For a long time, researchers have sought artificial intelligence (AI) that matches or exceeds
human intelligence. AI agents, which are artificial entities capable of sensing the …

Well-designed prompts can guide text-to-image models to generate amazing images.
However, the performant prompts are often model-specific and misaligned with user input …

Natural language generation has witnessed significant advancements due to the training of
large language models on vast internet-scale datasets. Despite these advancements, there …

Abstract Language models (LMs) often exhibit undesirable text generation behaviors,
including generating false, toxic, or irrelevant outputs. Reinforcement learning from human …

Large language models (LLMs) are used to generate content for a wide range of tasks, and
are set to reach a growing audience in coming years due to integration in product interfaces …

Collecting high quality conversational data can be very expensive for most applications and
infeasible for others due to privacy, ethical, or similar concerns. A promising direction to …

The recent spread of Deep Learning-based solutions for Artificial Intelligence and the
development of Large Language Models has pushed forwards significantly the Natural …

Despite the recent progress in language generation models, their outputs may not always
meet user expectations. In this work, we study whether informational feedback in natural …

Commonsense capabilities of pre-trained language models dramatically improve with scale,
leading many to believe that scale is the only winning recipe. But is it? Here, we investigate …

As humans, we consistently engage in interactions with our peers and receive feedback in
the form of natural language. This language feedback allows us to reflect on our actions …