Search Results for author: Gongshen Liu

Found 15 papers, 5 papers with code

Improving Constituent Representation with Hypertree Neural Networks

no code implementations NAACL 2022 Hao Zhou, Gongshen Liu, Kewei Tu

Many natural language processing tasks involve text spans and thus high-quality span representations are needed to enhance neural approaches to these tasks.

A Multi-Task Dual-Tree Network for Aspect Sentiment Triplet Extraction

no code implementations COLING 2022 Yichun Zhao, Kui Meng, Gongshen Liu, Jintao Du, Huijia Zhu

Aspect Sentiment Triplet Extraction (ASTE) aims at extracting triplets from a given sentence, where each triplet includes an aspect, its sentiment polarity, and a corresponding opinion explaining the polarity.

Aspect Sentiment Triplet Extraction

UOR: Universal Backdoor Attacks on Pre-trained Language Models

no code implementations16 May 2023 Wei Du, Peixuan Li, Boqun Li, Haodong Zhao, Gongshen Liu

In this paper, we first summarize the requirements that a more threatening backdoor attack against PLMs should satisfy, and then propose a new backdoor attack method called UOR, which breaks the bottleneck of the previous approach by turning manual selection into automatic optimization.

Backdoor Attack Contrastive Learning +2

FedPrompt: Communication-Efficient and Privacy Preserving Prompt Tuning in Federated Learning

no code implementations25 Aug 2022 Haodong Zhao, Wei Du, Fangqi Li, Peixuan Li, Gongshen Liu

In this paper, we propose "FedPrompt" to study prompt tuning in a model split aggregation way using FL, and prove that split aggregation greatly reduces the communication cost, only 0. 01% of the PLMs' parameters, with little decrease on accuracy both on IID and Non-IID data distribution.

Backdoor Attack Data Poisoning +2

Few-Shot Table-to-Text Generation with Prefix-Controlled Generator

no code implementations COLING 2022 Yutao Luo, Menghua Lu, Gongshen Liu, Shilin Wang

To alleviate these problems, we propose a prompt-based approach, Prefix-Controlled Generator (i. e., PCG), for few-shot table-to-text generation.

Table-to-Text Generation

ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation

1 code implementation12 Aug 2020 Hanwen Cao, Yongyi Lu, Cewu Lu, Bo Pang, Gongshen Liu, Alan Yuille

In this paper, we further improve spatio-temporal point cloud feature learning with a flexible module called ASAP considering both attention and structure information across frames, which we find as two important factors for successful segmentation in dynamic point clouds.

MoTiAC: Multi-Objective Actor-Critics for Real-Time Bidding

no code implementations18 Feb 2020 Haolin Zhou, Chaoqi Yang, Xiaofeng Gao, Qiong Chen, Gongshen Liu, Guihai Chen

Online Real-Time Bidding (RTB) is a complex auction game among which advertisers struggle to bid for ad impressions when a user request occurs.

Reinforcement Learning (RL)

Multiple Character Embeddings for Chinese Word Segmentation

no code implementations ACL 2019 Jingkang Wang, Jianing Zhou, Jie zhou, Gongshen Liu

Chinese word segmentation (CWS) is often regarded as a character-based sequence labeling task in most current works which have achieved great success with the help of powerful neural networks.

Chinese Word Segmentation

Sliced Recurrent Neural Networks

3 code implementations COLING 2018 Zeping Yu, Gongshen Liu

In this paper, we introduce sliced recurrent neural networks (SRNNs), which could be parallelized by slicing the sequences into many subsequences.

Sentiment Analysis

Modeling Multi-turn Conversation with Deep Utterance Aggregation

1 code implementation COLING 2018 Zhuosheng Zhang, Jiangtong Li, Pengfei Zhu, Hai Zhao, Gongshen Liu

In this paper, we formulate previous utterances into context using a proposed deep utterance aggregation model to form a fine-grained context representation.

Conversational Response Selection Retrieval

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