Alexander Borzunov

Efficiency & Compression · 2023

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Alexander Borzunov trusts

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Dan Alistarh (in Efficiency & Compression)

Papers from Alexander Borzunov's perspective

Ordered by how strongly the researchers Alexander Borzunov trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Language Models are Unsupervised Multitask Learners
  2. Training Compute-Optimal Large Language Models (Advances in Neural Information Processing Systems 35)
  3. Finetuned Language Models Are Zero-Shot Learners
  4. RoFormer: Enhanced Transformer with Rotary Position Embedding
  5. GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
  6. Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
  7. The case for 4-bit precision: k-bit Inference Scaling Laws
  8. Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning
  9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers