Search

Any time Past 24 hours Past week Past monthSort:Relevance Newest

Benchmark

WikiText-2

Reported in 19 papers on Zotpaper. The latest, each as the paper states it:

Combining model compression techniques can collapse small language models920.56 perplexity
4-bit language models run as integer math on Apple's M5 chips without extra accuracy loss10.4 perplexity

WikiText2 (2)All benchmarks →

1 result for “WikiText-2”

Research · Efficiency & systems
Combining model compression techniques can collapse small language models
Compression Technique Interactions in Small Language Models: A Factorial Ablation Study
A systematic study of 72 compression configurations shows that INT8 quantization is lossless, while NF4 with pruning causes total failure, and LoRA fine-tuning recovers most quality without a teacher model.
WikiText-2: 920.56 perplexity (as reported)
3 Nov 2026Amazon Web Services