179 citations · 462 across the 17 of their papers we have counts for
17 papers
Stabilizing RLHF through Advantage Model and Selective Rehearsal
Baolin Peng, Linfeng Song, Ye Tian +3
Large Language Models (LLMs) have revolutionized natural language processing, yet aligning these models with human values and preferences using RLHF remains a significant challenge…
Search-Engine-augmented Dialogue Response Generation with Cheaply Supervised Query Production
Ante Wang, Linfeng Song, Qi Liu +5
Knowledge-aided dialogue response generation aims at augmenting chatbots with relevant external knowledge in the hope of generating more informative responses. The majority of prev…
Friend-training: Learning from Models of Different but Related Tasks
Mian Zhang, Lifeng Jin, Linfeng Song +3
Current self-training methods such as standard self-training, co-training, tri-training, and others often focus on improving model performance on a single task, utilizing differenc…
Learning a Grammar Inducer from Massive Uncurated Instructional Videos
Songyang Zhang, Linfeng Song, Lifeng Jin +4
Video-aided grammar induction aims to leverage video information for finding more accurate syntactic grammars for accompanying text. While previous work focuses on building systems…
Towards Generalized Models for Task-oriented Dialogue Modeling on Spoken Conversations
Ruijie Yan, Shuang Peng, Haitao Mi +7
Building robust and general dialogue models for spoken conversations is challenging due to the gap in distributions of spoken and written data. This paper presents our approach to…
Fast-R2D2: A Pretrained Recursive Neural Network based on Pruned CKY for Grammar Induction and Text Representation
Xiang Hu, Haitao Mi, Liang Li +1
Recently CKY-based models show great potential in unsupervised grammar induction thanks to their human-like encoding paradigm, which runs recursively and hierarchically, but requir…
DP-FP: Differentially Private Forward Propagation for Large Models
Jian Du, Haitao Mi
When applied to large-scale learning problems, the conventional wisdom on privacy-preserving deep learning, known as Differential Private Stochastic Gradient Descent (DP-SGD), has…
A Dialogue-based Information Extraction System for Medical Insurance Assessment
Shuang Peng, Mengdi Zhou, Minghui Yang +6
In the Chinese medical insurance industry, the assessor's role is essential and requires significant efforts to converse with the claimant. This is a highly professional job that i…
R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling
Xiang Hu, Haitao Mi, Zujie Wen +4
Human language understanding operates at multiple levels of granularity (e.g., words, phrases, and sentences) with increasing levels of abstraction that can be hierarchically combi…
Multi-Perspective Context Matching for Machine Comprehension
Zhiguo Wang, Haitao Mi, Wael Hamza +1
Previous machine comprehension (MC) datasets are either too small to train end-to-end deep learning models, or not difficult enough to evaluate the ability of current MC techniques…
Temporal Attention Model for Neural Machine Translation
Baskaran Sankaran, Haitao Mi, Yaser Al-Onaizan +1
Attention-based Neural Machine Translation (NMT) models suffer from attention deficiency issues as has been observed in recent research. We propose a novel mechanism to address som…
Supervised Attentions for Neural Machine Translation
Haitao Mi, Zhiguo Wang, Abe Ittycheriah
In this paper, we improve the attention or alignment accuracy of neural machine translation by utilizing the alignments of training sentence pairs. We simply compute the distance b…
Sense Embedding Learning for Word Sense Induction
Linfeng Song, Zhiguo Wang, Haitao Mi +1
Conventional word sense induction (WSI) methods usually represent each instance with discrete linguistic features or cooccurrence features, and train a model for each polysemous wo…
Vocabulary Manipulation for Neural Machine Translation
Haitao Mi, Zhiguo Wang, Abe Ittycheriah
In order to capture rich language phenomena, neural machine translation models have to use a large vocabulary size, which requires high computing time and large memory usage. In th…
Coverage Embedding Models for Neural Machine Translation
Haitao Mi, Baskaran Sankaran, Zhiguo Wang +1
In this paper, we enhance the attention-based neural machine translation (NMT) by adding explicit coverage embedding models to alleviate issues of repeating and dropping translatio…
Sentence Similarity Learning by Lexical Decomposition and Composition
Zhiguo Wang, Haitao Mi, Abraham Ittycheriah
Most conventional sentence similarity methods only focus on similar parts of two input sentences, and simply ignore the dissimilar parts, which usually give us some clues and seman…
Semi-supervised Clustering for Short Text via Deep Representation Learning
Zhiguo Wang, Haitao Mi, Abraham Ittycheriah
In this work, we propose a semi-supervised method for short text clustering, where we represent texts as distributed vectors with neural networks, and use a small amount of labeled…