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20192023
most citedLong Document Summarization with Top-down and Bottom-up Inference

5 citations · 24 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.LG20215 cited

Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification

Bo Pang, Ying Nian Wu

We propose a latent space energy-based prior model for text generation and classification. The model stands on a generator network that generates the text sequence based on a conti…

cs.LG2021

Generative Text Modeling through Short Run Inference

Bo Pang, Erik Nijkamp, Tian Han +1

Latent variable models for text, when trained successfully, accurately model the data distribution and capture global semantic and syntactic features of sentences. The prominent ap…

cs.LG20215 cited

Trajectory Prediction with Latent Belief Energy-Based Model

Bo Pang, Tianyang Zhao, Xu Xie +1

Human trajectory prediction is critical for autonomous platforms like self-driving cars or social robots. We present a latent belief energy-based model (LB-EBM) for diverse human t…

cs.LG2020

Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling

Bo Pang, Erik Nijkamp, Jiali Cui +2

This paper proposes a latent space energy-based prior model for semi-supervised learning. The model stands on a generator network that maps a latent vector to the observed example.…

cs.LG2020

Learning Latent Space Energy-Based Prior Model for Molecule Generation

Bo Pang, Tian Han, Ying Nian Wu

Deep generative models have recently been applied to molecule design. If the molecules are encoded in linear SMILES strings, modeling becomes convenient. However, models relying on…