Zekun Li | DeepAI

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∙ 09/16/2023

Enhancing Large Language Model Induced Task-Oriented Dialogue Systems Through Look-Forward Motivated Goals

Recently, the development of large language models (LLMs) has been signi...

0 Zhiyuan Hu, et al. ∙

∙ 08/17/2023

Do you really follow me? Adversarial Instructions for Evaluating the Robustness of Large Language Models

Large Language Models (LLMs) have shown remarkable proficiency in follow...

0 Zekun Li, et al. ∙

∙ 06/29/2023

The mapKurator System: A Complete Pipeline for Extracting and Linking Text from Historical Maps

Scanned historical maps in libraries and archives are valuable repositor...

0 Jina Kim, et al. ∙

∙ 06/05/2023

Shoal: Improving DAG-BFT Latency And Robustness

The Narwhal system is a state-of-the-art Byzantine fault-tolerant scalab...

0 Alexander Spiegelman, et al. ∙

∙ 04/03/2023

Learning Anchor Transformations for 3D Garment Animation

This paper proposes an anchor-based deformation model, namely AnchorDEF,...

0 Fang Zhao, et al. ∙

∙ 03/20/2023

I2Edit: Towards Multi-turn Interactive Image Editing via Dialogue

Although there have been considerable research efforts on controllable f...

0 Xing Cui, et al. ∙

∙ 02/22/2023

Guiding Large Language Models via Directional Stimulus Prompting

We introduce a new framework, Directional Stimulus Prompting, that uses ...

0 Zekun Li, et al. ∙

∙ 10/21/2022

SpaBERT: A Pretrained Language Model from Geographic Data for Geo-Entity Representation

Named geographic entities (geo-entities for short) are the building bloc...

0 Zekun Li, et al. ∙

∙ 10/13/2022

Explanations from Large Language Models Make Small Reasoners Better

Integrating free-text explanations to in-context learning of large langu...

12 Shiyang Li, et al. ∙

∙ 10/09/2022

Controllable Dialogue Simulation with In-Context Learning

Building dialogue systems requires a large corpus of annotated dialogues...

8 Zekun Li, et al. ∙

∙ 08/09/2022

Limitations of Language Models in Arithmetic and Symbolic Induction

Recent work has shown that large pretrained Language Models (LMs) can no...

3 Jing Qian, et al. ∙

∙ 07/13/2022

Eliminating Gradient Conflict in Reference-based Line-art Colorization

Reference-based line-art colorization is a challenging task in computer ...

11 Zekun Li, et al. ∙

∙ 03/14/2022

Block-STM: Scaling Blockchain Execution by Turning Ordering Curse to a Performance Blessing

Block-STM is a parallel execution engine for smart contracts, built arou...

0 Rati Gelashvili, et al. ∙

∙ 12/12/2021

Synthetic Map Generation to Provide Unlimited Training Data for Historical Map Text Detection

Many historical map sheets are publicly available for studies that requi...

0 Zekun Li, et al. ∙

∙ 12/03/2021

An Automatic Approach for Generating Rich, Linked Geo-Metadata from Historical Map Images

Historical maps contain detailed geographic information difficult to fin...

0 Zekun Li, et al. ∙

∙ 10/03/2021

Be Aware of Your Leaders

Advances in blockchains have influenced the State-Machine-Replication (S...

0 Shir Cohen, et al. ∙

∙ 05/25/2021

GraphFM: Graph Factorization Machines for Feature Interaction Modeling

Factorization machine (FM) is a prevalent approach to modeling pairwise ...

7 Zekun Li, et al. ∙

∙ 04/07/2021

DyGCN: Dynamic Graph Embedding with Graph Convolutional Network

Graph embedding, aiming to learn low-dimensional representations (aka. e...

43 Zeyu Cui, et al. ∙

∙ 12/12/2020

PoP-Net: Pose over Parts Network for Multi-Person 3D Pose Estimation from a Depth Image

In this paper, a real-time method called PoP-Net is proposed to predict ...

0 Yuliang Guo, et al. ∙

∙ 12/10/2020

Cold-start Sequential Recommendation via Meta Learner

This paper explores meta-learning in sequential recommendation to allevi...

0 Yujia Zheng, et al. ∙

∙ 11/13/2020

Heterogeneous Graph Collaborative Filtering

Graph-based collaborative filtering (CF) algorithms have gained increasi...

5 Zekun Li, et al. ∙

∙ 09/21/2020

DGTN: Dual-channel Graph Transition Network for Session-based Recommendation

The task of session-based recommendation is to predict user actions base...

0 Yujia Zheng, et al. ∙

∙ 10/12/2019

Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction

Click-through rate (CTR) prediction is an essential task in web applicat...

0 Zekun Li, et al. ∙

∙ 07/31/2019

Semi-supervised Compatibility Learning Across Categories for Clothing Matching

Learning the compatibility between fashion items across categories is a ...

0 Zekun Li, et al. ∙

∙ 02/21/2019

Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks

With the rapid development of fashion market, the customers' demands of ...

0 Zeyu Cui, et al. ∙

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