9 citations · 10 across the 7 of their papers we have counts for
Showing cs.AIShow all
2 papers · 1 filter
cs.AI2026
Breaking the 1.58-bit Barrier for Ternary LLMs
Evangelos Georganas, Alexander Heinecke, Pradeep Dubey
Ternary Large Language Models (LLM) store every weight as one of three symbols , so the cost of a ternary model is conventionally referenced to the information-theoret…
cs.AI2025
Pushing the Envelope of LLM Inference with Ultra-Low-Bit Quantized Models
Evangelos Georganas, Dhiraj Kalamkar, Alexander Heinecke +1
The advent of ultra-low-bit LLM models, approaching the perplexity and task accuracy of their full precision counterparts, is ushering in a new era of LLM inference. While these ad…