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Found 5 papers, 2 papers with code
Topics, Authors, and Institutions in Large Language Model Research: Trends from 17K arXiv Papers
Large language models (LLMs) are dramatically influencing AI research, spurring discussions on what has changed so far and how to shape the field's future.
Coarse race data conceals disparities in clinical risk score performance
Across outcomes and metrics, we show that the risk scores exhibit significant granular performance disparities within coarse race groups.
Combining Compressions for Multiplicative Size Scaling on Natural Language Tasks
Our work quantitatively demonstrates that combining compression methods can synergistically reduce model size, and that practitioners should prioritize (1) quantization, (2) knowledge distillation, and (3) pruning to maximize accuracy vs. model size tradeoffs.
Studying the Consistency and Composability of Lottery Ticket Pruning Masks
Magnitude pruning is a common, effective technique to identify sparse subnetworks at little cost to accuracy.
Dissecting Lottery Ticket Transformers: Structural and Behavioral Study of Sparse Neural Machine Translation
Recent work on the lottery ticket hypothesis has produced highly sparse Transformers for NMT while maintaining BLEU.
