1.2k citations · 9.1k across the 205 of their papers we have counts for
205 papers
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance
Yuchen Fang, Zhenggang Tang, Kan Ren +7
Order execution is a fundamental task in quantitative finance, aiming at finishing acquisition or liquidation for a number of trading orders of the specific assets. Recent advance…
Extract and Attend: Improving Entity Translation in Neural Machine Translation
Zixin Zeng, Rui Wang, Yichong Leng +4
While Neural Machine Translation(NMT) has achieved great progress in recent years, it still suffers from inaccurate translation of entities (e.g., person/organization name, locatio…
MolXPT: Wrapping Molecules with Text for Generative Pre-training
Zequn Liu, Wei Zhang, Yingce Xia +5
Generative pre-trained Transformer (GPT) has demonstrates its great success in natural language processing and related techniques have been adapted into molecular modeling. Conside…
De Novo Molecular Generation via Connection-aware Motif Mining
Zijie Geng, Shufang Xie, Yingce Xia +6
De novo molecular generation is an essential task for science discovery. Recently, fragment-based deep generative models have attracted much research attention due to their flexibi…
Regeneration Learning: A Learning Paradigm for Data Generation
Xu Tan, Tao Qin, Jiang Bian +2
Machine learning methods for conditional data generation usually build a mapping from source conditional data X to target data Y. The target Y (e.g., text, speech, music, image, vi…
Retrosynthetic Planning with Dual Value Networks
Guoqing Liu, Di Xue, Shufang Xie +7
Retrosynthesis, which aims to find a route to synthesize a target molecule from commercially available starting materials, is a critical task in drug discovery and materials design…
An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context
Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng +8
One of the key challenges in deploying RL to real-world applications is to adapt to variations of unknown environment contexts, such as changing terrains in robotic tasks and fluct…
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
Yuanying Cai, Chuheng Zhang, Li Zhao +6
We consider an offline reinforcement learning (RL) setting where the agent need to learn from a dataset collected by rolling out multiple behavior policies. There are two challenge…
SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition
Yichong Leng, Xu Tan, Wenjie Liu +6
Error correction in automatic speech recognition (ASR) aims to correct those incorrect words in sentences generated by ASR models. Since recent ASR models usually have low word err…
Incorporating Pre-training Paradigm for Antibody Sequence-Structure Co-design
Kaiyuan Gao, Lijun Wu, Jinhua Zhu +8
Antibodies are versatile proteins that can bind to pathogens and provide effective protection for human body. Recently, deep learning-based computational antibody design has attrac…
Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation
Botao Yu, Peiling Lu, Rui Wang +6
Symbolic music generation aims to generate music scores automatically. A recent trend is to use Transformer or its variants in music generation, which is, however, suboptimal, beca…
BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining
Renqian Luo, Liai Sun, Yingce Xia +4
Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Among the two main…
MeloForm: Generating Melody with Musical Form based on Expert Systems and Neural Networks
Peiling Lu, Xu Tan, Botao Yu +3
Human usually composes music by organizing elements according to the musical form to express music ideas. However, for neural network-based music generation, it is difficult to do…
Re-creation of Creations: A New Paradigm for Lyric-to-Melody Generation
Ang Lv, Xu Tan, Tao Qin +2
Lyric-to-melody generation is an important task in songwriting, and is also quite challenging due to its unique characteristics: the generated melodies should not only follow good…
Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation
Guoqing Liu, Mengzhang Cai, Li Zhao +4
Deep reinforcement learning (DRL) has attracted much attention in automated game testing. Early attempts rely on game internal information for game space exploration, thus requirin…
Unified 2D and 3D Pre-Training of Molecular Representations
Jinhua Zhu, Yingce Xia, Lijun Wu +5
Molecular representation learning has attracted much attention recently. A molecule can be viewed as a 2D graph with nodes/atoms connected by edges/bonds, and can also be represent…
ReLyMe: Improving Lyric-to-Melody Generation by Incorporating Lyric-Melody Relationships
Chen Zhang, Luchin Chang, Songruoyao Wu +4
Lyric-to-melody generation, which generates melody according to given lyrics, is one of the most important automatic music composition tasks. With the rapid development of deep lea…
A Study of Syntactic Multi-Modality in Non-Autoregressive Machine Translation
Kexun Zhang, Rui Wang, Xu Tan +4
It is difficult for non-autoregressive translation (NAT) models to capture the multi-modal distribution of target translations due to their conditional independence assumption, whi…
Quantized Training of Gradient Boosting Decision Trees
Yu Shi, Guolin Ke, Zhuoming Chen +2
Recent years have witnessed significant success in Gradient Boosting Decision Trees (GBDT) for a wide range of machine learning applications. Generally, a consensus about GBDT's tr…
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
Da Yu, Gautam Kamath, Janardhan Kulkarni +3
Differentially private stochastic gradient descent (DP-SGD) is the workhorse algorithm for recent advances in private deep learning. It provides a single privacy guarantee to all d…
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
Xu Tan, Jiawei Chen, Haohe Liu +11
Text to speech (TTS) has made rapid progress in both academia and industry in recent years. Some questions naturally arise that whether a TTS system can achieve human-level quality…
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis
Yichong Leng, Zehua Chen, Junliang Guo +9
Binaural audio plays a significant role in constructing immersive augmented and virtual realities. As it is expensive to record binaural audio from the real world, synthesizing the…
Your Transformer May Not be as Powerful as You Expect
Shengjie Luo, Shanda Li, Shuxin Zheng +3
Relative Positional Encoding (RPE), which encodes the relative distance between any pair of tokens, is one of the most successful modifications to the original Transformer. As far…
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
Jiawei Huang, Li Zhao, Tao Qin +3
We propose a new learning framework that captures the tiered structure of many real-world user-interaction applications, where the users can be divided into two groups based on the…