14 accepted papers
The ability of zero-shot translation emerges when we train a multilingual model with certain translation directions; the model can then directly translate in unseen directions. Alternatively, zero-shot translation can be accomplished by pivoting through a third language (e.g., English). In our work,…
Online path planning for magnetic microrobots actuated by electromagnetic system in dynamic flow field presents significant challenges due to time-varying fluid dynamics, energy constraints, and collision risks. Traditional path planning approaches, which often rely on static flow assumptions or sim
Length-control summarization aims to condense long texts into a short one within a certain length limit. Previous approaches often use autoregressive (AR) models and treat the length requirement as a soft constraint, which may not always be satisfied. In this study, we propose a novel length-control…
The proliferation of social media platforms has given rise to the amount of online debates and arguments. Consequently, the need for automatic summarization methods for such debates is imperative, however this area of summarization is rather understudied. The Key Point Analysis (KPA) task formulates…
Recently, there has been considerable attention on detecting hallucinations and omissions in Machine Translation (MT) systems. The two dominant approaches to tackle this task involve analyzing the MT system’s internal states or relying on the output of external tools, such as sentence similarity or…
Magnetically actuated nanoparticle microrobots have great potential for biomedical applications, especially in blood vessels. However, they face a complex bifurcation environment, and magnetic control strategies targeting a single pathway limit the operational efficiency of the targeting task. In th
Endovascular techniques have been increasingly adapted to medical applications as a minimally-invasive treatment approach to diagnose and treat various vascular diseases. Guidewires are the basic devices in endovascular surgery. The conventional practice of endovascular procedures has a number of dr
Text summarization aims to generate a short summary for an input text. In this work, we propose a Non-Autoregressive Unsupervised Summarization (NAUS) approach, which does not require parallel data for training. Our NAUS first performs edit-based search towards a heuristically defined score, and gen…
How do we perform efficient inference while retaining high translation quality? Existing neural machine translation models, such as Transformer, achieve high performance, but they decode words one by one, which is inefficient. Recent non-autoregressive translation models speed up the inference, but…
It is a common belief that training deep transformers from scratch requires large datasets. Consequently, for small datasets, people usually use shallow and simple additional layers on top of pre-trained models during fine-tuning. This work shows that this does not always need to be the case: with p…
Multi-label emotion classification is an important task in NLP and is essential to many applications. In this work, we propose a sequence-to-emotion (Seq2Emo) approach, which implicitly models emotion correlations in a bi-directional decoder. Experiments on SemEval’18 and GoEmotions datasets show th…
Untethered, wirelessly controlled microrobots have a broad application prospect from industrial area, to the bioengineering due to their small scales. In a narrow environment containing viscous resistance and friction fluid, rigid body may damage the micro-objects that the microrobots manipulate. In
Deep Convolutional Neural Networks have been adopted for salient object detection and achieved the state-of-the-art performance. Most of the previous works however focus on region accuracy but not on the boundary quality. In this paper, we propose a predict-refine architecture, BASNet, and a new hyb…
Soft swimming microrobots that can be powered and guided remotely by magnetic field show greater potential for numerous applications than traditional rigid counterparts, due to their soft and flexible architectures. However, main challenges in closed-loop control remain to be overcome for the soft r