14 citations · 39 across the 11 of their papers we have counts for
11 papers
From Synthetic to Native: Benchmarking Multilingual Intent Classification in Logistics Customer Service
Haoyu He, Jinyu Zhuang, Haoran Chu +5
Multilingual intent classification is central to customer-service systems on global logistics platforms, where models must process noisy user queries across languages and hierarchi…
Orion-14B: Open-source Multilingual Large Language Models
Du Chen, Yi Huang, Xiaopu Li +7
In this study, we introduce Orion-14B, a collection of multilingual large language models with 14 billion parameters. We utilize a data scheduling approach to train a foundational…
A Hybrid Task-Oriented Dialog System with Domain and Task Adaptive Pretraining
Boliang Zhang, Ying Lyu, Ning Ding +4
This paper describes our submission for the End-to-end Multi-domain Task Completion Dialog shared task at the 9th Dialog System Technology Challenge (DSTC-9). Participants in the s…
Speech SIMCLR: Combining Contrastive and Reconstruction Objective for Self-supervised Speech Representation Learning
Dongwei Jiang, Wubo Li, Miao Cao +2
Self-supervised visual pretraining has shown significant progress recently. Among those methods, SimCLR greatly advanced the state of the art in self-supervised and semi-supervised…
DiDiSpeech: A Large Scale Mandarin Speech Corpus
Tingwei Guo, Cheng Wen, Dongwei Jiang +8
This paper introduces a new open-sourced Mandarin speech corpus, called DiDiSpeech. It consists of about 800 hours of speech data at 48kHz sampling rate from 6000 speakers and the…
Adversarial Multi-Binary Neural Network for Multi-class Classification
Haiyang Xu, Junwen Chen, Kun Han +1
Multi-class text classification is one of the key problems in machine learning and natural language processing. Emerging neural networks deal with the problem using a multi-output…
Learning Syntactic and Dynamic Selective Encoding for Document Summarization
Haiyang Xu, Yahao He, Kun Han +2
Text summarization aims to generate a headline or a short summary consisting of the major information of the source text. Recent studies employ the sequence-to-sequence framework t…
Selective Attention Encoders by Syntactic Graph Convolutional Networks for Document Summarization
Haiyang Xu, Yun Wang, Kun Han +3
Abstractive text summarization is a challenging task, and one need to design a mechanism to effectively extract salient information from the source text and then generate a summary…
Learning Alignment for Multimodal Emotion Recognition from Speech
Haiyang Xu, Hui Zhang, Kun Han +3
Speech emotion recognition is a challenging problem because human convey emotions in subtle and complex ways. For emotion recognition on human speech, one can either extract emotio…
DELTA: A DEep learning based Language Technology plAtform
Kun Han, Junwen Chen, Hui Zhang +20
In this paper we present DELTA, a deep learning based language technology platform. DELTA is an end-to-end platform designed to solve industry level natural language and speech pro…
Collaborative Multi-modal deep learning for the personalized product retrieval in Facebook Marketplace
Lu Zheng, Zhao Tan, Kun Han +1
Facebook Marketplace is quickly gaining momentum among consumers as a favored customer-to-customer (C2C) product trading platform. The recommendation system behind it helps to sign…