34 citations · 92 across the 26 of their papers we have counts for
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cs.CL2025
Scaling Laws for Code: Every Programming Language Matters
Jian Yang, Shawn Guo, Lin Jing +8
Code large language models (Code LLMs) are powerful but costly to train, with scaling laws predicting performance from model size, data, and compute. However, different programming…
cs.CL2024★ 1 cited
LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment
Ge Yang, Changyi He, Jinyang Guo +6
Although large language models (LLMs) have demonstrated their strong intelligence ability, the high demand for computation and storage hinders their practical application. To this…
cs.CL2022★ 34 cited
BiBERT: Accurate Fully Binarized BERT
Haotong Qin, Yifu Ding, Mingyuan Zhang +5
The large pre-trained BERT has achieved remarkable performance on Natural Language Processing (NLP) tasks but is also computation and memory expensive. As one of the powerful compr…