Language agents show potential in being capable of utilizing natural language for varied
and intricate tasks in diverse environments, particularly when built upon large language …

Evaluating outputs of large language models (LLMs) is challenging, requiring making—and
making sense of—many responses. Yet tools that go beyond basic prompting tend to require …

By simply composing prompts, developers can prototype novel generative applications with
Large Language Models (LLMs). To refine prototypes into products, however, developers …

Large language model (LLM) prompting is a promising new approach for users to create
and customize their own chatbots. However, current methods for steering a chatbot's …

Developing efficient and reliable voice-controlled systems involves addressing various
challenges that significantly impact the accuracy and usability of these systems [47]. One …

Compelling writing is tailored to its audience. This is challenging, as writers may struggle to
empathize with readers, get feedback in time, or gain access to the target group. We …

The use of Large Language Models (LLMs) for writing has sparked controversy both among
readers and writers. On one hand, writers are concerned that LLMs will deprive them of …

Conversational interfaces powered by Large Language Models (LLMs) have recently
become a popular way to obtain feedback during document editing. However, standard chat …

Prototyping AI applications is notoriously difficult. While large language model (LLM)
prompting has dramatically lowered the barriers to AI prototyping, designers are still …

Programmers increasingly rely on Large Language Models (LLMs) for code generation.
However, they now have to deal with issues like having to constantly switch between …