243 citations · 298 across the 18 of their papers we have counts for
5 papers · 1 filter
Learning Probabilistic Models from Generator Latent Spaces with Hat EBM
Mitch Hill, Erik Nijkamp, Jonathan Mitchell +2
This work proposes a method for using any generator network as the foundation of an Energy-Based Model (EBM). Our formulation posits that observed images are the sum of unobserved…
BigIssue: A Realistic Bug Localization Benchmark
Paul Kassianik, Erik Nijkamp, Bo Pang +2
As machine learning tools progress, the inevitable question arises: How can machine learning help us write better code? With significant progress being achieved in natural language…
Latent Diffusion Energy-Based Model for Interpretable Text Modeling
Peiyu Yu, Sirui Xie, Xiaojian Ma +6
Latent space Energy-Based Models (EBMs), also known as energy-based priors, have drawn growing interests in generative modeling. Fueled by its flexibility in the formulation and st…
Long Document Summarization with Top-down and Bottom-up Inference
Bo Pang, Erik Nijkamp, Wojciech Kryściński +3
Text summarization aims to condense long documents and retain key information. Critical to the success of a summarization model is the faithful inference of latent representations…
CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
Erik Nijkamp, Bo Pang, Hiroaki Hayashi +5
Program synthesis strives to generate a computer program as a solution to a given problem specification, expressed with input-output examples or natural language descriptions. The…