activity
20182024
most citedDialog State Tracking: A Neural Reading Comprehension Approach

23 citations · 129 across the 20 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CL2023

Mitigating Bias for Question Answering Models by Tracking Bias Influence

Mingyu Derek Ma, Jiun-Yu Kao, Arpit Gupta +6

Models of various NLP tasks have been shown to exhibit stereotypes, and the bias in the question answering (QA) models is especially harmful as the output answers might be directly…

cs.CL2023

DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models

Sidi Lu, Wenbo Zhao, Chenyang Tao +4

NeurAlly-Decomposed Oracle (NADO) is a powerful approach for controllable generation with large language models. It is designed to avoid catastrophic forgetting while achieving gua…

cs.AI2023

Unsupervised Melody-Guided Lyrics Generation

Yufei Tian, Anjali Narayan-Chen, Shereen Oraby +7

Automatic song writing is a topic of significant practical interest. However, its research is largely hindered by the lack of training data due to copyright concerns and challenged…

cs.CL2023

Unsupervised Melody-to-Lyric Generation

Yufei Tian, Anjali Narayan-Chen, Shereen Oraby +8

Automatic melody-to-lyric generation is a task in which song lyrics are generated to go with a given melody. It is of significant practical interest and more challenging than uncon…

cs.CL2023★ 1 cited

Parameter-Efficient Low-Resource Dialogue State Tracking by Prompt Tuning

Mingyu Derek Ma, Jiun-Yu Kao, Shuyang Gao +4

Dialogue state tracking (DST) is an important step in dialogue management to keep track of users' beliefs. Existing works fine-tune all language model (LM) parameters to tackle the…