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Found 3 papers, 2 papers with code
CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language Models
These help us curate CMoralEval that encompasses both explicit moral scenarios (14, 964 instances) and moral dilemma scenarios (15, 424 instances), each with instances from different data sources.
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale
We share in this paper our search strategies to adapt reference recommendation models to low-precision hardware, our optimization of low-precision compute kernels, and the design and development of tool chain so as to maintain our models' accuracy throughout their lifespan during which topic trends and users' interests inevitably evolve.
FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference
Deep learning models typically use single-precision (FP32) floating point data types for representing activations and weights, but a slew of recent research work has shown that computations with reduced-precision data types (FP16, 16-bit integers, 8-bit integers or even 4- or 2-bit integers) are enough to achieve same accuracy as FP32 and are much more efficient.
