85 citations · 446 across the 40 of their papers we have counts for
40 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…
Discrete Conditional Diffusion for Reranking in Recommendation
Xiao Lin, Xiaokai Chen, Chenyang Wang +4
Reranking plays a crucial role in modern multi-stage recommender systems by rearranging the initial ranking list to model interplay between items. Considering the inherent challeng…
Tree based Progressive Regression Model for Watch-Time Prediction in Short-video Recommendation
Xiao Lin, Xiaokai Chen, Linfeng Song +3
An accurate prediction of watch time has been of vital importance to enhance user engagement in video recommender systems. To achieve this, there are four properties that a watch t…
A Survey on Zero Pronoun Translation
Longyue Wang, Siyou Liu, Mingzhou Xu +3
Zero pronouns (ZPs) are frequently omitted in pro-drop languages (e.g. Chinese, Hungarian, and Hindi), but should be recalled in non-pro-drop languages (e.g. English). This phenome…
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…
Getting the Most out of Simile Recognition
Xiaoyue Wang, Linfeng Song, Xin Liu +2
Simile recognition involves two subtasks: simile sentence classification that discriminates whether a sentence contains simile, and simile component extraction that locates the cor…
Discover, Explanation, Improvement: An Automatic Slice Detection Framework for Natural Language Processing
Wenyue Hua, Lifeng Jin, Linfeng Song +3
Pretrained natural language processing (NLP) models have achieved high overall performance, but they still make systematic errors. Instead of manual error analysis, research on sli…
Cross-domain Generalization for AMR Parsing
Xuefeng Bai, Seng Yang, Leyang Cui +2
Abstract Meaning Representation (AMR) parsing aims to predict an AMR graph from textual input. Recently, there has been notable growth in AMR parsing performance. However, most exi…
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…
Augmenting Multi-Turn Text-to-SQL Datasets with Self-Play
Qi Liu, Zihuiwen Ye, Tao Yu +2
The task of context-dependent text-to-SQL aims to convert multi-turn user utterances to formal SQL queries. This is a challenging task due to both the scarcity of training data fro…
Semantic-based Pre-training for Dialogue Understanding
Xuefeng Bai, Linfeng Song, Yue Zhang
Pre-trained language models have made great progress on dialogue tasks. However, these models are typically trained on surface dialogue text, thus are proven to be weak in understa…
Hierarchical Context Tagging for Utterance Rewriting
Lisa Jin, Linfeng Song, Lifeng Jin +2
Utterance rewriting aims to recover coreferences and omitted information from the latest turn of a multi-turn dialogue. Recently, methods that tag rather than linearly generate seq…
An Empirical Study of Retrieval-enhanced Graph Neural Networks
Dingmin Wang, Shengchao Liu, Hanchen Wang +5
Graph Neural Networks (GNNs) are effective tools for graph representation learning. Most GNNs rely on a recursive neighborhood aggregation scheme, named message passing, thereby th…
Enhanced Aspect-Based Sentiment Analysis Models with Progressive Self-supervised Attention Learning
Jinsong Su, Jialong Tang, Hui Jiang +6
In aspect-based sentiment analysis (ABSA), many neural models are equipped with an attention mechanism to quantify the contribution of each context word to sentiment prediction. Ho…
Structural Information Preserving for Graph-to-Text Generation
Linfeng Song, Ante Wang, Jinsong Su +4
The task of graph-to-text generation aims at producing sentences that preserve the meaning of input graphs. As a crucial defect, the current state-of-the-art models may mess up or…
TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis
Haisong Zhang, Lemao Liu, Haiyun Jiang +14
This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities. Com…
Robust Dialogue Utterance Rewriting as Sequence Tagging
Jie Hao, Linfeng Song, Liwei Wang +3
The task of dialogue rewriting aims to reconstruct the latest dialogue utterance by copying the missing content from the dialogue context. Until now, the existing models for this t…
Online Back-Parsing for AMR-to-Text Generation
Xuefeng Bai, Linfeng Song, Yue Zhang
AMR-to-text generation aims to recover a text containing the same meaning as an input AMR graph. Current research develops increasingly powerful graph encoders to better represent…
Semantic Role Labeling Guided Multi-turn Dialogue ReWriter
Kun Xu, Haochen Tan, Linfeng Song +4
For multi-turn dialogue rewriting, the capacity of effectively modeling the linguistic knowledge in dialog context and getting rid of the noises is essential to improve its perform…
Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment
Kun Xu, Linfeng Song, Yansong Feng +2
Existing entity alignment methods mainly vary on the choices of encoding the knowledge graph, but they typically use the same decoding method, which independently chooses the local…
Neural Simile Recognition with Cyclic Multitask Learning and Local Attention
Jiali Zeng, Linfeng Song, Jinsong Su +3
Simile recognition is to detect simile sentences and to extract simile components, i.e., tenors and vehicles. It involves two subtasks: {\it simile sentence classification} and {\i…
Graph-based Neural Sentence Ordering
Yongjing Yin, Linfeng Song, Jinsong Su +3
Sentence ordering is to restore the original paragraph from a set of sentences. It involves capturing global dependencies among sentences regardless of their input order. In this p…
Leveraging Dependency Forest for Neural Medical Relation Extraction
Linfeng Song, Yue Zhang, Daniel Gildea +3
Medical relation extraction discovers relations between entity mentions in text, such as research articles. For this task, dependency syntax has been recognized as a crucial source…
Multi-Granular Text Encoding for Self-Explaining Categorization
Zhiguo Wang, Yue Zhang, Mo Yu +5
Self-explaining text categorization requires a classifier to make a prediction along with supporting evidence. A popular type of evidence is sub-sequences extracted from the input…