Search Results for author: Bing Yin

Found 39 papers, 14 papers with code

MetaTS: Meta Teacher-Student Network for Multilingual Sequence Labeling with Minimal Supervision

no code implementations EMNLP 2021 Zheng Li, Danqing Zhang, Tianyu Cao, Ying WEI, Yiwei Song, Bing Yin

In this work, we explore multilingual sequence labeling with minimal supervision using a single unified model for multiple languages.


Learn to Cross-lingual Transfer with Meta Graph Learning Across Heterogeneous Languages

no code implementations EMNLP 2020 Zheng Li, Mukul Kumar, William Headden, Bing Yin, Ying WEI, Yu Zhang, Qiang Yang

Recent emergence of multilingual pre-training language model (mPLM) has enabled breakthroughs on various downstream cross-lingual transfer (CLT) tasks.

Cross-Lingual Transfer Graph Learning +1

Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

no code implementations6 Feb 2024 Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, Zheyuan Liu, Bing Yin, Meng Jiang

OPPU integrates parametric user knowledge in the personal PEFT parameters with the non-parametric knowledge acquired through retrieval and profile.


Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns

1 code implementation NeurIPS 2023 Xin Liu, Zheng Li, Yifan Gao, Jingfeng Yang, Tianyu Cao, Zhengyang Wang, Bing Yin, Yangqiu Song

The goal of session-based recommendation in E-commerce is to predict the next item that an anonymous user will purchase based on the browsing and purchase history.

Attribute Session-Based Recommendations

1DFormer: a Transformer Architecture Learning 1D Landmark Representations for Facial Landmark Tracking

no code implementations1 Nov 2023 Shi Yin, Shijie Huan, Shangfei Wang, Jinshui Hu, Tao Guo, Bing Yin, BaoCai Yin, Cong Liu

For temporal modeling, we propose a recurrent token mixing mechanism, an axis-landmark-positional embedding mechanism, as well as a confidence-enhanced multi-head attention mechanism to adaptively and robustly embed long-term landmark dynamics into their 1D representations; for structure modeling, we design intra-group and inter-group structure modeling mechanisms to encode the component-level as well as global-level facial structure patterns as a refinement for the 1D representations of landmarks through token communications in the spatial dimension via 1D convolutional layers.

Landmark Tracking

Situated Natural Language Explanations

no code implementations27 Aug 2023 Zining Zhu, Haoming Jiang, Jingfeng Yang, Sreyashi Nag, Chao Zhang, Jie Huang, Yifan Gao, Frank Rudzicz, Bing Yin

Situated NLE provides a perspective and facilitates further research on the generation and evaluation of explanations.

Prompt Engineering

Exploring Part-Informed Visual-Language Learning for Person Re-Identification

no code implementations4 Aug 2023 Yin Lin, Cong Liu, Yehansen Chen, Jinshui Hu, Bing Yin, BaoCai Yin, Zengfu Wang

Recently, visual-language learning has shown great potential in enhancing visual-based person re-identification (ReID).

Human Parsing Person Re-Identification

Multimodal Prompt Learning for Product Title Generation with Extremely Limited Labels

no code implementations5 Jul 2023 Bang Yang, Fenglin Liu, Zheng Li, Qingyu Yin, Chenyu You, Bing Yin, Yuexian Zou

We observe that the core challenges of novel product title generation are the understanding of novel product characteristics and the generation of titles in a novel writing style.

Image Captioning Text Generation

Knowledge Graph Reasoning over Entities and Numerical Values

1 code implementation2 Jun 2023 Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Bing Yin, Yangqiu Song

To address the difference between entities and numerical values, we also propose the framework of Number Reasoning Network (NRN) for alternatively encoding entities and numerical values into separate encoding structures.

Attribute Complex Query Answering

Graph Reasoning for Question Answering with Triplet Retrieval

no code implementations30 May 2023 Shiyang Li, Yifan Gao, Haoming Jiang, Qingyu Yin, Zheng Li, Xifeng Yan, Chao Zhang, Bing Yin

State-of-the-art methods often utilize entities in questions to retrieve local subgraphs, which are then fed into KG encoder, e. g. graph neural networks (GNNs), to model their local structures and integrated into language models for question answering.

Knowledge Graphs Question Answering +1

CCGen: Explainable Complementary Concept Generation in E-Commerce

no code implementations19 May 2023 Jie Huang, Yifan Gao, Zheng Li, Jingfeng Yang, Yangqiu Song, Chao Zhang, Zining Zhu, Haoming Jiang, Kevin Chen-Chuan Chang, Bing Yin

We propose and study Complementary Concept Generation (CCGen): given a concept of interest, e. g., "Digital Cameras", generating a list of complementary concepts, e. g., 1) Camera Lenses 2) Batteries 3) Camera Cases 4) Memory Cards 5) Battery Chargers.

SCOTT: Self-Consistent Chain-of-Thought Distillation

1 code implementation3 May 2023 Peifeng Wang, Zhengyang Wang, Zheng Li, Yifan Gao, Bing Yin, Xiang Ren

While CoT can yield dramatically improved performance, such gains are only observed for sufficiently large LMs.

counterfactual Counterfactual Reasoning +1

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

1 code implementation26 Apr 2023 Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, Xia Hu

This paper presents a comprehensive and practical guide for practitioners and end-users working with Large Language Models (LLMs) in their downstream natural language processing (NLP) tasks.

Language Modelling Natural Language Understanding +1

VGTS: Visually Guided Text Spotting for Novel Categories in Historical Manuscripts

no code implementations3 Apr 2023 WenBo Hu, Hongjian Zhan, Xinchen Ma, Cong Liu, Bing Yin, Yue Lu

In the field of historical manuscript research, scholars frequently encounter novel symbols in ancient texts, investing considerable effort in their identification and documentation.

Geometric Matching Metric Learning +4

Mutually-paced Knowledge Distillation for Cross-lingual Temporal Knowledge Graph Reasoning

no code implementations27 Mar 2023 Ruijie Wang, Zheng Li, Jingfeng Yang, Tianyu Cao, Chao Zhang, Bing Yin, Tarek Abdelzaher

This paper investigates cross-lingual temporal knowledge graph reasoning problem, which aims to facilitate reasoning on Temporal Knowledge Graphs (TKGs) in low-resource languages by transfering knowledge from TKGs in high-resource ones.

Knowledge Distillation Knowledge Graphs +1

Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs

no code implementations16 Oct 2022 Ruijie Wang, Zheng Li, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek Abdelzaher

Second, the potentially dynamic distributions from the initially observable facts to the future facts ask for explicitly modeling the evolving characteristics of new entities.

Knowledge Graphs Meta-Learning

DiP-GNN: Discriminative Pre-Training of Graph Neural Networks

no code implementations15 Sep 2022 Simiao Zuo, Haoming Jiang, Qingyu Yin, Xianfeng Tang, Bing Yin, Tuo Zhao

Specifically, we train a generator to recover identities of the masked edges, and simultaneously, we train a discriminator to distinguish the generated edges from the original graph's edges.

Node Classification

Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites

no code implementations15 Sep 2022 Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao

The model subsequently calculates session representations by combining the contextual information with the instant search query using an aggregation network.

Graph Attention

SGBANet: Semantic GAN and Balanced Attention Network for Arbitrarily Oriented Scene Text Recognition

no code implementations21 Jul 2022 Dajian Zhong, Shujing Lyu, Palaiahnakote Shivakumara, Bing Yin, Jiajia Wu, Umapada Pal, Yue Lu

For target images (scene text images), the Semantic Generator Module generates simple semantic features that share the same feature distribution with support images (clear text images).

Image-to-Image Translation Scene Text Recognition

Condensing Graphs via One-Step Gradient Matching

3 code implementations15 Jun 2022 Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin

However, existing approaches have their inherent limitations: (1) they are not directly applicable to graphs where the data is discrete; and (2) the condensation process is computationally expensive due to the involved nested optimization.

Dataset Condensation

Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment

1 code implementation ACL 2022 Zijie Huang, Zheng Li, Haoming Jiang, Tianyu Cao, Hanqing Lu, Bing Yin, Karthik Subbian, Yizhou Sun, Wei Wang

In this paper, we explore multilingual KG completion, which leverages limited seed alignment as a bridge, to embrace the collective knowledge from multiple languages.

Knowledge Graph Completion

RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary Graph

no code implementations12 Feb 2022 Ruijie Wang, Zheng Li, Danqing Zhang, Qingyu Yin, Tong Zhao, Bing Yin, Tarek Abdelzaher

And meanwhile, RETE autoregressively accumulates retrieval-enhanced user representations from each time step, to capture evolutionary patterns for joint query and product prediction.

Product Recommendation Retrieval

QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction

no code implementations19 Aug 2021 Danqing Zhang, Zheng Li, Tianyu Cao, Chen Luo, Tony Wu, Hanqing Lu, Yiwei Song, Bing Yin, Tuo Zhao, Qiang Yang

We study the problem of query attribute value extraction, which aims to identify named entities from user queries as diverse surface form attribute values and afterward transform them into formally canonical forms.

Attribute Attribute Value Extraction +3

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data

1 code implementation ACL 2021 Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao

Unfortunately, we observe that weakly labeled data does not necessarily improve, or even deteriorate the model performance (due to the extensive noise in the weak labels) when we train deep NER models over a simple or weighted combination of the strongly labeled and weakly labeled data.

named-entity-recognition Named Entity Recognition +1

Graph-based Multilingual Product Retrieval in E-commerce Search

no code implementations NAACL 2021 Hanqing Lu, Youna Hu, Tong Zhao, Tony Wu, Yiwei Song, Bing Yin

Nowadays, with many e-commerce platforms conducting global business, e-commerce search systems are required to handle product retrieval under multilingual scenarios.

Graph Attention Retrieval

On Data Augmentation for Extreme Multi-label Classification

no code implementations22 Sep 2020 Danqing Zhang, Tao Li, Haiyang Zhang, Bing Yin

Our contributions are two-factored: (1) we introduce a new state-of-the-art classifier that uses label attention with RoBERTa and combine it with our augmentation framework for further improvement; (2) we present a broad study on how effective are different augmentation methods in the XMC task.

Classification Data Augmentation +2

Shareable Representations for Search Query Understanding

no code implementations20 Dec 2019 Mukul Kumar, Youna Hu, Will Headden, Rahul Goutam, Heran Lin, Bing Yin

Recent works such as BERT have demonstrated the success of a large transformer encoder architecture with language model pre-training on a variety of NLP tasks.

Language Modelling

Semantic Product Search

1 code implementation1 Jul 2019 Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian, Ding, Ankit Shingavi, Choon Hui Teo, Hao Gu, Bing Yin

To address these issues, we train a deep learning model for semantic matching using customer behavior data.

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