3 papers
cs.LG2026
Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback
Jungtaek Kim, Thomas Zeng, Ziqian Lin +5
Effective problem solving with Large Language Models (LLMs) can be enhanced when they are paired with external search algorithms. By viewing the space of diverse ideas and their fo…
cs.CL2023
H2O Open Ecosystem for State-of-the-art Large Language Models
Arno Candel, Jon McKinney, Philipp Singer +4
Large Language Models (LLMs) represent a revolution in AI. However, they also pose many significant risks, such as the presence of biased, private, copyrighted or harmful text. For…
cs.CL2023
h2oGPT: Democratizing Large Language Models
Arno Candel, Jon McKinney, Philipp Singer +12
Applications built on top of Large Language Models (LLMs) such as GPT-4 represent a revolution in AI due to their human-level capabilities in natural language processing. However,…