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papers

Publications (86)

cs.IR2024

Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank

Mouxiang Chen, Chenghao Liu, Zemin Liu +2

cs.LG2026

Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy

Tian Lan, Hao Duong Le, Jinbo Li +4

cs.CE2025

LLM-Enhanced Feature Engineering for Multi-Factor Electricity Price Predictions

Haochen Xue, Chenghao Liu, Chong Zhang +9

cs.CV2021

Cross-Modal Food Retrieval: Learning a Joint Embedding of Food Images and Recipes with Semantic Consistency and Attention Mechanism

Hao Wang, Doyen Sahoo, Chenghao Liu +4

cs.IR2022

Scalar is Not Enough: Vectorization-based Unbiased Learning to Rank

Mouxiang Chen, Chenghao Liu, Zemin Liu +1

eess.IV2021

CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation

Xinru Zhang, Chenghao Liu, Ni Ou +5

cs.IR2019

Compositional Coding for Collaborative Filtering

Chenghao Liu, Tao Lu, Xin Wang +3

cs.LG2024

Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift

Mouxiang Chen, Lefei Shen, Han Fu +3

cs.LG2026

EIDOS: Latent-Space Predictive Learning for Time Series Foundation Models

Xinxing Zhou, Qingren Yao, Yiji Zhao +5

cs.CV2026

MOSS-Video-Preview: Toward Real-Time Video Understanding via Cross-Attention

Pengyu Wang, Chenkun Tan, Shaojun Zhou +18

cs.CL2024

XForecast: Evaluating Natural Language Explanations for Time Series Forecasting

Taha Aksu, Chenghao Liu, Amrita Saha +3

cs.AI2023

PyRCA: A Library for Metric-based Root Cause Analysis

Chenghao Liu, Wenzhuo Yang, Himanshu Mittal +3

cs.LG2026

OATS: Online Data Augmentation for Time Series Foundation Models

Junwei Deng, Chang Xu, Jiaqi W. Ma +3

cs.LG2025

A Picture is Worth A Thousand Numbers: Enabling LLMs Reason about Time Series via Visualization

Haoxin Liu, Chenghao Liu, B. Aditya Prakash

cs.LG2021

Node-wise Localization of Graph Neural Networks

Zemin Liu, Yuan Fang, Chenghao Liu +1

cs.LG2018

SL$^2$MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization

Yong Liu, Min Wu, Chenghao Liu +2

cs.LG2016

SOL: A Library for Scalable Online Learning Algorithms

Yue Wu, Steven C. H. Hoi, Chenghao Liu +3

cs.CV2026

VETime: Vision Enhanced Zero-Shot Time Series Anomaly Detection

Yingyuan Yang, Tian Lan, Yifei Gao +5

cs.LG2016

Online Bayesian Collaborative Topic Regression

Chenghao Liu, Tao Jin, Steven C. H. Hoi +2

cs.LG2021

DualNet: Continual Learning, Fast and Slow

Quang Pham, Chenghao Liu, Steven Hoi

cs.CL2020

UniConv: A Unified Conversational Neural Architecture for Multi-domain Task-oriented Dialogues

Hung Le, Doyen Sahoo, Chenghao Liu +2

cs.CL2025

Enhancing Cryptocurrency Sentiment Analysis with Multimodal Features

Chenghao Liu, Aniket Mahanti, Ranesh Naha +2

cs.LG2024

Unified Training of Universal Time Series Forecasting Transformers

Gerald Woo, Chenghao Liu, Akshat Kumar +3

cs.LG2022

CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting

Gerald Woo, Chenghao Liu, Doyen Sahoo +2

cs.IR2020

A^2-GCN: An Attribute-aware Attentive GCN Model for Recommendation

Fan Liu, Zhiyong Cheng, Lei Zhu +2

cs.RO2026

PACE: Phase-Aware Chunk Execution for Robot Policies with Action Chunking

Junnan Nie, Jiayi Li, Jiachen Zhang +5

cs.LG2024

Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts

Xu Liu, Juncheng Liu, Gerald Woo +7

cs.LG2025

Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Models

Xu Liu, Taha Aksu, Juncheng Liu +7

cs.AI2021

Modeling Dynamic Attributes for Next Basket Recommendation

Yongjun Chen, Jia Li, Chenghao Liu +4

cs.LG2024

Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

Qingxiang Liu, Xu Liu, Chenghao Liu +2

cs.LG2019

Malicious URL Detection using Machine Learning: A Survey

Doyen Sahoo, Chenghao Liu, Steven C. H. Hoi

cs.LG2020

Feature Interaction-aware Graph Neural Networks

Kaize Ding, Yichuan Li, Jundong Li +2

cs.CV2025

MSNav: Zero-Shot Vision-and-Language Navigation with Dynamic Memory and LLM Spatial Reasoning

Chenghao Liu, Zhimu Zhou, Jiachen Zhang +3

cs.AI2023

Continual Learning, Fast and Slow

Quang Pham, Chenghao Liu, Steven C. H. Hoi

cs.CV2019

Learning Cross-Modal Embeddings with Adversarial Networks for Cooking Recipes and Food Images

Hao Wang, Doyen Sahoo, Chenghao Liu +2

cs.LG2023

ULTRA-DP: Unifying Graph Pre-training with Multi-task Graph Dual Prompt

Mouxiang Chen, Zemin Liu, Chenghao Liu +3

cs.LG2026

ARFBench: Benchmarking Time Series Question Answering Ability for Software Incident Response

Stephan Xie, Ben Cohen, Mononito Goswami +6

cs.LG2023

Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain

Gerald Woo, Chenghao Liu, Akshat Kumar +1

cs.LG2026

It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks

Zhongzheng Qiao, Sheng Pan, Anni Wang +7

cs.LG2026

Toto 2.0: Time Series Forecasting Enters the Scaling Era

Emaad Khwaja, Chris Lettieri, Gerald Woo +10

cs.LG2026

Moirai 2.0: When Less Is More for Time Series Forecasting

Chenghao Liu, Taha Aksu, Juncheng Liu +7

cs.AI2023

LogAI: A Library for Log Analytics and Intelligence

Qian Cheng, Amrita Saha, Wenzhuo Yang +3

cs.LG2023

OTW: Optimal Transport Warping for Time Series

Fabian Latorre, Chenghao Liu, Doyen Sahoo +1

cs.LG2026

Post-Training in Time Series Foundation Models: A Unifying Framework

Shifeng Xie, Ambroise Odonnat, Zehao Xiao +7

cs.LG2022

Continual Normalization: Rethinking Batch Normalization for Online Continual Learning

Quang Pham, Chenghao Liu, Steven Hoi

cs.SD2026

MOSS-Audio Technical Report

Chen Yang, Chufan Yu, Hanfu Chen +27

cs.LG2025

ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models

Bosong Huang, Ming Jin, Yuxuan Liang +5

cs.LG2024

GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation

Taha Aksu, Gerald Woo, Juncheng Liu +5

cs.LG2024

CompeteSMoE -- Effective Training of Sparse Mixture of Experts via Competition

Quang Pham, Giang Do, Huy Nguyen +8

cs.LG2023

Learning Deep Time-index Models for Time Series Forecasting

Gerald Woo, Chenghao Liu, Doyen Sahoo +2

cs.CL2024

PEMT: Multi-Task Correlation Guided Mixture-of-Experts Enables Parameter-Efficient Transfer Learning

Zhisheng Lin, Han Fu, Chenghao Liu +2

cs.AI2026

Generative Retrieval via Diffusion Transformer with Metric-Ordered Sequence Training and Hybrid-Policy Preference Optimization

Chenghao Liu, Yu Zhang, Zhongtao Jiang +7

cs.LG2023

HyperRouter: Towards Efficient Training and Inference of Sparse Mixture of Experts

Giang Do, Khiem Le, Quang Pham +7

cs.LG2026

TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models

Hongkai Li, Shifeng Xie, Lefei Shen +7

cs.LG2024

UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting

Juncheng Liu, Chenghao Liu, Gerald Woo +4

cs.LG2020

Graph Prototypical Networks for Few-shot Learning on Attributed Networks

Kaize Ding, Jianling Wang, Jundong Li +3

cs.LG2026

Achieving Time Series Reasoning Requires Rethinking Model Design, Tasks Formulation, and Evaluation

Yaxuan Kong, Yiyuan Yang, Shiyu Wang +7

cs.LG2023

HINormer: Representation Learning On Heterogeneous Information Networks with Graph Transformer

Qiheng Mao, Zemin Liu, Chenghao Liu +1

cs.LG2025

AXIS: Explainable Time Series Anomaly Detection with Large Language Models

Tian Lan, Hao Duong Le, Jinbo Li +4

cs.LG2022

ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

Gerald Woo, Chenghao Liu, Doyen Sahoo +2

cs.CV2020

MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images with Latent Variable Model

Han Fu, Rui Wu, Chenghao Liu +1

cs.LG2025

A Survey on Diffusion Models for Time Series and Spatio-Temporal Data

Yiyuan Yang, Ming Jin, Haomin Wen +9

cs.AI2026

VFEAgent: A Multimodal Agent Framework for End-to-End Automated Finite Element Analysis

Jiachen Zhang, Junyi Lao, Chenghao Liu +5

cs.LG2025

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting

Lefei Shen, Mouxiang Chen, Han Fu +5

cs.CV2025

TTF-VLA: Temporal Token Fusion via Pixel-Attention Integration for Vision-Language-Action Models

Chenghao Liu, Jiachen Zhang, Chengxuan Li +4

cs.LG2024

Incremental Label Distribution Learning with Scalable Graph Convolutional Networks

Ziqi Jia, Xiaoyang Qu, Chenghao Liu +1

cs.LG2022

Learning Fast and Slow for Online Time Series Forecasting

Quang Pham, Chenghao Liu, Doyen Sahoo +1

cs.LG2023

AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges

Qian Cheng, Doyen Sahoo, Amrita Saha +6

cs.CV2025

MolCLIP: A Molecular-Auxiliary CLIP Framework for Identifying Drug Mechanism of Action Based on Time-Lapsed Mitochondrial Images

Fengqian Pang, Chunyue Lei, Hongfei Zhao +4

cs.CV2024

MTSA-SNN: A Multi-modal Time Series Analysis Model Based on Spiking Neural Network

Chengzhi Liu, Zheng Tao, Zihong Luo +1

cs.LG2024

Advancing Graph Representation Learning with Large Language Models: A Comprehensive Survey of Techniques

Qiheng Mao, Zemin Liu, Chenghao Liu +2

cs.LG2021

Merlion: A Machine Learning Library for Time Series

Aadyot Bhatnagar, Paul Kassianik, Chenghao Liu +20

cs.CV2020

Adaptive Task Sampling for Meta-Learning

Chenghao Liu, Zhihao Wang, Doyen Sahoo +3

cs.LG2025

Multi-Scale Finetuning for Encoder-based Time Series Foundation Models

Zhongzheng Qiao, Chenghao Liu, Yiming Zhang +6

cs.AI2026

CloudCons: A Comprehensive End-to-End Benchmark for Cloud Resource Consolidation

Xiaobin Zhang, Lefei Shen, Mouxiang Chen +6

cs.LG2023

Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data

Devansh Arpit, Matthew Fernandez, Itai Feigenbaum +11

cs.CV2025

VisionTS++: Cross-Modal Time Series Foundation Model with Continual Pre-trained Vision Backbones

Lefei Shen, Mouxiang Chen, Xu Liu +5

cs.LG2024

Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction

Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng +9

cs.CV2023

Unsupervised Brain Tumor Segmentation with Image-based Prompts

Xinru Zhang, Ni Ou, Chenghao Liu +3

cs.LG2020

Bilevel Continual Learning

Quang Pham, Doyen Sahoo, Chenghao Liu +1

cs.CV2025

VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters

Mouxiang Chen, Lefei Shen, Zhuo Li +3

cs.CL2019

Reference Network for Neural Machine Translation

Han Fu, Chenghao Liu, Jianling Sun

cs.RO2026

What Frozen VLAs Already Know About Success: A Probing Study of Value-Like Structure in Foundation Robot Policies

Jiachen Zhang, Junnan Nie, Junyi Lao +4

cs.LG2026

GDformer: Going Beyond Subsequence Isolation for Multivariate Time Series Anomaly Detection

Qingxiang Liu, Xiaoliang Luo, Chenghao Liu +5

cs.LG2023

FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer

Chenghao Liu, Xiaoyang Qu, Jianzong Wang +1

cs.LG2020

Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling

Jianwen Yin, Chenghao Liu, Weiqing Wang +2