Changelog#
4 February 2026#
Bitflip-aware LoRA fine-tuning of Llama-3.1-8B (Bitflip-Aware LoRA Fine-Tuning)
LoRA adapters with only 1.2% trainable parameters effectively mitigate random bitflip noise, reducing validation perplexity from 1008.95 to 11.01 (clean baseline: 7.91).
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Llama-3.1-8B with random bitflip noise |
4 October 2025#
Optical Transformer fine-tuning on CLM models (60M – 1.1B) (Scaling Optical Transformers to Causal Language Models)
Full fine-tuning of pretrained CLM models with optical transformer simulation.
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Link |
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Optical Transformer on CLM |
1 October 2025#
Optical Transformer, Spiking Transformer, and PIM on RoBERTa
Initial experiments on RoBERTa with three new compute paradigms.
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Optical Transformer on RoBERTa |
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Spiking Transformer on RoBERTa |
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Processing in Memory on RoBERTa |
9 June 2025#
Mase-triton released on PyPI (Mase-Triton)
Our software-emulation and acceleration backend is now publicly available:
pip install mase-triton
See Mase-Triton for full documentation.
15 April 2025#
System and model-level training simulation for Small Language Models
Initial release of the scaling framework and bitflip-aware pretraining pipeline.
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Link |
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Environment setup |
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Pretraining AICrossSim-CLM (60M – 1.1B) and evaluation |
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Bitflip-aware pretraining and evaluation |