activity
20222024
most citedTraining language models to follow instructions with human feedback

4.3k citations · 4.4k across the 10 of their papers we have counts for

collaborators

10 papers

cs.RO20243 cited

Learning Human-to-Humanoid Real-Time Whole-Body Teleoperation

Tairan He, Zhengyi Luo, Wenli Xiao +4

We present Human to Humanoid (H2O), a reinforcement learning (RL) based framework that enables real-time whole-body teleoperation of a full-sized humanoid robot with only an RGB ca…

cs.CL20231 cited

Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path Prediction

Chong Zhang, Ya Guo, Yi Tu +5

Recent advances in multimodal pre-trained models have significantly improved information extraction from visually-rich documents (VrDs), in which named entity recognition (NER) is…

cs.SD2023

Are Soft Prompts Good Zero-shot Learners for Speech Recognition?

Dianwen Ng, Chong Zhang, Ruixi Zhang +7

Large self-supervised pre-trained speech models require computationally expensive fine-tuning for downstream tasks. Soft prompt tuning offers a simple parameter-efficient alternati…

cs.CL20233 cited

HiTIN: Hierarchy-aware Tree Isomorphism Network for Hierarchical Text Classification

He Zhu, Chong Zhang, Junjie Huang +2

Hierarchical text classification (HTC) is a challenging subtask of multi-label classification as the labels form a complex hierarchical structure. Existing dual-encoder methods in…

cs.SD2023

ACA-Net: Towards Lightweight Speaker Verification using Asymmetric Cross Attention

Jia Qi Yip, Tuan Truong, Dianwen Ng +7

In this paper, we propose ACA-Net, a lightweight, global context-aware speaker embedding extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetri…

cs.SD20231 cited

Contrastive Speech Mixup for Low-resource Keyword Spotting

Dianwen Ng, Ruixi Zhang, Jia Qi Yip +6

Most of the existing neural-based models for keyword spotting (KWS) in smart devices require thousands of training samples to learn a decent audio representation. However, with the…