Papers by Lavinia Dunagan
Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand (2022.naacl-main)
Copied to clipboard
Jungo Kasai, Keisuke Sakaguchi, Ronan Le Bras, Lavinia Dunagan, Jacob Morrison, Alexander Fabbri, Yejin Choi, Noah A. Smith
| Challenge: | Recent advances on models and metrics should benefit and inform each other, authors argue . bidimensional leaderboards allow for fast, accurate evaluation of language generation models . |
| Approach: | They propose a bidimensional leaderboard that tracks progress in language generation models and metrics for their evaluation. |
| Outcome: | The proposed leaderboards track progress in language generation models and metrics for their evaluation. |
Transparent Human Evaluation for Image Captioning (2022.naacl-main)
Copied to clipboard
Jungo Kasai, Keisuke Sakaguchi, Lavinia Dunagan, Jacob Morrison, Ronan Le Bras, Yejin Choi, Noah A. Smith
| Challenge: | Recent work has demonstrated that image captioning is a complex task that requires a large amount of human input. |
| Approach: | They develop a human evaluation protocol for image captioning models based on machine- and human-generated captions on the MSCOCO dataset. |
| Outcome: | The proposed model improves CLIPScore, a recent metric that uses image features, and improves human judgments because it is more sensitive to recall. |
You don’t need a personality test to know these models are unreliable: Assessing the Reliability of Large Language Models on Psychometric Instruments (2024.naacl-long)
Copied to clipboard
Bangzhao Shu, Lechen Zhang, Minje Choi, Lavinia Dunagan, Lajanugen Logeswaran, Moontae Lee, Dallas Card, David Jurgens
| Challenge: | Large Language Models (LLMs) are popular for research in social sciences . currently, prompting LLMs is insufficient to accurately and reliably capture model perceptions, and we discuss potential alternatives to improve this. |
| Approach: | They construct a dataset that contains 693 questions encompassing 39 different instruments of persona measurement on 115 persona axes and a set of questions containing minor variations. |
| Outcome: | The proposed model can generate answers and negate statements in a consistent and robust manner. |