European Chapter of the Association for Computational Linguistics (EACL)Niklas Muennighoff, Nouamane Tazi, Loïc Magne, et al.2022 · 1,021 citations
3. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 779 citations
4. SDXL: Improving Latent Diffusion Models for High-Resolution Image SynthesisarXiv:2307.01952Dustin Podell, Zion English, Kyle Lacey, et al.2023 · 570 citations
5. Diffusion-LM Improves Controllable Text GenerationarXiv:2205.14217Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, et al.2022 · 423 citations
6. Can AI-Generated Text be Reliably Detected?arXiv:2303.11156Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, et al.2023 · 302 citations
7. Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified FlowarXiv:2209.03003Xingchao Liu, Chengyue Gong, Qiang Liu2022 · 254 citations
8. Structured Denoising Diffusion Models in Discrete State-SpacesarXiv:2107.03006Jacob Austin, Daniel D. Johnson, Jonathan Ho, et al.2021 · 244 citations
   OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text DocumentsConference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.2023 · 183 citations
   Glancing Transformer for Non-Autoregressive Neural Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Lihua Qian, Hao Zhou, Yu Bao, et al.2021 · 180 citations
   Fully Non-autoregressive Neural Machine Translation: Tricks of the TradeFindings of the Association for Computational LinguisticsJiatao Gu, Xiang Kong2021 · 141 citations
   DiffusionBERT: Improving Generative Masked Language Models with Diffusion ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhengfu He, Tianxiang Sun, Qiong Tang, et al.2023 · 134 citations
9. Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine TranslationarXiv:2006.10369Jungo Kasai, Nikolaos Pappas, Hao Peng, et al.2020 · 132 citations
   Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq GenerationFindings of the Association for Computational LinguisticsHeming Xia, Tao Ge, Peiyi Wang, et al.2023 · 102 citations
   Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and GenerationIEEE Computer Society Conference on Computer Vision and Pattern RecognitionChengyue Wu, Xiaokang Chen, Zhiyu Wu, et al.2024 · 100 citations
10. InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and CompositionarXiv:2309.15112Pan Zhang, Xiaoyi Dong, Bin Wang, et al.2023 · 85 citations
    Bridging the Gap between Synthetic and Authentic Images for Multimodal Machine TranslationConference on Empirical Methods in Natural Language Processing (EMNLP)Wenyu Guo, Qingkai Fang, Dong Yu, et al.2023 · 15 citations
    MUSIA: Multilingual Story Illustration Corpus for Cross-Cultural Alignment and GenerationLanguage Resources and Evaluation Conference (LREC)Krishna Tewari, Supriya Chanda, Nirmit Patil, et al.2026

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