no code implementations • 25 Jul 2024 • Xingcheng Xu, Zibo Zhao, Haipeng Zhang, Yanqing Yang
Large language models (LLMs) have demonstrated impressive versatility across numerous tasks, yet their generalization capabilities remain poorly understood.
1 code implementation • 8 Jun 2024 • Zhaoru Ke, Hang Yu, Jianguo Li, Haipeng Zhang
Current directed graph embedding methods build upon undirected techniques but often inadequately capture directed edge information, leading to challenges such as: (1) Suboptimal representations for nodes with low in/out-degrees, due to the insufficient neighbor interactions; (2) Limited inductive ability for representing new nodes post-training; (3) Narrow generalizability, as training is overly coupled with specific tasks.
no code implementations • 29 May 2024 • Yao Zhao, Zhining Liu, Tianchi Cai, Haipeng Zhang, Chenyi Zhuang, Jinjie Gu
Using both synthetic and industrial datasets, we first show how this widely coexisted ranking bias deteriorates the performance of the existing position bias estimation methods.
1 code implementation • 25 May 2024 • Ying Zhang, Xiaofeng Li, Zhaoyang Liu, Haipeng Zhang
The life trajectories of notable people have been studied to pinpoint the times and places of significant events such as birth, death, education, marriage, competition, work, speeches, scientific discoveries, artistic achievements, and battles.
no code implementations • 10 May 2024 • Xiaocong Du, Haipeng Zhang
Achieving gender equality is a pivotal factor in realizing the UN's Global Goals for Sustainable Development.
no code implementations • 8 Jan 2024 • Ran Li, Haipeng Zhang, Mingyang Sun, Fei Teng, Can Wan, Salvador Pineda, Georges Kariniotakis
This paper first elaborates on the mismatch between more accurate forecasts and more optimal decisions in the power system caused by statistical-based learning (SBL) and explains how DOL resolves this problem.
no code implementations • 21 Dec 2023 • Haipeng Zhang, Ran Li, Mingyang Sun, Teng Fei
However, the implementation of decision loss in power systems faces challenges in 1) accommodating multi-stage decision-making problems where upstream optimality cannot guarantee final optimality; 2) adapting to dynamic environments such as changing parameters and nature of the problem like continuous or discrete optimization tasks.
no code implementations • 15 Dec 2023 • Yao Zhao, Haipeng Zhang, Shiwei Lyu, Ruiying Jiang, Jinjie Gu, Guannan Zhang
Uplift modeling is widely used in performance marketing to estimate effects of promotion campaigns (e. g., increase of customer retention rate).
1 code implementation • 16 Aug 2023 • Xingcheng Xu, Zihao Pan, Haipeng Zhang, Yanqing Yang
Large language models (LLMs) have achieved remarkable proficiency on solving diverse problems.
1 code implementation • 17 Jul 2023 • Kai Peng, Ying Zhang, Shuai Ling, Zhaoru Ke, Haipeng Zhang
Although news articles contain travel information of celebrities, it is not possible to perform large-scale and network-wise analysis due to the lack of automatic itinerary detection tools.
1 code implementation • International Conference on Learning Representations 2023 • Ziyue Li, Kan Ren, Xinyang Jiang, Yifei Shen, Haipeng Zhang, Dongsheng Li
Moreover, our method is highly efficient and achieves more than 1000 times training speedup compared to the conventional DG methods with fine-tuning a pretrained model.
Ranked #1 on
Domain Generalization
on PACS
no code implementations • 21 Mar 2023 • Haipeng Zhang, Ran Li, Yan Chen, Zhongda Chu, Mingyang Sun, Fei Teng
The objective-based forecasting considers the asymmetric and non-linear impacts of forecasting errors on decision objectives, thus improving the effectiveness of its downstream decision-making process.
1 code implementation • 1 Feb 2023 • Zihao Pan, Kai Peng, Shuai Ling, Haipeng Zhang
We open-source a more balanced multi-character dataset from an official source together with our code, hoping to help future research promoting gender equality.
no code implementations • 9 Mar 2022 • Ziyue Li, Kan Ren, Xinyang Jiang, Bo Li, Haipeng Zhang, Dongsheng Li
Fine-tuning pretrained models is a common practice in domain generalization (DG) tasks.
Ranked #10 on
Domain Generalization
on TerraIncognita
no code implementations • 29 Sep 2021 • Ziyue Li, Kan Ren, Xinyang Jiang, Mingzhe Han, Haipeng Zhang, Dongsheng Li
Real-world data is often generated by some complex distribution, which can be approximated by a composition of multiple simpler distributions.
no code implementations • 6 Sep 2021 • Kaihao Guo, Tianpei Jiang, Haipeng Zhang
Event extraction is a classic task in natural language processing with wide use in handling large amount of yet rapidly growing financial, legal, medical, and government documents which often contain multiple events with their elements scattered and mixed across the documents, making the problem much more difficult.
no code implementations • 25 May 2021 • Shiwei Lyu, Shuai Ling, Kaihao Guo, Haipeng Zhang, Kunpeng Zhang, Suting Hong, Qing Ke, Jinjie Gu
Predicting the start-ups that will eventually succeed is essentially important for the venture capital business and worldwide policy makers, especially at an early stage such that rewards can possibly be exponential.
1 code implementation • 6 Feb 2021 • Haipeng Zhang, Zhong Cao, Ziang Yan, ChangShui Zhang
For visual object recognition tasks, the illumination variations can cause distinct changes in object appearance and thus confuse the deep neural network based recognition models.
Ranked #1 on
Traffic Sign Recognition
on TopLogo-10