26 citations · 66 across the 11 of their papers we have counts for
20 papers
Latent Action Pretraining from Videos
Seonghyeon Ye, Joel Jang, Byeongguk Jeon +13
We introduce Latent Action Pretraining for general Action models (LAPA), an unsupervised method for pretraining Vision-Language-Action (VLA) models without ground-truth robot actio…
Reflect, Not Reflex: Inference-Based Common Ground Improves Dialogue Response Quality
Pei Zhou, Hyundong Cho, Pegah Jandaghi +4
Human communication relies on common ground (CG), the mutual knowledge and beliefs shared by participants, to produce coherent and interesting conversations. In this paper, we demo…
On Continual Model Refinement in Out-of-Distribution Data Streams
Bill Yuchen Lin, Sida Wang, Xi Victoria Lin +4
Real-world natural language processing (NLP) models need to be continually updated to fix the prediction errors in out-of-distribution (OOD) data streams while overcoming catastrop…
RockNER: A Simple Method to Create Adversarial Examples for Evaluating the Robustness of Named Entity Recognition Models
Bill Yuchen Lin, Wenyang Gao, Jun Yan +2
To audit the robustness of named entity recognition (NER) models, we propose RockNER, a simple yet effective method to create natural adversarial examples. Specifically, at the ent…
Common Sense Beyond English: Evaluating and Improving Multilingual Language Models for Commonsense Reasoning
Bill Yuchen Lin, Seyeon Lee, Xiaoyang Qiao +1
Commonsense reasoning research has so far been limited to English. We aim to evaluate and improve popular multilingual language models (ML-LMs) to help advance commonsense reasonin…
Probing Commonsense Explanation in Dialogue Response Generation
Pei Zhou, Pegah Jandaghi, Bill Yuchen Lin +3
Humans use commonsense reasoning (CSR) implicitly to produce natural and coherent responses in conversations. Aiming to close the gap between current response generation (RG) model…