293 citations
- Accenture (Switzerland)CH7 papers
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4 papers · 1 filter
Learning After Model Deployment
Derda Kaymak, Gyuhak Kim, Tomoya Kaichi +2
In classic supervised learning, once a model is deployed in an application, it is fixed. No updates will be made to it during the application. This is inappropriate for many dynami…
Breaking the ICE: Exploring promises and challenges of benchmarks for Inference Carbon & Energy estimation for LLMs
Samarth Sikand, Rohit Mehra, Priyavanshi Pathania +5
While Generative AI stands to be one of the fastest adopted technologies ever, studies have made evident that the usage of Large Language Models (LLMs) puts significant burden on e…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1144
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data
Mohak Shah, Mario Marchand, Jacques Corbeil
One of the objectives of designing feature selection learning algorithms is to obtain classifiers that depend on a small number of attributes and have verifiable future performance…