34 citations · 142 across the 32 of their papers we have counts for
9 papers · 1 filter
MnTTS2: An Open-Source Multi-Speaker Mongolian Text-to-Speech Synthesis Dataset
Kailin Liang, Bin Liu, Yifan Hu +3
Text-to-Speech (TTS) synthesis for low-resource languages is an attractive research issue in academia and industry nowadays. Mongolian is the official language of the Inner Mongoli…
Fine-Grained Selective Similarity Integration for Drug-Target Interaction Prediction
Bin Liu, Jin Wang, Kaiwei Sun +1
The discovery of drug-target interactions (DTIs) is a pivotal process in pharmaceutical development. Computational approaches are a promising and efficient alternative to tedious a…
A Theoretical Study on Solving Continual Learning
Gyuhak Kim, Changnan Xiao, Tatsuya Konishi +2
Continual learning (CL) learns a sequence of tasks incrementally. There are two popular CL settings, class incremental learning (CIL) and task incremental learning (TIL). A major c…
Continual Learning of Natural Language Processing Tasks: A Survey
Zixuan Ke, Bing Liu
Continual learning (CL) is a learning paradigm that emulates the human capability of learning and accumulating knowledge continually without forgetting the previously learned knowl…
Continual Training of Language Models for Few-Shot Learning
Zixuan Ke, Haowei Lin, Yijia Shao +3
Recent work on applying large language models (LMs) achieves impressive performance in many NLP applications. Adapting or posttraining an LM using an unlabeled domain corpus can pr…
Learnable Distribution Calibration for Few-Shot Class-Incremental Learning
Binghao Liu, Boyu Yang, Lingxi Xie +3
Few-shot class-incremental learning (FSCIL) faces challenges of memorizing old class distributions and estimating new class distributions given few training samples. In this study,…
A Multi-Head Model for Continual Learning via Out-of-Distribution Replay
Gyuhak Kim, Zixuan Ke, Bing Liu
This paper studies class incremental learning (CIL) of continual learning (CL). Many approaches have been proposed to deal with catastrophic forgetting (CF) in CIL. Most methods in…
Open-set Recognition via Augmentation-based Similarity Learning
Sepideh Esmaeilpour, Lei Shu, Bing Liu
The primary assumption of conventional supervised learning or classification is that the test samples are drawn from the same distribution as the training samples, which is called…
Topological Lifshitz transition and one-dimensional Weyl mode in HfTe5
Wenbin Wu, Zeping Shi, Yuhan Du +11
Landau band crossings typically stem from the intra-band evolution of electronic states in magnetic fields and enhance the interaction effect in their vicinity. Here in the extreme…