• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 48 matches

• 2024
• 
  Nélida Mirabet-Herranz, Chiara Galdi, Jean-Luc Dugelay:
  One Embedding to Predict Them All: Visible and Thermal Universal Face Representations for Soft Biometric Estimation via Vision Transformers. CVPR Workshops 2024: 1500-1509
• 
  Matthew Kowal, Achal Dave, Rares Ambrus, Adrien Gaidon, Konstantinos G. Derpanis, Pavel Tokmakov:
  Understanding Video Transformers via Universal Concept Discovery. CVPR 2024: 10946-10956
• 
  Tokio Kajitsuka, Issei Sato:
  Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators? ICLR 2024
• 
  Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo:
  Unified Training of Universal Time Series Forecasting Transformers. ICML 2024
• 
  Matthew Kowal, Achal Dave, Rares Ambrus, Adrien Gaidon, Konstantinos G. Derpanis, Pavel Tokmakov:
  Understanding Video Transformers via Universal Concept Discovery. CoRR abs/2401.10831 (2024)
• 
  Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo:
  Unified Training of Universal Time Series Forecasting Transformers. CoRR abs/2402.02592 (2024)
• 
  Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter:
  Universal Physics Transformers. CoRR abs/2402.12365 (2024)
• 
  Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber, Christopher Potts, Christopher D. Manning:
  MoEUT: Mixture-of-Experts Universal Transformers. CoRR abs/2405.16039 (2024)
• 
  Hang Zhou, Yuezhou Ma, Haixu Wu, Haowen Wang, Mingsheng Long:
  Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers. CoRR abs/2405.17527 (2024)
• 
  Souradip Poddar, Youngmin Oh, Yao Lai, Hanqing Zhu, Bosun Hwang, David Z. Pan:
  INSIGHT: Universal Neural Simulator for Analog Circuits Harnessing Autoregressive Transformers. CoRR abs/2407.07346 (2024)
• 
  Takashi Furuya, Maarten V. de Hoop, Gabriel Peyré:
  Transformers are Universal In-context Learners. CoRR abs/2408.01367 (2024)
• 
  Emanuele Zappala, Maryam Bagherian:
  Universal Approximation of Operators with Transformers and Neural Integral Operators. CoRR abs/2409.00841 (2024)
• 
  Michael E. Sander, Gabriel Peyré:
  Towards Understanding the Universality of Transformers for Next-Token Prediction. CoRR abs/2410.03011 (2024)
• 
  Joseph Liu, Joshua Geddes, Ziyu Guo, Haomiao Jiang, Mahesh Kumar Nandwana:
  SmoothCache: A Universal Inference Acceleration Technique for Diffusion Transformers. CoRR abs/2411.10510 (2024)
• 
  Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, Han Liu:
  Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency. CoRR abs/2411.16525 (2024)
• 2023
• 
  Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanic:
  Small Transformers Compute Universal Metric Embeddings. J. Mach. Learn. Res. 24: 170:1-170:48 (2023)
• 
  Hongwei Yu, Jiansheng Chen, Huimin Ma, Cheng Yu, Xinlong Ding:
  Defending Against Universal Patch Attacks by Restricting Token Attention in Vision Transformers. ICASSP 2023: 1-5
• 
  Silas Alberti, Niclas Dern, Laura Thesing, Gitta Kutyniok:
  Sumformer: Universal Approximation for Efficient Transformers. TAG-ML 2023: 72-86
• 
  André Brasil Vieira Wyzykowski, Anil Kumar Jain:
  A Universal Latent Fingerprint Enhancer Using Transformers. CoRR abs/2306.00231 (2023)
• 
  Silas Alberti, Niclas Dern, Laura Thesing, Gitta Kutyniok:
  Sumformer: Universal Approximation for Efficient Transformers. CoRR abs/2307.02301 (2023)
• 
  Sourya Basu, Moulik Choraria, Lav R. Varshney:
  Transformers are Universal Predictors. CoRR abs/2307.07843 (2023)
• 
  Tokio Kajitsuka, Issei Sato:
  Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators? CoRR abs/2307.14023 (2023)
• 
  K. L. Navaneet, Soroush Abbasi Koohpayegani, Essam Sleiman, Hamed Pirsiavash:
  SlowFormer: Universal Adversarial Patch for Attack on Compute and Energy Efficiency of Inference Efficient Vision Transformers. CoRR abs/2310.02544 (2023)
• 2022
• 
  Yuan Li:
  Learning both Expert and Universal Knowledge using Transformers. Duke University, Durham, NC, USA, 2022
• 
  Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch:
  Frozen Pretrained Transformers as Universal Computation Engines. AAAI 2022: 7628-7636
• 
  Agrim Gupta, Linxi Fan, Surya Ganguli, Li Fei-Fei:
  MetaMorph: Learning Universal Controllers with Transformers. ICLR 2022
• 
  Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, Ivan Dokmanic:
  Universal Approximation Under Constraints is Possible with Transformers. ICLR 2022
• 
  Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
  Towards Learning Universal Hyperparameter Optimizers with Transformers. NeurIPS 2022
• 
  Rahul Goel, Modar Sulaiman, Kimia Noorbakhsh, Mahdi Sharifi, Rajesh Sharma, Pooyan Jamshidi, Kallol Roy:
  Pre-Trained Language Transformers are Universal Image Classifiers. CoRR abs/2201.10182 (2022)
• 
  Agrim Gupta, Linxi Fan, Surya Ganguli, Li Fei-Fei:
  MetaMorph: Learning Universal Controllers with Transformers. CoRR abs/2203.11931 (2022)

skipping 18 more matches