Search Results for author: Jinsong Su

Found 87 papers, 47 papers with code

Towards Robust Neural Machine Translation with Iterative Scheduled Data-Switch Training

1 code implementation COLING 2022 Zhongjian Miao, Xiang Li, Liyan Kang, Wen Zhang, Chulun Zhou, Yidong Chen, Bin Wang, Min Zhang, Jinsong Su

Most existing methods on robust neural machine translation (NMT) construct adversarial examples by injecting noise into authentic examples and indiscriminately exploit two types of examples.

Machine Translation NMT +2

Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal

no code implementations2 Mar 2024 Jianheng Huang, Leyang Cui, Ante Wang, Chengyi Yang, Xinting Liao, Linfeng Song, Junfeng Yao, Jinsong Su

When conducting continual learning based on a publicly-released LLM checkpoint, the availability of the original training data may be non-existent.

Fine-Grained Self-Endorsement Improves Factuality and Reasoning

no code implementations23 Feb 2024 Ante Wang, Linfeng Song, Baolin Peng, Ye Tian, Lifeng Jin, Haitao Mi, Jinsong Su, Dong Yu

Experiments on Biographies show that our method can effectively improve the factuality of generations with simple and intuitive prompts across different scales of LLMs.

GSM8K Language Modelling +2

TDAG: A Multi-Agent Framework based on Dynamic Task Decomposition and Agent Generation

no code implementations15 Feb 2024 Yaoxiang Wang, Zhiyong Wu, Junfeng Yao, Jinsong Su

The emergence of Large Language Models (LLMs) like ChatGPT has inspired the development of LLM-based agents capable of addressing complex, real-world tasks.

Conditional Variational Autoencoder for Sign Language Translation with Cross-Modal Alignment

1 code implementation25 Dec 2023 Rui Zhao, Liang Zhang, Biao Fu, Cong Hu, Jinsong Su, Yidong Chen

The first KL divergence optimizes the conditional variational autoencoder and regularizes the encoder outputs, while the second KL divergence performs a self-distillation from the posterior path to the prior path, ensuring the consistency of decoder outputs.

Sign Language Translation Translation

Response Enhanced Semi-supervised Dialogue Query Generation

1 code implementation20 Dec 2023 Jianheng Huang, Ante Wang, Linfeng Gao, Linfeng Song, Jinsong Su

Based on the observation that the search query is typically related to the topic of dialogue response, we train a response-augmented query producer (RA) to provide rich and effective training signals for QP.

Domain Adaptation

Retrieval-augmented Multi-modal Chain-of-Thoughts Reasoning for Large Language Models

no code implementations4 Dec 2023 Bingshuai Liu, Chenyang Lyu, Zijun Min, Zhanyu Wang, Jinsong Su, Longyue Wang

However, the selection of optimal CoT demonstration examples in multi-modal reasoning for LLMs remains less explored for LLMs due to the inherent complexity of multi-modal examples.

Question Answering Retrieval

IBADR: an Iterative Bias-Aware Dataset Refinement Framework for Debiasing NLU models

no code implementations1 Nov 2023 Xiaoyue Wang, Xin Liu, Lijie Wang, Yaoxiang Wang, Jinsong Su, Hua Wu

Then, we pair each sample with a bias indicator representing its bias degree, and use these extended samples to train a sample generator.

Natural Language Understanding

On the Cultural Gap in Text-to-Image Generation

no code implementations6 Jul 2023 Bingshuai Liu, Longyue Wang, Chenyang Lyu, Yong Zhang, Jinsong Su, Shuming Shi, Zhaopeng Tu

Accordingly, we propose a novel multi-modal metric that considers object-text alignment to filter the fine-tuning data in the target culture, which is used to fine-tune a T2I model to improve cross-cultural generation.

Text-to-Image Generation

A Simple yet Effective Self-Debiasing Framework for Transformer Models

1 code implementation2 Jun 2023 Xiaoyue Wang, Lijie Wang, Xin Liu, Suhang Wu, Jinsong Su, Hua Wu

In this way, the top-layer sentence representation will be trained to ignore the common biased features encoded by the low-layer sentence representation and focus on task-relevant unbiased features.

Natural Language Understanding Sentence

A Sequence-to-Sequence&Set Model for Text-to-Table Generation

1 code implementation31 May 2023 Tong Li, Zhihao Wang, Liangying Shao, Xuling Zheng, Xiaoli Wang, Jinsong Su

Specifically, in addition to a text encoder encoding the input text, our model is equipped with a table header generator to first output a table header, i. e., the first row of the table, in the manner of sequence generation.

Exploring Better Text Image Translation with Multimodal Codebook

1 code implementation27 May 2023 Zhibin Lan, Jiawei Yu, Xiang Li, Wen Zhang, Jian Luan, Bin Wang, Degen Huang, Jinsong Su

Text image translation (TIT) aims to translate the source texts embedded in the image to target translations, which has a wide range of applications and thus has important research value.

Machine Translation Optical Character Recognition +2

Bridging the Domain Gaps in Context Representations for k-Nearest Neighbor Neural Machine Translation

1 code implementation26 May 2023 Zhiwei Cao, Baosong Yang, Huan Lin, Suhang Wu, Xiangpeng Wei, Dayiheng Liu, Jun Xie, Min Zhang, Jinsong Su

$k$-Nearest neighbor machine translation ($k$NN-MT) has attracted increasing attention due to its ability to non-parametrically adapt to new translation domains.

Domain Adaptation Machine Translation +3

Revisiting Non-Autoregressive Translation at Scale

1 code implementation25 May 2023 Zhihao Wang, Longyue Wang, Jinsong Su, Junfeng Yao, Zhaopeng Tu

Experimental results on the large-scale WMT20 En-De show that the asymmetric architecture (e. g. bigger encoder and smaller decoder) can achieve comparable performance with the scaling model, while maintaining the superiority of decoding speed with standard NAT models.

Translation

BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine Translation

1 code implementation23 May 2023 Liyan Kang, Luyang Huang, Ningxin Peng, Peihao Zhu, Zewei Sun, Shanbo Cheng, Mingxuan Wang, Degen Huang, Jinsong Su

We also introduce two deliberately designed test sets to verify the necessity of visual information: Ambiguous with the presence of ambiguous words, and Unambiguous in which the text context is self-contained for translation.

Contrastive Learning Multimodal Machine Translation +4

RC3: Regularized Contrastive Cross-lingual Cross-modal Pre-training

no code implementations13 May 2023 Chulun Zhou, Yunlong Liang, Fandong Meng, Jinan Xu, Jinsong Su, Jie zhou

In this paper, we propose Regularized Contrastive Cross-lingual Cross-modal (RC^3) pre-training, which further exploits more abundant weakly-aligned multilingual image-text pairs.

Contrastive Learning Machine Translation

From Statistical Methods to Deep Learning, Automatic Keyphrase Prediction: A Survey

no code implementations4 May 2023 Binbin Xie, Jia Song, Liangying Shao, Suhang Wu, Xiangpeng Wei, Baosong Yang, Huan Lin, Jun Xie, Jinsong Su

In this paper, we comprehensively summarize representative studies from the perspectives of dominant models, datasets and evaluation metrics.

Search-Engine-augmented Dialogue Response Generation with Cheaply Supervised Query Production

1 code implementation16 Feb 2023 Ante Wang, Linfeng Song, Qi Liu, Haitao Mi, Longyue Wang, Zhaopeng Tu, Jinsong Su, Dong Yu

We propose a dialogue model that can access the vast and dynamic information from any search engine for response generation.

Chatbot Response Generation

A Multi-task Multi-stage Transitional Training Framework for Neural Chat Translation

no code implementations27 Jan 2023 Chulun Zhou, Yunlong Liang, Fandong Meng, Jie zhou, Jinan Xu, Hongji Wang, Min Zhang, Jinsong Su

To address these issues, in this paper, we propose a multi-task multi-stage transitional (MMT) training framework, where an NCT model is trained using the bilingual chat translation dataset and additional monolingual dialogues.

NMT Sentence +1

Towards Better Document-level Relation Extraction via Iterative Inference

1 code implementation26 Nov 2022 Liang Zhang, Jinsong Su, Yidong Chen, Zhongjian Miao, Zijun Min, Qingguo Hu, Xiaodong Shi

Existing methods usually directly predict the relations of all entity pairs of input document in a one-pass manner, ignoring the fact that predictions of some entity pairs heavily depend on the predicted results of other pairs.

Contrastive Learning Document-level Relation Extraction +1

WR-ONE2SET: Towards Well-Calibrated Keyphrase Generation

1 code implementation13 Nov 2022 Binbin Xie, Xiangpeng Wei, Baosong Yang, Huan Lin, Jun Xie, Xiaoli Wang, Min Zhang, Jinsong Su

Keyphrase generation aims to automatically generate short phrases summarizing an input document.

Keyphrase Generation

Getting the Most out of Simile Recognition

no code implementations11 Nov 2022 Xiaoyue Wang, Linfeng Song, Xin Liu, Chulun Zhou, Jinsong Su

Simile recognition involves two subtasks: simile sentence classification that discriminates whether a sentence contains simile, and simile component extraction that locates the corresponding objects (i. e., tenors and vehicles).

POS Sentence +1

Sentiment-Aware Word and Sentence Level Pre-training for Sentiment Analysis

1 code implementation18 Oct 2022 Shuai Fan, Chen Lin, Haonan Li, Zhenghao Lin, Jinsong Su, Hang Zhang, Yeyun Gong, Jian Guo, Nan Duan

Most existing pre-trained language representation models (PLMs) are sub-optimal in sentiment analysis tasks, as they capture the sentiment information from word-level while under-considering sentence-level information.

Contrastive Learning Language Modelling +3

Towards Robust k-Nearest-Neighbor Machine Translation

3 code implementations17 Oct 2022 Hui Jiang, Ziyao Lu, Fandong Meng, Chulun Zhou, Jie zhou, Degen Huang, Jinsong Su

Meanwhile we inject two types of perturbations into the retrieved pairs for robust training.

Machine Translation NMT +1

Type-Driven Multi-Turn Corrections for Grammatical Error Correction

1 code implementation Findings (ACL) 2022 Shaopeng Lai, Qingyu Zhou, Jiali Zeng, Zhongli Li, Chao Li, Yunbo Cao, Jinsong Su

First, they simply mix additionally-constructed training instances and original ones to train models, which fails to help models be explicitly aware of the procedure of gradual corrections.

Data Augmentation Grammatical Error Correction +1

A Variational Hierarchical Model for Neural Cross-Lingual Summarization

1 code implementation ACL 2022 Yunlong Liang, Fandong Meng, Chulun Zhou, Jinan Xu, Yufeng Chen, Jinsong Su, Jie zhou

The goal of the cross-lingual summarization (CLS) is to convert a document in one language (e. g., English) to a summary in another one (e. g., Chinese).

Machine Translation Translation

Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation

no code implementations ACL 2022 Chulun Zhou, Fandong Meng, Jie zhou, Min Zhang, Hongji Wang, Jinsong Su

Most dominant neural machine translation (NMT) models are restricted to make predictions only according to the local context of preceding words in a left-to-right manner.

Knowledge Distillation Language Modelling +3

A Label Dependence-aware Sequence Generation Model for Multi-level Implicit Discourse Relation Recognition

1 code implementation22 Dec 2021 Changxing Wu, Liuwen Cao, Yubin Ge, Yang Liu, Min Zhang, Jinsong Su

Then, we employ a label sequence decoder to output the predicted labels in a top-down manner, where the predicted higher-level labels are directly used to guide the label prediction at the current level.

Relation

KGR^4: Retrieval, Retrospect, Refine and Rethink for Commonsense Generation

1 code implementation15 Dec 2021 Xin Liu, Dayiheng Liu, Baosong Yang, Haibo Zhang, Junwei Ding, Wenqing Yao, Weihua Luo, Haiying Zhang, Jinsong Su

Generative commonsense reasoning requires machines to generate sentences describing an everyday scenario given several concepts, which has attracted much attention recently.

Retrieval Sentence

Controllable Dialogue Generation with Disentangled Multi-grained Style Specification and Attribute Consistency Reward

no code implementations14 Sep 2021 Zhe Hu, Zhiwei Cao, Hou Pong Chan, Jiachen Liu, Xinyan Xiao, Jinsong Su, Hua Wu

Controllable text generation is an appealing but challenging task, which allows users to specify particular attributes of the generated outputs.

Attribute Dialogue Generation +1

BACO: A Background Knowledge- and Content-Based Framework for Citing Sentence Generation

no code implementations ACL 2021 Yubin Ge, Ly Dinh, Xiaofeng Liu, Jinsong Su, Ziyao Lu, Ante Wang, Jana Diesner

In this paper, we focus on the problem of citing sentence generation, which entails generating a short text to capture the salient information in a cited paper and the connection between the citing and cited paper.

Sentence Text Generation

Exploring Dynamic Selection of Branch Expansion Orders for Code Generation

1 code implementation ACL 2021 Hui Jiang, Chulun Zhou, Fandong Meng, Biao Zhang, Jie zhou, Degen Huang, Qingqiang Wu, Jinsong Su

Due to the great potential in facilitating software development, code generation has attracted increasing attention recently.

Code Generation

Improving Tree-Structured Decoder Training for Code Generation via Mutual Learning

no code implementations31 May 2021 Binbin Xie, Jinsong Su, Yubin Ge, Xiang Li, Jianwei Cui, Junfeng Yao, Bin Wang

However, such a decoder only exploits the preorder traversal based preceding actions, which are insufficient to ensure correct action predictions.

Code Generation

Enhanced Aspect-Based Sentiment Analysis Models with Progressive Self-supervised Attention Learning

1 code implementation5 Mar 2021 Jinsong Su, Jialong Tang, Hui Jiang, Ziyao Lu, Yubin Ge, Linfeng Song, Deyi Xiong, Le Sun, Jiebo Luo

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.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)

Dynamic Context-guided Capsule Network for Multimodal Machine Translation

1 code implementation4 Sep 2020 Huan Lin, Fandong Meng, Jinsong Su, Yongjing Yin, Zhengyuan Yang, Yubin Ge, Jie zhou, Jiebo Luo

Particularly, we represent the input image with global and regional visual features, we introduce two parallel DCCNs to model multimodal context vectors with visual features at different granularities.

Multimodal Machine Translation Representation Learning +1

Exploring Contextual Word-level Style Relevance for Unsupervised Style Transfer

1 code implementation ACL 2020 Chulun Zhou, Liang-Yu Chen, Jiachen Liu, Xinyan Xiao, Jinsong Su, Sheng Guo, Hua Wu

Unsupervised style transfer aims to change the style of an input sentence while preserving its original content without using parallel training data.

Denoising Sentence +1

Neural Simile Recognition with Cyclic Multitask Learning and Local Attention

1 code implementation19 Dec 2019 Jiali Zeng, Linfeng Song, Jinsong Su, Jun Xie, Wei Song, Jiebo Luo

Simile recognition is to detect simile sentences and to extract simile components, i. e., tenors and vehicles.

Sentence Sentence Classification

Iterative Dual Domain Adaptation for Neural Machine Translation

no code implementations IJCNLP 2019 Jiali Zeng, Yang Liu, Jinsong Su, Yubin Ge, Yaojie Lu, Yongjing Yin, Jiebo Luo

Previous studies on the domain adaptation for neural machine translation (NMT) mainly focus on the one-pass transferring out-of-domain translation knowledge to in-domain NMT model.

Domain Adaptation Knowledge Distillation +4

Graph-based Neural Sentence Ordering

1 code implementation16 Dec 2019 Yongjing Yin, Linfeng Song, Jinsong Su, Jiali Zeng, Chulun Zhou, Jiebo Luo

Sentence ordering is to restore the original paragraph from a set of sentences.

Sentence Sentence Ordering

Grounding-Tracking-Integration

no code implementations13 Dec 2019 Zhengyuan Yang, Tushar Kumar, Tianlang Chen, Jinsong Su, Jiebo Luo

In this paper, we study Tracking by Language that localizes the target box sequence in a video based on a language query.

A Real-time Global Inference Network for One-stage Referring Expression Comprehension

1 code implementation7 Dec 2019 Yiyi Zhou, Rongrong Ji, Gen Luo, Xiaoshuai Sun, Jinsong Su, Xinghao Ding, Chia-Wen Lin, Qi Tian

Referring Expression Comprehension (REC) is an emerging research spot in computer vision, which refers to detecting the target region in an image given an text description.

feature selection Referring Expression +1

Exploiting Temporal Relationships in Video Moment Localization with Natural Language

1 code implementation11 Aug 2019 Songyang Zhang, Jinsong Su, Jiebo Luo

We address the problem of video moment localization with natural language, i. e. localizing a video segment described by a natural language sentence.

Sentence

Neural Collective Entity Linking Based on Recurrent Random Walk Network Learning

1 code implementation20 Jun 2019 Mengge Xue, Weiming Cai, Jinsong Su, Linfeng Song, Yubin Ge, Yubao Liu, Bin Wang

However, most neural collective EL methods depend entirely upon neural networks to automatically model the semantic dependencies between different EL decisions, which lack of the guidance from external knowledge.

Entity Disambiguation Entity Linking +1

Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis

1 code implementation ACL 2019 Jialong Tang, Ziyao Lu, Jinsong Su, Yubin Ge, Linfeng Song, Le Sun, Jiebo Luo

In aspect-level sentiment classification (ASC), it is prevalent to equip dominant neural models with attention mechanisms, for the sake of acquiring the importance of each context word on the given aspect.

Aspect-Based Sentiment Analysis (ABSA) Sentiment Classification

Semantic Neural Machine Translation using AMR

1 code implementation TACL 2019 Linfeng Song, Daniel Gildea, Yue Zhang, Zhiguo Wang, Jinsong Su

It is intuitive that semantic representations can be useful for machine translation, mainly because they can help in enforcing meaning preservation and handling data sparsity (many sentences correspond to one meaning) of machine translation models.

Machine Translation NMT +1

Towards Linear Time Neural Machine Translation with Capsule Networks

no code implementations IJCNLP 2019 Mingxuan Wang, Jun Xie, Zhixing Tan, Jinsong Su, Deyi Xiong, Lei LI

In this study, we first investigate a novel capsule network with dynamic routing for linear time Neural Machine Translation (NMT), referred as \textsc{CapsNMT}.

Machine Translation NMT +2

Simplifying Neural Machine Translation with Addition-Subtraction Twin-Gated Recurrent Networks

3 code implementations EMNLP 2018 Biao Zhang, Deyi Xiong, Jinsong Su, Qian Lin, Huiji Zhang

Experiments on WMT14 translation tasks demonstrate that ATR-based neural machine translation can yield competitive performance on English- German and English-French language pairs in terms of both translation quality and speed.

Chinese Word Segmentation Machine Translation +2

Otem&Utem: Over- and Under-Translation Evaluation Metric for NMT

1 code implementation24 Jul 2018 Jing Yang, Biao Zhang, Yue Qin, Xiangwen Zhang, Qian Lin, Jinsong Su

Although neural machine translation(NMT) yields promising translation performance, it unfortunately suffers from over- and under-translation is- sues [Tu et al., 2016], of which studies have become research hotspots in NMT.

Machine Translation NMT +1

Deconvolution-Based Global Decoding for Neural Machine Translation

1 code implementation COLING 2018 Junyang Lin, Xu sun, Xuancheng Ren, Shuming Ma, Jinsong Su, Qi Su

A great proportion of sequence-to-sequence (Seq2Seq) models for Neural Machine Translation (NMT) adopt Recurrent Neural Network (RNN) to generate translation word by word following a sequential order.

Machine Translation NMT +1

GroupCap: Group-Based Image Captioning With Structured Relevance and Diversity Constraints

no code implementations CVPR 2018 Fuhai Chen, Rongrong Ji, Xiaoshuai Sun, Yongjian Wu, Jinsong Su

In offline optimization, we adopt an end-to-end formulation, which jointly trains the visual tree parser, the structured relevance and diversity constraints, as well as the LSTM based captioning model.

Image Captioning

Accelerating Neural Transformer via an Average Attention Network

1 code implementation ACL 2018 Biao Zhang, Deyi Xiong, Jinsong Su

To alleviate this issue, we propose an average attention network as an alternative to the self-attention network in the decoder of the neural Transformer.

Machine Translation Translation

Asynchronous Bidirectional Decoding for Neural Machine Translation

2 code implementations16 Jan 2018 Xiangwen Zhang, Jinsong Su, Yue Qin, Yang Liu, Rongrong Ji, Hongji Wang

The dominant neural machine translation (NMT) models apply unified attentional encoder-decoder neural networks for translation.

Machine Translation NMT +1

Variational Recurrent Neural Machine Translation

no code implementations16 Jan 2018 Jinsong Su, Shan Wu, Deyi Xiong, Yaojie Lu, Xianpei Han, Biao Zhang

Partially inspired by successful applications of variational recurrent neural networks, we propose a novel variational recurrent neural machine translation (VRNMT) model in this paper.

Machine Translation NMT +2

A GRU-Gated Attention Model for Neural Machine Translation

no code implementations27 Apr 2017 Biao Zhang, Deyi Xiong, Jinsong Su

In this paper, we propose a novel GRU-gated attention model (GAtt) for NMT which enhances the degree of discrimination of context vectors by enabling source representations to be sensitive to the partial translation generated by the decoder.

Machine Translation NMT +1

Lattice-Based Recurrent Neural Network Encoders for Neural Machine Translation

no code implementations25 Sep 2016 Jinsong Su, Zhixing Tan, Deyi Xiong, Rongrong Ji, Xiaodong Shi, Yang Liu

Neural machine translation (NMT) heavily relies on word-level modelling to learn semantic representations of input sentences.

Machine Translation NMT +2

Cseq2seq: Cyclic Sequence-to-Sequence Learning

no code implementations29 Jul 2016 Biao Zhang, Deyi Xiong, Jinsong Su

The vanilla sequence-to-sequence learning (seq2seq) reads and encodes a source sequence into a fixed-length vector only once, suffering from its insufficiency in modeling structural correspondence between the source and target sequence.

Machine Translation Test +2

BattRAE: Bidimensional Attention-Based Recursive Autoencoders for Learning Bilingual Phrase Embeddings

1 code implementation25 May 2016 Biao Zhang, Deyi Xiong, Jinsong Su

In this paper, we propose a bidimensional attention based recursive autoencoder (BattRAE) to integrate clues and sourcetarget interactions at multiple levels of granularity into bilingual phrase representations.

Semantic Similarity Semantic Textual Similarity +1

Variational Neural Machine Translation

1 code implementation EMNLP 2016 Biao Zhang, Deyi Xiong, Jinsong Su, Hong Duan, Min Zhang

Models of neural machine translation are often from a discriminative family of encoderdecoders that learn a conditional distribution of a target sentence given a source sentence.

Machine Translation Sentence +1

Variational Neural Discourse Relation Recognizer

1 code implementation EMNLP 2016 Biao Zhang, Deyi Xiong, Jinsong Su, Qun Liu, Rongrong Ji, Hong Duan, Min Zhang

In order to perform efficient inference and learning, we introduce neural discourse relation models to approximate the prior and posterior distributions of the latent variable, and employ these approximated distributions to optimize a reparameterized variational lower bound.

Relation

Neural Discourse Relation Recognition with Semantic Memory

no code implementations12 Mar 2016 Biao Zhang, Deyi Xiong, Jinsong Su

Inspired by this, we propose a neural recognizer for implicit discourse relation analysis, which builds upon a semantic memory that stores knowledge in a distributed fashion.

General Knowledge Relation +1

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