Musashi Hinck

According to our database, Musashi Hinck authored at least 9 papers between 2023 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Steering Large Language Models to Evaluate and Amplify Creativity.

Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Shao-Yen Tseng, Vasudev Lal

CoRR, 2024

Debias your Large Multi-Modal Model at Test-Time with Non-Contrastive Visual Attribute Steering.

Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Estelle Aflalo, Shao-Yen Tseng, Vasudev Lal, Phillip Howard

CoRR, 2024

Debiasing Large Vision-Language Models by Ablating Protected Attribute Representations.

Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Shao-Yen Tseng, Vasudev Lal, Phillip Howard

CoRR, 2024

ClimDetect: A Benchmark Dataset for Climate Change Detection and Attribution.

Sungduk Yu, Brian L. White, Anahita Bhiwandiwalla, Musashi Hinck, Matthew Lyle Olson, Tung Nguyen, Vasudev Lal

CoRR, 2024

LLaVA-Gemma: Accelerating Multimodal Foundation Models with a Compact Language Model.

Musashi Hinck, Matthew L. Olson, David Cobbley, Shao-Yen Tseng, Vasudev Lal

CoRR, 2024

AutoPersuade: A Framework for Evaluating and Explaining Persuasive Arguments.

Till Saenger, Musashi Hinck, Justin Grimmer, Brandon M. Stewart

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Why do LLaVA Vision-Language Models Reply to Images in English?

Musashi Hinck, Carolin Holtermann, Matthew L. Olson, Florian Schneider, Sungduk Yu, Anahita Bhiwandiwalla, Anne Lauscher, Shao-Yen Tseng, Vasudev Lal

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models.

Paul Röttger, Valentin Hofmann, Valentina Pyatkin, Musashi Hinck, Hannah Kirk, Hinrich Schütze, Dirk Hovy

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models.

Naoki Egami, Musashi Hinck, Brandon M. Stewart, Hanying Wei

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023