Tianxing He

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 51

Top Topics

Comprehensive Empirical Study

Top Venues

Publications

Yichen Wang, Shangbin Feng, Abe Bohan Hou, Xiao Pu, Chao Shen, Xiaoming Liu, Yulia Tsvetkov, Tianxing He
Stumbling Blocks: Stress Testing the Robustness of Machine-Generated Text Detectors Under Attacks. CoRR (2024)
Abe Bohan Hou, Jingyu Zhang, Yichen Wang, Daniel Khashabi, Tianxing He
k-SemStamp: A Clustering-Based Semantic Watermark for Detection of Machine-Generated Text. CoRR (2024)
Xiao Pu, Jingyu Zhang, Xiaochuang Han, Yulia Tsvetkov, Tianxing He
On the Zero-Shot Generalization of Machine-Generated Text Detectors. EMNLP (Findings) (2023)
Jingyu Zhang, James R. Glass, Tianxing He
PCFG-Based Natural Language Interface Improves Generalization for Controlled Text Generation. *SEM@ACL (2023)
Shangbin Feng, Weijia Shi, Yuyang Bai, Vidhisha Balachandran, Tianxing He, Yulia Tsvetkov
CooK: Empowering General-Purpose Language Models with Modular and Collaborative Knowledge. CoRR (2023)
Xiao Pu, Jingyu Zhang, Xiaochuang Han, Yulia Tsvetkov, Tianxing He
On the Zero-Shot Generalization of Machine-Generated Text Detectors. CoRR (2023)
Tianxing He, Jingyu Zhang, Tianle Wang, Sachin Kumar, Kyunghyun Cho, James R. Glass, Yulia Tsvetkov
On the Blind Spots of Model-Based Evaluation Metrics for Text Generation. ACL (1) (2023)
Wenxuan Ding, Shangbin Feng, Yuhan Liu, Zhaoxuan Tan, Vidhisha Balachandran, Tianxing He, Yulia Tsvetkov
Knowledge Crosswords: Geometric Reasoning over Structured Knowledge with Large Language Models. CoRR (2023)
Yuyang Bai, Shangbin Feng, Vidhisha Balachandran, Zhaoxuan Tan, Shiqi Lou, Tianxing He, Yulia Tsvetkov
KGQuiz: Evaluating the Generalization of Encoded Knowledge in Large Language Models. CoRR (2023)
Mengke Zhang, Tianxing He, Tianle Wang, Lu Mi, Fatemehsadat Mireshghallah, Binyi Chen, Hao Wang, Yulia Tsvetkov
LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud. CoRR (2023)
Lu Mi, Trung Le, Tianxing He, Eli Shlizerman, Uygar Sümbül
Learning Time-Invariant Representations for Individual Neurons from Population Dynamics. NeurIPS (2023)
Heng Wang, Shangbin Feng, Tianxing He, Zhaoxuan Tan, Xiaochuang Han, Yulia Tsvetkov
Can Language Models Solve Graph Problems in Natural Language? CoRR (2023)
Yike Wang, Shangbin Feng, Heng Wang, Weijia Shi, Vidhisha Balachandran, Tianxing He, Yulia Tsvetkov
Resolving Knowledge Conflicts in Large Language Models. CoRR (2023)
Heng Wang, Shangbin Feng, Tianxing He, Zhaoxuan Tan, Xiaochuang Han, Yulia Tsvetkov
Can Language Models Solve Graph Problems in Natural Language? NeurIPS (2023)
Abe Bohan Hou, Jingyu Zhang, Tianxing He, Yichen Wang, Yung-Sung Chuang, Hongwei Wang, Lingfeng Shen, Benjamin Van Durme, Daniel Khashabi, Yulia Tsvetkov
SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation. CoRR (2023)
Lu Mi, Trung Le, Tianxing He, Eli Shlizerman, Uygar Sümbül
Learning Time-Invariant Representations for Individual Neurons from Population Dynamics. CoRR (2023)
Rui Zhou, Hongchao Xu, Hao Zhang, Jie Zhang, Miao Liu, Tianxing He, Jun Gao, Chunlin Li
Quantifying the Relationship between 2D/3D Building Patterns and Land Surface Temperature: Study on the Metropolitan Shanghai. Remote. Sens. 14 (16) (2022)
Tianxing He, Jingyu Zhang, Tianle Wang, Sachin Kumar, Kyunghyun Cho, James R. Glass, Yulia Tsvetkov
On the Blind Spots of Model-Based Evaluation Metrics for Text Generation. CoRR (2022)
Yilin Yang, Tianxing He, Yang Feng, Shaoying Liu, Baowen Xu
Mining Python fix patterns via analyzing fine-grained source code changes. Empir. Softw. Eng. 27 (2) (2022)
Yilin Yang, Tianxing He, Zhilong Xia, Yang Feng
A comprehensive empirical study on bug characteristics of deep learning frameworks. Inf. Softw. Technol. 151 (2022)
Jiabao Ji, Yoon Kim, James R. Glass, Tianxing He
Controlling the Focus of Pretrained Language Generation Models. ACL (Findings) (2022)
Jiabao Ji, Yoon Kim, James R. Glass, Tianxing He
Controlling the Focus of Pretrained Language Generation Models. CoRR (2022)
Jingyu Zhang, James R. Glass, Tianxing He
PCFG-based Natural Language Interface Improves Generalization for Controlled Text Generation. CoRR (2022)
Lu Mi, Tianxing He, Core Francisco Park, Hao Wang, Yue Wang, Nir Shavit
Revisiting Latent-Space Interpolation via a Quantitative Evaluation Framework. CoRR (2021)
Tianxing He, Bryan McCann, Caiming Xiong, Ehsan Hosseini-Asl
Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models. CoRR (2021)
Tianxing He, Bryan McCann, Caiming Xiong, Ehsan Hosseini-Asl
Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models. EACL (2021)
Tianxing He, Jun Liu, Kyunghyun Cho, Myle Ott, Bing Liu, James R. Glass, Fuchun Peng
Analyzing the Forgetting Problem in Pretrain-Finetuning of Open-domain Dialogue Response Models. EACL (2021)
Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass
Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation? EMNLP (1) (2021)
Tianxing He, Kyunghyun Cho, James R. Glass
An Empirical Study on Few-shot Knowledge Probing for Pretrained Language Models. CoRR (2021)
Ke Li, Zhe Liu, Tianxing He, Hongzhao Huang, Fuchun Peng, Daniel Povey, Sanjeev Khudanpur
An Empirical Study of Transformer-Based Neural Language Model Adaptation. ICASSP (2020)
Tianxing He, James R. Glass
Negative Training for Neural Dialogue Response Generation. ACL (2020)
Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie
Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity. ICLR (2020)
Moin Nadeem, Tianxing He, Kyunghyun Cho, James R. Glass
A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation. CoRR (2020)
Seunghak Yu, Tianxing He, James R. Glass
Constructing a Knowledge Graph from Unstructured Documents without External Alignment. CoRR (2020)
Moin Nadeem, Tianxing He, Kyunghyun Cho, James R. Glass
A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation. AACL/IJCNLP (2020)
Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie
Analysis of Gradient Clipping and Adaptive Scaling with a Relaxed Smoothness Condition. CoRR (2019)
Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass
Quantifying Exposure Bias for Neural Language Generation. CoRR (2019)
Tianxing He, Shengcheng Yu, Ziyuan Wang, Jieqiong Li, Zhenyu Chen
From Data Quality to Model Quality: An Exploratory Study on Deep Learning. Internetware (2019)
Tianxing He, Shengcheng Yu, Ziyuan Wang, Jieqiong Li, Zhenyu Chen
From Data Quality to Model Quality: an Exploratory Study on Deep Learning. CoRR (2019)
Tianxing He, James R. Glass
Detecting Egregious Responses in Neural Sequence-to-sequence Models. ICLR (Poster) (2019)
Tianxing He, James R. Glass
Negative Training for Neural Dialogue Response Generation. CoRR (2019)
Tianxing He, Jun Liu, Kyunghyun Cho, Myle Ott, Bing Liu, James R. Glass, Fuchun Peng
Mix-review: Alleviate Forgetting in the Pretrain-Finetune Framework for Neural Language Generation Models. CoRR (2019)
Tianxing He, James R. Glass
Detecting egregious responses in neural sequence-to-sequence models. CoRR (2018)
Yue Wu, Tianxing He, Zhehuai Chen, Yanmin Qian, Kai Yu
Multi-view LSTM Language Model with Word-Synchronized Auxiliary Feature for LVCSR. CCL (2017)
Tianxing He, Yu Zhang, Jasha Droppo, Kai Yu
On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation. CoRR (2016)
Tianxing He, Jasha Droppo
Exploiting LSTM structure in deep neural networks for speech recognition. ICASSP (2016)
Tianxing He, Yu Zhang, Jasha Droppo, Kai Yu
On training bi-directional neural network language model with noise contrastive estimation. ISCSLP (2016)
Wengong Jin, Tianxing He, Yanmin Qian, Kai Yu
Paragraph vector based topic model for language model adaptation. INTERSPEECH (2015)
Tianxing He, Xu Xiang, Yanmin Qian, Kai Yu
Recurrent neural network language model with structured word embeddings for speech recognition. ICASSP (2015)
Yongbin You, Yanmin Qian, Tianxing He, Kai Yu
An investigation on DNN-derived bottleneck features for GMM-HMM based robust speech recognition. ChinaSIP (2015)
Yanmin Qian, Tianxing He, Wei Deng, Kai Yu
Automatic model redundancy reduction for fast back-propagation for deep neural networks in speech recognition. IJCNN (2015)
Tianxing He, Yuchen Fan, Yanmin Qian, Tian Tan, Kai Yu
Reshaping deep neural network for fast decoding by node-pruning. ICASSP (2014)