activity
20202022
most citedDistilling Object Detectors via Decoupled Features

26 citations · 34 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2022

Zero-shot Cross-lingual Conversational Semantic Role Labeling

Han Wu, Haochen Tan, Kun Xu +3

While conversational semantic role labeling (CSRL) has shown its usefulness on Chinese conversational tasks, it is still under-explored in non-Chinese languages due to the lack of…

cs.CL20225 cited

A Sentence is Worth 128 Pseudo Tokens: A Semantic-Aware Contrastive Learning Framework for Sentence Embeddings

Haochen Tan, Wei Shao, Han Wu +2

Contrastive learning has shown great potential in unsupervised sentence embedding tasks, e.g., SimCSE. However, We find that these existing solutions are heavily affected by superf…

cs.CL2021

CSAGN: Conversational Structure Aware Graph Network for Conversational Semantic Role Labeling

Han Wu, Kun Xu, Linqi Song

Conversational semantic role labeling (CSRL) is believed to be a crucial step towards dialogue understanding. However, it remains a major challenge for existing CSRL parser to hand…

cs.CL20212 cited

Domain-Adaptive Pretraining Methods for Dialogue Understanding

Han Wu, Kun Xu, Linfeng Song +3

Language models like BERT and SpanBERT pretrained on open-domain data have obtained impressive gains on various NLP tasks. In this paper, we probe the effectiveness of domain-adapt…

cs.CL2021

Conversational Semantic Role Labeling

Kun Xu, Han Wu, Linfeng Song +3

Semantic role labeling (SRL) aims to extract the arguments for each predicate in an input sentence. Traditional SRL can fail to analyze dialogues because it only works on every sin…

cs.CV202126 cited

Distilling Object Detectors via Decoupled Features

Jianyuan Guo, Kai Han, Yunhe Wang +4

Knowledge distillation is a widely used paradigm for inheriting information from a complicated teacher network to a compact student network and maintaining the strong performance.…