21 citations · 86 across the 12 of their papers we have counts for
12 papers
Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting
Zhen Qin, Rolf Jagerman, Kai Hui +9
Ranking documents using Large Language Models (LLMs) by directly feeding the query and candidate documents into the prompt is an interesting and practical problem. However, researc…
SLiC-HF: Sequence Likelihood Calibration with Human Feedback
Yao Zhao, Rishabh Joshi, Tianqi Liu +3
Learning from human feedback has been shown to be effective at aligning language models with human preferences. Past work has often relied on Reinforcement Learning from Human Feed…
Do Not Blindly Imitate the Teacher: Using Perturbed Loss for Knowledge Distillation
Rongzhi Zhang, Jiaming Shen, Tianqi Liu +4
Knowledge distillation is a popular technique to transfer knowledge from large teacher models to a small student model. Typically, the student learns to imitate the teacher by mini…
Clustering High-dimensional Data via Feature Selection
Tianqi Liu, Yu Lu, Biqing Zhu +1
High-dimensional clustering analysis is a challenging problem in statistics and machine learning, with broad applications such as the analysis of microarray data and RNA-seq data.…
All Birds with One Stone: Multi-task Text Classification for Efficient Inference with One Forward Pass
Jiaxin Huang, Tianqi Liu, Jialu Liu +3
Multi-Task Learning (MTL) models have shown their robustness, effectiveness, and efficiency for transferring learned knowledge across tasks. In real industrial applications such as…
NewsEmbed: Modeling News through Pre-trained Document Representations
Jialu Liu, Tianqi Liu, Cong Yu
Effectively modeling text-rich fresh content such as news articles at document-level is a challenging problem. To ensure a content-based model generalize well to a broad range of a…
Training ELECTRA Augmented with Multi-word Selection
Jiaming Shen, Jialu Liu, Tianqi Liu +2
Pre-trained text encoders such as BERT and its variants have recently achieved state-of-the-art performances on many NLP tasks. While being effective, these pre-training methods ty…
A Deep Probabilistic Model for Customer Lifetime Value Prediction
Xiaojing Wang, Tianqi Liu, Jingang Miao
Accurate predictions of customers' future lifetime value (LTV) given their attributes and past purchase behavior enables a more customer-centric marketing strategy. Marketers can s…
BERT for Large-scale Video Segment Classification with Test-time Augmentation
Tianqi Liu, Qizhan Shao
This paper presents our approach to the third YouTube-8M video understanding competition that challenges par-ticipants to localize video-level labels at scale to the pre-cise time…
Constrained-size Tensorflow Models for YouTube-8M Video Understanding Challenge
Tianqi Liu, Bo Liu
This paper presents our 7th place solution to the second YouTube-8M video understanding competition which challenges participates to build a constrained-size model to classify mill…
Characterizing Spatiotemporal Transcriptome of Human Brain via Low Rank Tensor Decomposition
Tianqi Liu, Ming Yuan, Hongyu Zhao
Spatiotemporal gene expression data of the human brain offer insights on the spa- tial and temporal patterns of gene regulation during brain development. Most existing methods for…
Ultrahigh Dimensional Feature Selection via Kernel Canonical Correlation Analysis
Tianqi Liu, Kuang-Yao Lee, Hongyu Zhao
High-dimensional variable selection is an important issue in many scientific fields, such as genomics. In this paper, we develop a sure independence feature screening pro- cedure b…