Search Results for author: Michael Terry

Found 14 papers, 4 papers with code

Farsight: Fostering Responsible AI Awareness During AI Application Prototyping

1 code implementation23 Feb 2024 Zijie J. Wang, Chinmay Kulkarni, Lauren Wilcox, Michael Terry, Michael Madaio

To address this, we present Farsight, a novel in situ interactive tool that helps people identify potential harms from the AI applications they are prototyping.

LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models

no code implementations16 Feb 2024 Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, Lucas Dixon

Automatic side-by-side evaluation has emerged as a promising approach to evaluating the quality of responses from large language models (LLMs).

ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles

no code implementations24 Oct 2023 Savvas Petridis, Ben Wedin, James Wexler, Aaron Donsbach, Mahima Pushkarna, Nitesh Goyal, Carrie J. Cai, Michael Terry

Inspired by these findings, we developed ConstitutionMaker, an interactive tool for converting user feedback into principles, to steer LLM-based chatbots.

Chatbot Language Modelling +2

The Design Space of Generative Models

no code implementations15 Apr 2023 Meredith Ringel Morris, Carrie J. Cai, Jess Holbrook, Chinmay Kulkarni, Michael Terry

Card et al.'s classic paper "The Design Space of Input Devices" established the value of design spaces as a tool for HCI analysis and invention.

IMACS: Image Model Attribution Comparison Summaries

no code implementations26 Jan 2022 Eldon Schoop, Ben Wedin, Andrei Kapishnikov, Tolga Bolukbasi, Michael Terry

Developing a suitable Deep Neural Network (DNN) often requires significant iteration, where different model versions are evaluated and compared.

Image Classification

AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts

no code implementations4 Oct 2021 Tongshuang Wu, Michael Terry, Carrie J. Cai

Although large language models (LLMs) have demonstrated impressive potential on simple tasks, their breadth of scope, lack of transparency, and insufficient controllability can make them less effective when assisting humans on more complex tasks.

Language Modelling Large Language Model

Program Synthesis with Large Language Models

1 code implementation16 Aug 2021 Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, Charles Sutton

Our largest models, even without finetuning on a code dataset, can synthesize solutions to 59. 6 percent of the problems from MBPP using few-shot learning with a well-designed prompt.

Few-Shot Learning Program Synthesis

Guided Integrated Gradients: An Adaptive Path Method for Removing Noise

1 code implementation CVPR 2021 Andrei Kapishnikov, Subhashini Venugopalan, Besim Avci, Ben Wedin, Michael Terry, Tolga Bolukbasi

To minimize the effect of this source of noise, we propose adapting the attribution path itself -- conditioning the path not just on the image but also on the model being explained.

Similar Image Search for Histopathology: SMILY

no code implementations30 Jan 2019 Narayan Hegde, Jason D. Hipp, Yun Liu, Michael E. Buck, Emily Reif, Daniel Smilkov, Michael Terry, Carrie J. Cai, Mahul B. Amin, Craig H. Mermel, Phil Q. Nelson, Lily H. Peng, Greg S. Corrado, Martin C. Stumpe

SMILY may be a useful general-purpose tool in the pathologist's arsenal, to improve the efficiency of searching large archives of histopathology images, without the need to develop and implement specific tools for each application.

Image Retrieval

AutoMOS: Learning a non-intrusive assessor of naturalness-of-speech

no code implementations28 Nov 2016 Brian Patton, Yannis Agiomyrgiannakis, Michael Terry, Kevin Wilson, Rif A. Saurous, D. Sculley

Developers of text-to-speech synthesizers (TTS) often make use of human raters to assess the quality of synthesized speech.

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