Search Results for author: Bo Zheng

Found 82 papers, 25 papers with code

MT-Bench-101: A Fine-Grained Benchmark for Evaluating Large Language Models in Multi-Turn Dialogues

no code implementations22 Feb 2024 Ge Bai, Jie Liu, Xingyuan Bu, Yancheng He, Jiaheng Liu, Zhanhui Zhou, Zhuoran Lin, Wenbo Su, Tiezheng Ge, Bo Zheng, Wanli Ouyang

By conducting a detailed analysis of real multi-turn dialogue data, we construct a three-tier hierarchical ability taxonomy comprising 4208 turns across 1388 multi-turn dialogues in 13 distinct tasks.

ConceptMath: A Bilingual Concept-wise Benchmark for Measuring Mathematical Reasoning of Large Language Models

1 code implementation22 Feb 2024 Yanan Wu, Jie Liu, Xingyuan Bu, Jiaheng Liu, Zhanhui Zhou, Yuanxing Zhang, Chenchen Zhang, Zhiqi Bai, Haibin Chen, Tiezheng Ge, Wanli Ouyang, Wenbo Su, Bo Zheng

This paper introduces ConceptMath, a bilingual (English and Chinese), fine-grained benchmark that evaluates concept-wise mathematical reasoning of Large Language Models (LLMs).

Math Mathematical Reasoning

Scalable Virtual Valuations Combinatorial Auction Design by Combining Zeroth-Order and First-Order Optimization Method

no code implementations19 Feb 2024 Zhijian Duan, Haoran Sun, Yichong Xia, Siqiang Wang, Zhilin Zhang, Chuan Yu, Jian Xu, Bo Zheng, Xiaotie Deng

Subsequently, we propose a novel optimization method that combines both zeroth-order and first-order techniques to optimize the VVCA parameters.

E^2-LLM: Efficient and Extreme Length Extension of Large Language Models

no code implementations13 Jan 2024 Jiaheng Liu, Zhiqi Bai, Yuanxing Zhang, Chenchen Zhang, Yu Zhang, Ge Zhang, Jiakai Wang, Haoran Que, Yukang Chen, Wenbo Su, Tiezheng Ge, Jie Fu, Wenhu Chen, Bo Zheng

Typically, training LLMs with long context sizes is computationally expensive, requiring extensive training hours and GPU resources.


EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Masked Audio Gesture Modeling

no code implementations31 Dec 2023 Haiyang Liu, Zihao Zhu, Giorgio Becherini, Yichen Peng, Mingyang Su, You Zhou, Naoya Iwamoto, Bo Zheng, Michael J. Black

We propose EMAGE, a framework to generate full-body human gestures from audio and masked gestures, encompassing facial, local body, hands, and global movements.

Gesture Generation

Calibration-compatible Listwise Distillation of Privileged Features for CTR Prediction

no code implementations14 Dec 2023 Xiaoqiang Gui, Yueyao Cheng, Xiang-Rong Sheng, Yunfeng Zhao, Guoxian Yu, Shuguang Han, Yuning Jiang, Jian Xu, Bo Zheng

A typical practice is privileged features distillation (PFD): train a teacher model using all features (including privileged ones) and then distill the knowledge from the teacher model using a student model (excluding the privileged features), which is then employed for online serving.

Click-Through Rate Prediction

Combating Bilateral Edge Noise for Robust Link Prediction

1 code implementation NeurIPS 2023 Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, Li He, Liang Wang, Bo Zheng, Bo Han

To address this dilemma, we propose an information-theory-guided principle, Robust Graph Information Bottleneck (RGIB), to extract reliable supervision signals and avoid representation collapse.

Denoising Link Prediction +1

Robust Representation Learning for Unified Online Top-K Recommendation

no code implementations24 Oct 2023 Minfang Lu, Yuchen Jiang, Huihui Dong, Qi Li, Ziru Xu, Yuanlin Liu, Lixia Wu, Haoyuan Hu, Han Zhu, Yuning Jiang, Jian Xu, Bo Zheng

The robust representation learning employs domain adversarial learning and multi-view wasserstein distribution learning to learn robust representations.

Fairness Representation Learning

OneSeg: Self-learning and One-shot Learning based Single-slice Annotation for 3D Medical Image Segmentation

no code implementations24 Sep 2023 Yixuan Wu, Bo Zheng, Jintai Chen, Danny Z. Chen, Jian Wu

As deep learning methods continue to improve medical image segmentation performance, data annotation is still a big bottleneck due to the labor-intensive and time-consuming burden on medical experts, especially for 3D images.

Image Segmentation Medical Image Segmentation +5

Neuro-Symbolic Recommendation Model based on Logic Query

no code implementations14 Sep 2023 Maonian Wu, Bang Chen, Shaojun Zhu, Bo Zheng, Wei Peng, Mingyi Zhang

A recommendation system assists users in finding items that are relevant to them.

Entire Space Cascade Delayed Feedback Modeling for Effective Conversion Rate Prediction

no code implementations9 Aug 2023 Yunfeng Zhao, Xu Yan, Xiaoqiang Gui, Shuguang Han, Xiang-Rong Sheng, Guoxian Yu, Jufeng Chen, Zhao Xu, Bo Zheng

Furthermore, there is delayed feedback in both conversion and refund events and they are sequentially dependent, named cascade delayed feedback (CDF), which significantly harms data freshness for model training.

Recommendation Systems Selection bias

Neural-Symbolic Recommendation with Graph-Enhanced Information

1 code implementation11 Jul 2023 Bang Chen, Wei Peng, Maonian Wu, Bo Zheng, Shaojun Zhu

Some researchers use user behavior for logic reasoning to achieve recommendation prediction from the perspective of cognitive reasoning, but this kind of reasoning is a local one and ignores implicit information on a global scale.

Recommendation Systems

Multi-Scenario Ranking with Adaptive Feature Learning

no code implementations29 Jun 2023 Yu Tian, Bofang Li, Si Chen, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng, Qian Wang, Chenliang Li

Recently, Multi-Scenario Learning (MSL) is widely used in recommendation and retrieval systems in the industry because it facilitates transfer learning from different scenarios, mitigating data sparsity and reducing maintenance cost.

Retrieval Transfer Learning

Adversarial Constrained Bidding via Minimax Regret Optimization with Causality-Aware Reinforcement Learning

no code implementations12 Jun 2023 Haozhe Wang, Chao Du, Panyan Fang, Li He, Liang Wang, Bo Zheng

In this regard, we explore the problem of constrained bidding in adversarial bidding environments, which assumes no knowledge about the adversarial factors.

Meta-Learning reinforcement-learning

COPR: Consistency-Oriented Pre-Ranking for Online Advertising

no code implementations6 Jun 2023 Zhishan Zhao, Jingyue Gao, Yu Zhang, Shuguang Han, Siyuan Lou, Xiang-Rong Sheng, Zhe Wang, Han Zhu, Yuning Jiang, Jian Xu, Bo Zheng

In this architecture, the pre-ranking model is expected to be a lightweight approximation of the ranking model, which handles more candidates with strict latency requirements.

On Structural Expressive Power of Graph Transformers

no code implementations23 May 2023 Wenhao Zhu, Tianyu Wen, Guojie Song, Liang Wang, Bo Zheng

Graph Transformer has recently received wide attention in the research community with its outstanding performance, yet its structural expressive power has not been well analyzed.


FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning

no code implementations15 May 2023 Penghui Wei, Hongjian Dou, Shaoguo Liu, Rongjun Tang, Li Liu, Liang Wang, Bo Zheng

We introduce FedAds, the first benchmark for CVR estimation with vFL, to facilitate standardized and systematical evaluations for vFL algorithms.

Federated Learning Privacy Preserving

Hybrid Contrastive Constraints for Multi-Scenario Ad Ranking

no code implementations6 Feb 2023 Shanlei Mu, Penghui Wei, Wayne Xin Zhao, Shaoguo Liu, Liang Wang, Bo Zheng

In this paper, we propose a Hybrid Contrastive Constrained approach (HC^2) for multi-scenario ad ranking.

Contrastive Learning

RLTP: Reinforcement Learning to Pace for Delayed Impression Modeling in Preloaded Ads

no code implementations6 Feb 2023 Penghui Wei, Yongqiang Chen, Shaoguo Liu, Liang Wang, Bo Zheng

In a whole delivery period, advertisers usually desire a certain impression count for the ads, and they also expect that the delivery performance is as good as possible (e. g., obtaining high click-through rate).

reinforcement-learning Reinforcement Learning (RL)

End-to-End Modeling Hierarchical Time Series Using Autoregressive Transformer and Conditional Normalizing Flow based Reconciliation

1 code implementation28 Dec 2022 Shiyu Wang, Fan Zhou, Yinbo Sun, Lintao Ma, James Zhang, Yangfei Zheng, Bo Zheng, Lei Lei, Yun Hu

Multivariate time series forecasting with hierarchical structure is pervasive in real-world applications, demanding not only predicting each level of the hierarchy, but also reconciling all forecasts to ensure coherency, i. e., the forecasts should satisfy the hierarchical aggregation constraints.

Multivariate Time Series Forecasting Time Series

Correlative Preference Transfer with Hierarchical Hypergraph Network for Multi-Domain Recommendation

no code implementations21 Nov 2022 Zixuan Xu, Penghui Wei, Shaoguo Liu, Weimin Zhang, Liang Wang, Bo Zheng

Conventional graph neural network based methods usually deal with each domain separately, or train a shared model to serve all domains.

Marketing Recommendation Systems

Sustainable Online Reinforcement Learning for Auto-bidding

1 code implementation13 Oct 2022 Zhiyu Mou, Yusen Huo, Rongquan Bai, Mingzhou Xie, Chuan Yu, Jian Xu, Bo Zheng

Due to safety concerns, it was believed that the RL training process can only be carried out in an offline virtual advertising system (VAS) that is built based on the historical data generated in the RAS.

Q-Learning reinforcement-learning +1

Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Prediction Models

1 code implementation4 Sep 2022 Zhao-Yu Zhang, Xiang-Rong Sheng, Yujing Zhang, Biye Jiang, Shuguang Han, Hongbo Deng, Bo Zheng

However, far less attention has been paid to the overfitting problem of models in recommendation systems, which, on the contrary, is recognized as a critical issue for deep neural networks.

Click-Through Rate Prediction Recommendation Systems

Modeling Adaptive Fine-grained Task Relatedness for Joint CTR-CVR Estimation

no code implementations29 Aug 2022 Zihan Lin, Xuanhua Yang, Xiaoyu Peng, Wayne Xin Zhao, Shaoguo Liu, Liang Wang, Bo Zheng

For this purpose, we build a relatedness prediction network, so that it can predict the contrast strength for inter-task representations of an instance.

Contrastive Learning Multi-Task Learning +2

KEEP: An Industrial Pre-Training Framework for Online Recommendation via Knowledge Extraction and Plugging

no code implementations22 Aug 2022 Yujing Zhang, Zhangming Chan, Shuhao Xu, Weijie Bian, Shuguang Han, Hongbo Deng, Bo Zheng

To alleviate this issue, we propose to extract knowledge from the \textit{super-domain} that contains web-scale and long-time impression data, and further assist the online recommendation task (downstream task).

Recommendation Systems

Joint Optimization of Ranking and Calibration with Contextualized Hybrid Model

no code implementations12 Aug 2022 Xiang-Rong Sheng, Jingyue Gao, Yueyao Cheng, Siran Yang, Shuguang Han, Hongbo Deng, Yuning Jiang, Jian Xu, Bo Zheng

It can be attributed to the calibration ability of the pointwise loss since the prediction can be viewed as the click probability.

Click-Through Rate Prediction

Adaptive Domain Interest Network for Multi-domain Recommendation

no code implementations20 Jun 2022 Yuchen Jiang, Qi Li, Han Zhu, Jinbei Yu, Jin Li, Ziru Xu, Huihui Dong, Bo Zheng

Industrial recommender systems usually hold data from multiple business scenarios and are expected to provide recommendation services for these scenarios simultaneously.

Domain Adaptation Recommendation Systems +1

Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimization

no code implementations2 Jun 2022 Mingyuan Cheng, Xinru Liao, Quan Liu, Bin Ma, Jian Xu, Bo Zheng

Learning individual-level treatment effect is a fundamental problem in causal inference and has received increasing attention in many areas, especially in the user growth area which concerns many internet companies.

Causal Inference counterfactual +3

Hierarchically Constrained Adaptive Ad Exposure in Feeds

no code implementations31 May 2022 Dagui Chen, Qi Yan, Chunjie Chen, Zhenzhe Zheng, Yangsu Liu, Zhenjia Ma, Chuan Yu, Jian Xu, Bo Zheng

To this end, adaptive ad exposure has become an appealing strategy to boost the overall performance of the feed.

Computational Efficiency

Towards Personalized Bundle Creative Generation with Contrastive Non-Autoregressive Decoding

no code implementations30 May 2022 Penghui Wei, Shaoguo Liu, Xuanhua Yang, Liang Wang, Bo Zheng

Current bundle generation studies focus on generating a combination of items to improve user experience.

GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Model

no code implementations23 May 2022 Wenbo Su, Yuanxing Zhang, Yufeng Cai, Kaixu Ren, Pengjie Wang, Huimin Yi, Yue Song, Jing Chen, Hongbo Deng, Jian Xu, Lin Qu, Bo Zheng

High-concurrency asynchronous training upon parameter server (PS) architecture and high-performance synchronous training upon all-reduce (AR) architecture are the most commonly deployed distributed training modes for recommendation models.

Recommendation Systems

CREATER: CTR-driven Advertising Text Generation with Controlled Pre-Training and Contrastive Fine-Tuning

no code implementations NAACL (ACL) 2022 Penghui Wei, Xuanhua Yang, Shaoguo Liu, Liang Wang, Bo Zheng

This paper focuses on automatically generating the text of an ad, and the goal is that the generated text can capture user interest for achieving higher click-through rate (CTR).

Contrastive Learning Text Generation

StableMoE: Stable Routing Strategy for Mixture of Experts

1 code implementation ACL 2022 Damai Dai, Li Dong, Shuming Ma, Bo Zheng, Zhifang Sui, Baobao Chang, Furu Wei

We point out that existing learning-to-route MoE methods suffer from the routing fluctuation issue, i. e., the target expert of the same input may change along with training, but only one expert will be activated for the input during inference.

Language Modelling Machine Translation

PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems

1 code implementation11 Apr 2022 Yuanxing Zhang, Langshi Chen, Siran Yang, Man Yuan, Huimin Yi, Jie Zhang, Jiamang Wang, Jianbo Dong, Yunlong Xu, Yue Song, Yong Li, Di Zhang, Wei Lin, Lin Qu, Bo Zheng

However, we observe that GPU devices in training recommender systems are underutilized, and they cannot attain an expected throughput improvement as what it has achieved in CV and NLP areas.

Marketing Recommendation Systems

APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction

1 code implementation30 Mar 2022 Bencheng Yan, Pengjie Wang, Kai Zhang, Feng Li, Hongbo Deng, Jian Xu, Bo Zheng

In many web applications, deep learning-based CTR prediction models (deep CTR models for short) are widely adopted.

Click-Through Rate Prediction

AMCAD: Adaptive Mixed-Curvature Representation based Advertisement Retrieval System

no code implementations28 Mar 2022 Zhirong Xu, Shiyang Wen, Junshan Wang, Guojun Liu, Liang Wang, Zhi Yang, Lei Ding, Yan Zhang, Di Zhang, Jian Xu, Bo Zheng

Moreover, to deploy AMCAD in Taobao, one of the largest ecommerce platforms with hundreds of million users, we design an efficient two-layer online retrieval framework for the task of graph based advertisement retrieval.

Graph Embedding Information Retrieval +1

BEAT: A Large-Scale Semantic and Emotional Multi-Modal Dataset for Conversational Gestures Synthesis

1 code implementation10 Mar 2022 Haiyang Liu, Zihao Zhu, Naoya Iwamoto, Yichen Peng, Zhengqing Li, You Zhou, Elif Bozkurt, Bo Zheng

Achieving realistic, vivid, and human-like synthesized conversational gestures conditioned on multi-modal data is still an unsolved problem due to the lack of available datasets, models and standard evaluation metrics.

Gesture Generation Gesture Recognition

Asymptotically Unbiased Estimation for Delayed Feedback Modeling via Label Correction

1 code implementation14 Feb 2022 Yu Chen, Jiaqi Jin, Hui Zhao, Pengjie Wang, Guojun Liu, Jian Xu, Bo Zheng

Moreover, to estimate CVR upon the freshly observed but biased distribution with fake negatives, the importance sampling is widely used to reduce the distribution bias.

MBCT: Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration

1 code implementation9 Feb 2022 Siguang Huang, Yunli Wang, Lili Mou, Huayue Zhang, Han Zhu, Chuan Yu, Bo Zheng

In previous work, researchers have developed several calibration methods to post-process the outputs of a predictor to obtain calibrated values, such as binning and scaling methods.

Medical Diagnosis

UKD: Debiasing Conversion Rate Estimation via Uncertainty-regularized Knowledge Distillation

no code implementations20 Jan 2022 Zixuan Xu, Penghui Wei, Weimin Zhang, Shaoguo Liu, Liang Wang, Bo Zheng

Then a student model is trained on both clicked and unclicked ads with knowledge distillation, performing uncertainty modeling to alleviate the inherent noise in pseudo-labels.

Knowledge Distillation Selection bias

Adversarial Gradient Driven Exploration for Deep Click-Through Rate Prediction

no code implementations21 Dec 2021 Kailun Wu, Zhangming Chan, Weijie Bian, Lejian Ren, Shiming Xiang, Shuguang Han, Hongbo Deng, Bo Zheng

We further show that such a process is equivalent to adding an adversarial perturbation to the model input, and thereby name our proposed approach as an the Adversarial Gradient Driven Exploration (AGE).

Click-Through Rate Prediction Recommendation Systems

Characterizing the adversarial vulnerability of speech self-supervised learning

no code implementations8 Nov 2021 Haibin Wu, Bo Zheng, Xu Li, Xixin Wu, Hung-Yi Lee, Helen Meng

As the paradigm of the self-supervised learning upstream model followed by downstream tasks arouses more attention in the speech community, characterizing the adversarial robustness of such paradigm is of high priority.

Adversarial Robustness Benchmarking +2

Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training

2 code implementations EMNLP 2021 Bo Zheng, Li Dong, Shaohan Huang, Saksham Singhal, Wanxiang Che, Ting Liu, Xia Song, Furu Wei

We find that many languages are under-represented in recent cross-lingual language models due to the limited vocabulary capacity.

Language Modelling

Binary Code based Hash Embedding for Web-scale Applications

no code implementations24 Aug 2021 Bencheng Yan, Pengjie Wang, Jinquan Liu, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng

In these applications, embedding learning of categorical features is crucial to the success of deep learning models.

Recommendation Systems

Real-world Video Deblurring: A Benchmark Dataset and An Efficient Recurrent Neural Network

1 code implementation ECCV 2020 Zhihang Zhong, Ye Gao, Yinqiang Zheng, Bo Zheng, Imari Sato

Real-world video deblurring in real time still remains a challenging task due to the complexity of spatially and temporally varying blur itself and the requirement of low computational cost.

Ranked #33 on Image Deblurring on GoPro (using extra training data)

Deblurring Image Deblurring

Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search

no code implementations8 Jun 2021 Ziyu Guan, Hongchang Wu, Qingyu Cao, Hao liu, Wei Zhao, Sheng Li, Cai Xu, Guang Qiu, Jian Xu, Bo Zheng

Although a few studies use multi-agent reinforcement learning to set up a cooperative game, they still suffer the following drawbacks: (1) They fail to avoid collusion solutions where all the advertisers involved in an auction collude to bid an extremely low price on purpose.

Model Optimization Multi-agent Reinforcement Learning

4DComplete: Non-Rigid Motion Estimation Beyond the Observable Surface

1 code implementation ICCV 2021 Yang Li, Hikari Takehara, Takafumi Taketomi, Bo Zheng, Matthias Nießner

Tracking non-rigidly deforming scenes using range sensors has numerous applications including computer vision, AR/VR, and robotics.

Motion Estimation

Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multiple Data Sources

no code implementations11 Mar 2021 Guannan Geng, Qingyang Xiao, Shigan Liu, Xiaodong Liu, Jing Cheng, Yixuan Zheng, Dan Tong, Bo Zheng, Yiran Peng, Xiaomeng Huang, Kebin He, Qiang Zhang

Accordingly, a full-coverage high-resolution air pollutant dataset with timely updates and historical long-term records is essential to support both research and environmental management.


Global Daily CO$_2$ emissions for the year 2020

no code implementations3 Mar 2021 Zhu Liu, Zhu Deng, Philippe Ciais, Jianguang Tan, Biqing Zhu, Steven J. Davis, Robbie Andrew, Olivier Boucher, Simon Ben Arous, Pep Canadel, Xinyu Dou, Pierre Friedlingstein, Pierre Gentine, Rui Guo, Chaopeng Hong, Robert B. Jackson, Daniel M. Kammen, Piyu Ke, Corinne Le Quere, Crippa Monica, Greet Janssens-Maenhout, Glen Peters, Katsumasa Tanaka, Yilong Wang, Bo Zheng, Haiwang Zhong, Taochun Sun, Hans Joachim Schellnhuber

That even substantial world-wide lockdowns of activity led to a one-time decline in global CO$_2$ emissions of only 5. 4% in one year highlights the significant challenges for climate change mitigation that we face in the post-COVID era.

Atmospheric and Oceanic Physics General Economics Economics

Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension

1 code implementation ACL 2020 Bo Zheng, Haoyang Wen, Yaobo Liang, Nan Duan, Wanxiang Che, Daxin Jiang, Ming Zhou, Ting Liu

Natural Questions is a new challenging machine reading comprehension benchmark with two-grained answers, which are a long answer (typically a paragraph) and a short answer (one or more entities inside the long answer).

Graph Attention Machine Reading Comprehension +1

Adversarial Multimodal Representation Learning for Click-Through Rate Prediction

no code implementations7 Mar 2020 Xiang Li, Chao Wang, Jiwei Tan, Xiaoyi Zeng, Dan Ou, Bo Zheng

Finally, we achieve the multimodal item representations by combining both modality-specific and modality-invariant representations.

Click-Through Rate Prediction Representation Learning

RPM-Oriented Query Rewriting Framework for E-commerce Keyword-Based Sponsored Search

no code implementations28 Oct 2019 Xiuying Chen, Daorui Xiao, Shen Gao, Guojun Liu, Wei. Lin, Bo Zheng, Dongyan Zhao, Rui Yan

Sponsored search optimizes revenue and relevance, which is estimated by Revenue Per Mille (RPM).

A bi-diffusion based layer-wise sampling method for deep learning in large graphs

no code implementations25 Sep 2019 Yu He, Shiyang Wen, Wenjin Wu, Yan Zhang, Siran Yang, Yuan Wei, Di Zhang, Guojie Song, Wei Lin, Liang Wang, Bo Zheng

The Graph Convolutional Network (GCN) and its variants are powerful models for graph representation learning and have recently achieved great success on many graph-based applications.

Graph Representation Learning

A Minimax Game for Instance based Selective Transfer Learning

no code implementations1 Jul 2019 Bo wang, Minghui Qiu, Xisen Wang, Yaliang Li, Yu Gong, Xiaoyi Zeng, Jung Huang, Bo Zheng, Deng Cai, Jingren Zhou

To the best of our knowledge, this is the first to build a minimax game based model for selective transfer learning.

Retrieval Text Retrieval +1

An AMR Aligner Tuned by Transition-based Parser

1 code implementation EMNLP 2018 Yijia Liu, Wanxiang Che, Bo Zheng, Bing Qin, Ting Liu

In this paper, we propose a new rich resource enhanced AMR aligner which produces multiple alignments and a new transition system for AMR parsing along with its oracle parser.

AMR Parsing POS +1

The HIT-SCIR System for End-to-End Parsing of Universal Dependencies

no code implementations CONLL 2017 Wanxiang Che, Jiang Guo, Yuxuan Wang, Bo Zheng, Huaipeng Zhao, Yang Liu, Dechuan Teng, Ting Liu

Our system includes three pipelined components: \textit{tokenization}, \textit{Part-of-Speech} (POS) \textit{tagging} and \textit{dependency parsing}.

Dependency Parsing Information Retrieval +5

Robust 3D Features for Matching between Distorted Range Scans Captured by Moving Systems

no code implementations CVPR 2014 Xiangqi Huang, Bo Zheng, Takeshi Masuda, Katsushi Ikeuchi

Our feature description is designed as two steps: 1) we normalize the detected local regions to canonical shapes for robust matching; 2) we encode each key point with multiple vectors at different Morse function values.

3D Reconstruction

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