Amir Yazdanbakhsh
15 papers · 2020–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π Cross-Pollinator (10) πΊοΈ Taxonomy Completionist (15) π Academic Marathon (5) π§ Keyword Pioneer
π
Conference Polyglot
(4)
π
Triple Crown
π
Century Club
(15)
β‘
Prolific Year
(6)
β
The Questioner
Conferences
ICLR (6)
ICML (5)
NIPS (3)
EMNLP (1)
Top co-authors
Keywords
large language model
(3)
model compression
(2)
few-shot learning
(1)
in-context learning
(1)
text generation
(1)
iterative refinement
(1)
variance estimation
(1)
structured sparsity
(1)
adam optimizer
(1)
weight pruning
(1)
weight quantization
(1)
inference acceleration
(1)
multiplication-free model
(1)
hardware acceleration
(1)
chain-of-thought prompting
(1)
encoder-decoder architecture
(1)
bidirectional translation
(1)
code translation
(1)
cuda programming
(1)
bit allocation
(1)
Papers
SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression
ICML 2025
The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws
ICLR 2025
SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs
ICLR 2025
Effective Interplay between Sparsity and Quantization: From Theory to Practice
ICLR 2025
Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding
ICML 2025
SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity
ICML 2025
Learning Performance-Improving Code Edits
ICLR 2024
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
ICML 2024
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
NIPS 2024
CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming
NIPS 2024
STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition
ICML 2023
What Makes Chain-of-Thought Prompting Effective? A Counterfactual Study
EMNLP 2023
Self-Refine: Iterative Refinement with Self-Feedback
NIPS 2023
Data-Driven Offline Optimization for Architecting Hardware Accelerators
ICLR 2022
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation
ICLR 2020