6 papers
SeqSAM: Autoregressive Multiple Hypothesis Prediction for Medical Image Segmentation using SAM
Benjamin Towle, Xin Chen, Ke Zhou
Pre-trained segmentation models are a powerful and flexible tool for segmenting images. Recently, this trend has extended to medical imaging. Yet, often these methods only produce…
Enhancing AI Assisted Writing with One-Shot Implicit Negative Feedback
Benjamin Towle, Ke Zhou
AI-mediated communication enables users to communicate more quickly and efficiently. Various systems have been proposed such as smart reply and AI-assisted writing. Yet, the hetero…
SimSAM: Zero-shot Medical Image Segmentation via Simulated Interaction
Benjamin Towle, Xin Chen, Ke Zhou
The recently released Segment Anything Model (SAM) has shown powerful zero-shot segmentation capabilities through a semi-automatic annotation setup in which the user can provide a…
End-to-End Autoregressive Retrieval via Bootstrapping for Smart Reply Systems
Benjamin Towle, Ke Zhou
Reply suggestion systems represent a staple component of many instant messaging and email systems. However, the requirement to produce sets of replies, rather than individual repli…
Model-Based Simulation for Optimising Smart Reply
Benjamin Towle, Ke Zhou
Smart Reply (SR) systems present a user with a set of replies, of which one can be selected in place of having to type out a response. To perform well at this task, a system should…
Learn What Is Possible, Then Choose What Is Best: Disentangling One-To-Many Relations in Language Through Text-based Games
Benjamin Towle, Ke Zhou
Language models pre-trained on large self-supervised corpora, followed by task-specific fine-tuning has become the dominant paradigm in NLP. These pre-training datasets often have…