Reinforcement learning from human feedback (RLHF) is a variant of reinforcement learning
(RL) that learns from human feedback instead of relying on an engineered reward function …

While large language models (LLMs) trained with large-scale unsupervised learning acquire
a wide variety of world knowledge and skills, its behavior does not necessarily align with …

Large language models (LLMs) are effective at answering questions that are clearly asked.
However, when faced with ambiguous queries they can act unpredictably and produce …

Despite LLMs' recent advancements, they still suffer from factual inconsistency and
hallucination. An often-opted remedy is retrieval-augmented generation–however, there is …

Accurately carrying out complex reasoning is a crucial component of deployable and
reliable language models. While current language models can exhibit this capability with …