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Found 5 papers, 1 papers with code
A Survey on Efficient Inference for Large Language Models
This paper presents a comprehensive survey of the existing literature on efficient LLM inference.
Evaluating Quantized Large Language Models
Post-training quantization (PTQ) has emerged as a promising technique to reduce the cost of large language models (LLMs).
A Causal Framework to Unify Common Domain Generalization Approaches
Domain generalization (DG) is about learning models that generalize well to new domains that are related to, but different from, the training domain(s).
Model Debiasing via Gradient-based Explanation on Representation
Machine learning systems produce biased results towards certain demographic groups, known as the fairness problem.
Contrastive Domain Generalization via Logit Attribution Matching
Domain Generalization (DG) is an important open problem in machine learning.
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