We view large language models (LLMs) as stochastic language layers in a network, where the learnable parameters are the natural language prompts at each layer. We stack two such layers, feeding the output of one layer to the next. We call the stacked architecture a…
Powered by recent advances in code-generating models, AI assistants like Github Copilot promise to change the face of programming forever. But what is this new face of programming? We present the first grounded theory analysis of how programmers interact with Copilot, based on observing 20…
AI explanations are often mentioned as a way to improve human-AI decision-making. Yet, empirical studies have not found consistent evidence of explanations' effectiveness and, on the contrary, suggest that they can increase overreliance when the AI system is wrong. While many factors may affect reliance…
Code-generating large language models (LLMs) are transforming programming. Their capability to generate multi-step solutions provides even non-programmers a mechanism to harness the power of programming. Non-programmers typically use spreadsheets to manage tabular data, as it offers an intuitive understanding of data manipulation and formula outcomes.…
Formatting is an important property in tables for visualization, presentation, and analysis. Spreadsheet software allows users to automatically format their tables by writing data-dependent conditional formatting (CF) rules. Writing such rules is often challenging for users as it requires them to understand and implement the…
With the proliferation of IoT sensors, the reliance on sensor telemetry has never been greater. Today numerous applications from smart agriculture to smart buildings and cities, rely on IoT telemetry to provide insights and to take decisions. However, due to the characteristics of these IoT…
Modern email clients support predicate-based folder assignment rules that can automatically organize emails. Unfortunately, users still need to write these rules manually. Prior machine learning approaches have framed automatically assigning email to folders as a classification task and do not produce symbolic rules. Prior inductive…
Building an interactive AI assistant that can perceive, reason, and collaborate with humans in the real world has been a long-standing pursuit in the AI community. This work is part of a broader research effort to develop intelligent agents that can interactively guide humans through…
Log data can reveal valuable information about how users interact with web search services, what they want, and how satisfied they are. However, analyzing user intents in log data is not easy, especially for new forms of web search such as AI-driven chat. To understand…
Generative Large Language Models (LLMs) have achieved remarkable advancements in various NLP tasks. However, these advances have not been reflected in the translation task, especially those with moderate model sizes (i.e., 7B or 13B parameters), which still lag behind conventional supervised encoder-decoder translation models. Previous…
With most modern visualization tools, authors need to transform their data into tidy formats to create visualizations they want. Because this requires experience with programming or separate data processing tools, data transformation remains a barrier in visualization authoring. To address this challenge, we present a…
We continue the investigation into the power of smaller Transformer-based language models as initiated by \textbf{TinyStories} -- a 10 million parameter model that can produce coherent English -- and the follow-up work on \textbf{phi-1}, a 1.3 billion parameter model with Python coding performance close to…
