44 citations · 244 across the 30 of their papers we have counts for
30 papers
Deep Reinforcement Learning with Task-Adaptive Retrieval via Hypernetwork
Yonggang Jin, Chenxu Wang, Tianyu Zheng +5
Deep reinforcement learning algorithms are usually impeded by sampling inefficiency, heavily depending on multiple interactions with the environment to acquire accurate decision-ma…
HUB: Guiding Learned Optimizers with Continuous Prompt Tuning
Gaole Dai, Wei Wu, Ziyu Wang +3
Learned optimizers are a crucial component of meta-learning. Recent advancements in scalable learned optimizers have demonstrated their superior performance over hand-designed opti…
Prompt as Triggers for Backdoor Attack: Examining the Vulnerability in Language Models
Shuai Zhao, Jinming Wen, Luu Anh Tuan +2
The prompt-based learning paradigm, which bridges the gap between pre-training and fine-tuning, achieves state-of-the-art performance on several NLP tasks, particularly in few-shot…
Chinese Open Instruction Generalist: A Preliminary Release
Ge Zhang, Yemin Shi, Ruibo Liu +9
Instruction tuning is widely recognized as a key technique for building generalist language models, which has attracted the attention of researchers and the public with the release…
Modular Retrieval for Generalization and Interpretation
Juhao Liang, Chen Zhang, Zhengyang Tang +3
New retrieval tasks have always been emerging, thus urging the development of new retrieval models. However, instantiating a retrieval model for each new retrieval task is resource…
A Pathway Towards Responsible AI Generated Content
Chen Chen, Jie Fu, Lingjuan Lyu
AI Generated Content (AIGC) has received tremendous attention within the past few years, with content generated in the format of image, text, audio, video, etc. Meanwhile, AIGC has…
A Close Look at Spatial Modeling: From Attention to Convolution
Xu Ma, Huan Wang, Can Qin +4
Vision Transformers have shown great promise recently for many vision tasks due to the insightful architecture design and attention mechanism. By revisiting the self-attention resp…
SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing
Jie Fu, Zhili Chen, XinPeng Ling
Differential privacy (DP) provides a formal privacy guarantee that prevents adversaries with access to machine learning models from extracting information about individual training…
MAP-Music2Vec: A Simple and Effective Baseline for Self-Supervised Music Audio Representation Learning
Yizhi Li, Ruibin Yuan, Ge Zhang +11
The deep learning community has witnessed an exponentially growing interest in self-supervised learning (SSL). However, it still remains unexplored how to build a framework for lea…
1Cademy @ Causal News Corpus 2022: Enhance Causal Span Detection via Beam-Search-based Position Selector
Xingran Chen, Ge Zhang, Adam Nik +2
In this paper, we present our approach and empirical observations for Cause-Effect Signal Span Detection -- Subtask 2 of Shared task 3~\cite{tan-etal-2022-event} at CASE 2022. The…
Text Editing as Imitation Game
Ning Shi, Bin Tang, Bo Yuan +4
Text editing, such as grammatical error correction, arises naturally from imperfect textual data. Recent works frame text editing as a multi-round sequence tagging task, where oper…
Towards Representation Identical Privacy-Preserving Graph Neural Network via Split Learning
Chuanqiang Shan, Huiyun Jiao, Jie Fu
In recent years, the fast rise in number of studies on graph neural network (GNN) has put it from the theories research to reality application stage. Despite the encouraging perfor…
Learning Contact-aware CPG-based Locomotion in a Soft Snake Robot
Xuan Liu, Cagdas Onal, Jie Fu
In this paper, we present a model-free learning-based control scheme for the soft snake robot to improve its contact-aware locomotion performance in a cluttered environment. The co…
Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with Parameters
Aston Zhang, Yi Tay, Shuai Zhang +4
Recent works have demonstrated reasonable success of representation learning in hypercomplex space. Specifically, "fully-connected layers with Quaternions" (4D hypercomplex numbers…
Semantic SLAM with Autonomous Object-Level Data Association
Zhentian Qian, Kartik Patath, Jie Fu +1
It is often desirable to capture and map semantic information of an environment during simultaneous localization and mapping (SLAM). Such semantic information can enable a robot to…
GLGE: A New General Language Generation Evaluation Benchmark
Dayiheng Liu, Yu Yan, Yeyun Gong +15
Multi-task benchmarks such as GLUE and SuperGLUE have driven great progress of pretraining and transfer learning in Natural Language Processing (NLP). These benchmarks mostly focus…
Tell Me How to Ask Again: Question Data Augmentation with Controllable Rewriting in Continuous Space
Dayiheng Liu, Yeyun Gong, Jie Fu +5
In this paper, we propose a novel data augmentation method, referred to as Controllable Rewriting based Question Data Augmentation (CRQDA), for machine reading comprehension (MRC),…
CoCon: A Self-Supervised Approach for Controlled Text Generation
Alvin Chan, Yew-Soon Ong, Bill Pung +2
Pretrained Transformer-based language models (LMs) display remarkable natural language generation capabilities. With their immense potential, controlling text generation of such LM…
RikiNet: Reading Wikipedia Pages for Natural Question Answering
Dayiheng Liu, Yeyun Gong, Jie Fu +5
Reading long documents to answer open-domain questions remains challenging in natural language understanding. In this paper, we introduce a new model, called RikiNet, which reads W…
Role-Wise Data Augmentation for Knowledge Distillation
Jie Fu, Xue Geng, Zhijian Duan +6
Knowledge Distillation (KD) is a common method for transferring the ``knowledge'' learned by one machine learning model (the \textit{teacher}) into another model (the \textit{stude…
Diverse, Controllable, and Keyphrase-Aware: A Corpus and Method for News Multi-Headline Generation
Dayiheng Liu, Yeyun Gong, Jie Fu +6
News headline generation aims to produce a short sentence to attract readers to read the news. One news article often contains multiple keyphrases that are of interest to different…
Learning to Locomote with Deep Neural-Network and CPG-based Control in a Soft Snake Robot
Xuan Liu, Renato Gasoto, Cagdas Onal +1
In this paper, we present a new locomotion control method for soft robot snakes. Inspired by biological snakes, our control architecture is composed of two key modules: A deep rein…
Jacobian Adversarially Regularized Networks for Robustness
Alvin Chan, Yi Tay, Yew Soon Ong +1
Adversarial examples are crafted with imperceptible perturbations with the intent to fool neural networks. Against such attacks, adversarial training and its variants stand as the…
Learning Sparse Mixture of Experts for Visual Question Answering
Vardaan Pahuja, Jie Fu, Christopher J. Pal
There has been a rapid progress in the task of Visual Question Answering with improved model architectures. Unfortunately, these models are usually computationally intensive due to…