Huan Zhao

Translation-Based Implicit Annotation Projection for Zero-Shot Cross-Lingual Event Argument Extraction

2022 · Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Zero-shot cross-lingual event argument extraction (EAE) is a challenging yet practical problem in Information Extraction. Most previous works heavily rely on external structured linguistic features, which are not easily accessible in real-world scenarios. This paper …

TSUP Speaker Diarization System for Conversational Short-phrase Speaker Diarization Challenge

2022 · arXiv (Cornell University)

This paper describes the TSUP team's submission to the ISCSLP 2022 conversational short-phrase speaker diarization (CSSD) challenge which particularly focuses on short-phrase conversations with a new evaluation metric called conversational diarization error rate (CDER). In …

Ensuring Fairness in Federated Learning Services: Innovative Approaches to Client Selection, Scheduling, and Rewards

2024

Federated Learning (FL) Services enable customers (requesters) to outsource their FL tasks to the FL service provider, who will recruit a group of clients with appropriate datasets to complete the FL task. For a given …

Large Language Model-Based Operation Ticket Generation: A Case Study

2025

The power dispatch task is becoming increasingly complex since more and more factors need to be considered, such as weather conditions, energy storage, and the electricity market. To ensure the safe operation of power dispatch, …

Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks

2017

Heterogeneous Information Network (HIN) is a natural and general representation of data in modern large commercial recommender systems which involve heterogeneous types of data. HIN based recommenders face two problems: how to represent the high-level …

Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba

2018

Recommender systems (RSs) have been the most important technology for increasing the business in Taobao, the largest online consumer-to-consumer (C2C) platform in China. There are three major challenges facing RS in Taobao: scalability, sparsity and …

Multi-Interest Network with Dynamic Routing for Recommendation at Tmall

2019

Industrial recommender systems have embraced deep learning algorithms for building intelligent systems to make accurate recommendations. At its core, deep learning offers powerful ability for learning representations from data, especially for user and item representations. …

Behavior sequence transformer for e-commerce recommendation in Alibaba

2019

Deep learning based methods have been widely used in industrial recommendation systems (RSs). Previous works adopt an Embedding&MLP paradigm: raw features are embedded into low-dimensional vectors, which are then fed on to MLP for final …