34 citations · 142 across the 32 of their papers we have counts for
17 papers · 1 filter
Emotion-Aware Prosodic Phrasing for Expressive Text-to-Speech
Rui Liu, Bin Liu, Haizhou Li
Prosodic phrasing is crucial to the naturalness and intelligibility of end-to-end Text-to-Speech (TTS). There exist both linguistic and emotional prosody in natural speech. As the…
Data Generation-based Operator Learning for Solving Partial Differential Equations on Unbounded Domains
Jihong Wang, Xin Wang, Jing Li +1
Wave propagation problems are typically formulated as partial differential equations (PDEs) on unbounded domains to be solved. The classical approach to solving such problems invol…
Proton-Boron Fusion Yield Increased by Orders of Magnitude with Foam Targets
Wen-Qing Wei, Shi-Zheng Zhang, Zhi-Gang Deng +35
A novel intense beam-driven scheme for high yield of the tri-alpha reaction 11B(p,α)2α was investigated. We used a foam target made of cellulose triacetate (TAC, C_9H_{16}O_8) dope…
Video Captioning with Aggregated Features Based on Dual Graphs and Gated Fusion
Yutao Jin, Bin Liu, Jing Wang
The application of video captioning models aims at translating the content of videos by using accurate natural language. Due to the complex nature inbetween object interaction in t…
Debiased Pairwise Learning from Positive-Unlabeled Implicit Feedback
Bin Liu, Qin Luo, Bang Wang
Learning contrastive representations from pairwise comparisons has achieved remarkable success in various fields, such as natural language processing, computer vision, and informat…
Class-Incremental Learning based on Label Generation
Yijia Shao, Yiduo Guo, Dongyan Zhao +1
Despite the great success of pre-trained language models, it is still a challenge to use these models for continual learning, especially for the class-incremental learning (CIL) se…
Parameter-Level Soft-Masking for Continual Learning
Tatsuya Konishi, Mori Kurokawa, Chihiro Ono +3
Existing research on task incremental learning in continual learning has primarily focused on preventing catastrophic forgetting (CF). Although several techniques have achieved lea…
Open-loop and closed-loop solvabilities for discrete-time mean-field stochastic linear quadratic optimal control problems
Teng Song, Bin Liu
This paper discusses the discrete-time mean-field stochastic linear quadratic optimal control problems, whose weighting matrices in the cost functional are not assumed to be defini…
Learnability and Algorithm for Continual Learning
Gyuhak Kim, Changnan Xiao, Tatsuya Konishi +1
This paper studies the challenging continual learning (CL) setting of Class Incremental Learning (CIL). CIL learns a sequence of tasks consisting of disjoint sets of concepts or cl…
Enabling Intelligent Interactions between an Agent and an LLM: A Reinforcement Learning Approach
Bin Hu, Chenyang Zhao, Pu Zhang +4
Large language models (LLMs) encode a vast amount of world knowledge acquired from massive text datasets. Recent studies have demonstrated that LLMs can assist an embodied agent in…
Analyzing and Reducing the Performance Gap in Cross-Lingual Transfer with Fine-tuning Slow and Fast
Yiduo Guo, Yaobo Liang, Dongyan Zhao +2
Existing research has shown that a multilingual pre-trained language model fine-tuned with one (source) language also performs well on downstream tasks for non-source languages, ev…
A Unified Evaluation Framework for Novelty Detection and Accommodation in NLP with an Instantiation in Authorship Attribution
Neeraj Varshney, Himanshu Gupta, Eric Robertson +2
State-of-the-art natural language processing models have been shown to achieve remarkable performance in 'closed-world' settings where all the labels in the evaluation set are know…
Open-World Continual Learning: Unifying Novelty Detection and Continual Learning
Gyuhak Kim, Changnan Xiao, Tatsuya Konishi +2
As AI agents are increasingly used in the real open world with unknowns or novelties, they need the ability to (1) recognize objects that (a) they have learned before and (b) detec…
Grab What You Need: Rethinking Complex Table Structure Recognition with Flexible Components Deliberation
Hao Liu, Xin Li, Mingming Gong +5
Recently, Table Structure Recognition (TSR) task, aiming at identifying table structure into machine readable formats, has received increasing interest in the community. While impr…
Three-dimensional real Chern insulator in bulk -graphyne
Xu-Tao Zeng, Bin-Bin Liu, Fan Yang +4
The real Chern insulator state, featuring nontrivial real Chern number and second-order boundary modes, has been revealed in a few two-dimensional systems. The concept can be exten…
Continual Pre-training of Language Models
Zixuan Ke, Yijia Shao, Haowei Lin +3
Language models (LMs) have been instrumental for the rapid advance of natural language processing. This paper studies continual pre-training of LMs, in particular, continual domain…
Adapting a Language Model While Preserving its General Knowledge
Zixuan Ke, Yijia Shao, Haowei Lin +3
Domain-adaptive pre-training (or DA-training for short), also known as post-training, aims to train a pre-trained general-purpose language model (LM) using an unlabeled corpus of a…