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Rashid, Ahmad

  1. Towards Zero-Shot Knowledge Distillation for Natural Language Processing
    2020/12/31 by Rashid, Ahmad, Lioutas, Vasileios, Ghaddar, Abbas +1 · 2 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  2. A Short Study on Compressing Decoder-Based Language Models
    2021/10/16 by Tianda Li, Yassir El Mesbahi, Li, Tianda +15 · 2 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text and Document Classification Technologies #Topic Modeling
  3. A Critical Look At Tokenwise Reward-Guided Text Generation
    2024/06/12 by Ahmad Rashid, Ruotian Wu, Rashid, Ahmad +7 · 3 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques
  4. MATE-KD: Masked Adversarial TExt, a Companion to Knowledge Distillation
    2021/05/12 by Rashid, Ahmad, Lioutas, Vasileios, Rezagholizadeh, Mehdi · 1 citation
    #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  5. Kronecker Decomposition for GPT Compression
    2021/10/15 by Ali Edalati, Edalati, Ali, Marzieh S. Tahaei +9 · 1 citation
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning in Healthcare #Natural Language Processing Techniques #Topic Modeling
  6. Learning Functions on Multiple Sets using Multi-Set Transformers
    2022/06/30 by Kira Selby, Selby, Kira, Ahmad Rashid +7 · 1 citation
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms
  7. Towards Cost-Effective Reward Guided Text Generation
    2025/02/06 by Ahmad Rashid, Ruotian Wu, Rashid, Ahmad +8 · 2 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Topic Modeling