activity
20162022
most citedA Systematic Characterization of Sampling Algorithms for Open-ended Language Generation

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

collaborators

13 papers

cs.CL2022

PCFG-based Natural Language Interface Improves Generalization for Controlled Text Generation

Jingyu Zhang, James Glass, Tianxing He

Existing work on controlled text generation (CTG) assumes a control interface of categorical attributes. In this work, we propose a natural language (NL) interface, where we craft…

cs.AI2022

Controlling the Focus of Pretrained Language Generation Models

Jiabao Ji, Yoon Kim, James Glass +1

The finetuning of pretrained transformer-based language generation models are typically conducted in an end-to-end manner, where the model learns to attend to relevant parts of the…

cs.LG20217 cited

Revisiting Latent-Space Interpolation via a Quantitative Evaluation Framework

Lu Mi, Tianxing He, Core Francisco Park +3

Latent-space interpolation is commonly used to demonstrate the generalization ability of deep latent variable models. Various algorithms have been proposed to calculate the best tr…

cs.AI20215 cited

An Empirical Study on Few-shot Knowledge Probing for Pretrained Language Models

Tianxing He, Kyunghyun Cho, James Glass

Prompt-based knowledge probing for 1-hop relations has been used to measure how much world knowledge is stored in pretrained language models. Existing work uses considerable amount…

cs.CL20212 cited

Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models

Tianxing He, Bryan McCann, Caiming Xiong +1

In this work, we explore joint energy-based model (EBM) training during the finetuning of pretrained text encoders (e.g., Roberta) for natural language understanding (NLU) tasks. O…

cs.CL20208 cited

A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation

Moin Nadeem, Tianxing He, Kyunghyun Cho +1

This work studies the widely adopted ancestral sampling algorithms for auto-regressive language models, which is not widely studied in the literature. We use the quality-diversity…