| 2026 | AAAI | A Visualized Framework for Event Cooperation with Generative Agents. | Yuyang Tian, Shunqiang Mao, Wenchang Gao, Lanlan Qiu, Tianxing He |
| 2026 | ACL | ChatAnime: Towards User-Centered Emotional Support in LLM-based Virtual Character Chat. | Lanlan Qiu, Sophia Xiao Pu, Yeqi Feng, Wenchang Gao, Tianxing He |
| 2026 | WWW | Pay for The Second-Best Service: A Game-Theoretic Approach against Dishonest LLM Providers. | Yuhan Cao, Yu Wang, Sitong Liu, Miao Li, Yixin Tao, Tianxing He |
| 2025 | ACL | SATA: A Paradigm for LLM Jailbreak via Simple Assistive Task Linkage. | Xiaoning Dong, Wenbo Hu, Wei Xu, Tianxing He |
| 2025 | ACL | Jailbreak Large Vision-Language Models Through Multi-Modal Linkage. | Yu Wang, Xiaofei Zhou, Yichen Wang, Geyuan Zhang, Tianxing He |
| 2025 | ICML | Towards Black-Box Membership Inference Attack for Diffusion Models. | Jingwei Li, Jing Dong, Tianxing He, Jingzhao Zhang |
| 2024 | ACL | Knowledge Crosswords: Geometric Knowledge Reasoning with Large Language Models. | Wenxuan Ding, Shangbin Feng, Yuhan Liu, Zhaoxuan Tan, Vidhisha Balachandran, Tianxing He, Yulia Tsvetkov |
| 2024 | ACL | k-SemStamp: A Clustering-Based Semantic Watermark for Detection of Machine-Generated Text. | Abe Bohan Hou, Jingyu Zhang, Yichen Wang, Daniel Khashabi, Tianxing He |
| 2024 | ACL | Stumbling Blocks: Stress Testing the Robustness of Machine-Generated Text Detectors Under Attacks. | Yichen Wang, Shangbin Feng, Abe Bohan Hou, Xiao Pu, Chao Shen, Xiaoming Liu, Yulia Tsvetkov, Tianxing He |
| 2024 | EMNLP | Style-Compress: An LLM-Based Prompt Compression Framework Considering Task-Specific Styles. | Xiao Pu, Tianxing He, Xiaojun Wan |
| 2024 | EMNLP | Can LLM Graph Reasoning Generalize beyond Pattern Memorization? | Yizhuo Zhang, Heng Wang, Shangbin Feng, Zhaoxuan Tan, Xiaochuang Han, Tianxing He, Yulia Tsvetkov |
| 2024 | ICLR | Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models. | Shangbin Feng, Weijia Shi, Yuyang Bai, Vidhisha Balachandran, Tianxing He, Yulia Tsvetkov |
| 2024 | NAACL | SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation. | Abe Bohan Hou, Jingyu Zhang, Tianxing He, Yichen Wang, Yung-Sung Chuang, Hongwei Wang, Lingfeng Shen, Benjamin Van Durme, Daniel Khashabi, Yulia Tsvetkov |
| 2024 | NAACL | LatticeGen: Hiding Generated Text in a Lattice for Privacy-Aware Large Language Model Generation on Cloud. | Mengke Zhang, Tianxing He, Tianle Wang, Lu Mi, Niloofar Mireshghallah, Binyi Chen, Hao Wang, Yulia Tsvetkov |
| 2024 | WWW | KGQuiz: Evaluating the Generalization of Encoded Knowledge in Large Language Models. | Yuyang Bai, Shangbin Feng, Vidhisha Balachandran, Zhaoxuan Tan, Shiqi Lou, Tianxing He, Yulia Tsvetkov |
| 2023 | ACL | On the Blind Spots of Model-Based Evaluation Metrics for Text Generation. | Tianxing He, Jingyu Zhang, Tianle Wang, Sachin Kumar, Kyunghyun Cho, James R. Glass, Yulia Tsvetkov |
| 2023 | EMNLP | On the Zero-Shot Generalization of Machine-Generated Text Detectors. | Xiao Pu, Jingyu Zhang, Xiaochuang Han, Yulia Tsvetkov, Tianxing He |
| 2022 | ACL | Controlling the Focus of Pretrained Language Generation Models. | Jiabao Ji, Yoon Kim, James R. Glass, Tianxing He |
| 2021 | EACL | Analyzing the Forgetting Problem in Pretrain-Finetuning of Open-domain Dialogue Response Models. | Tianxing He, Jun Liu, Kyunghyun Cho, Myle Ott, Bing Liu, James R. Glass, Fuchun Peng |
| 2021 | EACL | Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models. | Tianxing He, Bryan McCann, Caiming Xiong, Ehsan Hosseini-Asl |
| 2021 | EMNLP | Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation? | Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass |
| 2020 | ACL | Negative Training for Neural Dialogue Response Generation. | Tianxing He, James R. Glass |
| 2020 | ICASSP | An Empirical Study of Transformer-Based Neural Language Model Adaptation. | Ke Li, Zhe Liu, Tianxing He, Hongzhao Huang, Fuchun Peng, Daniel Povey, Sanjeev Khudanpur |
| 2020 | ICLR | Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity. | Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie |
| 2020 | IJCNLP | A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation. | Moin Nadeem, Tianxing He, Kyunghyun Cho, James R. Glass |
| 2019 | ICLR | Detecting Egregious Responses in Neural Sequence-to-sequence Models. | Tianxing He, James R. Glass |
| 2016 | ICASSP | Exploiting LSTM structure in deep neural networks for speech recognition. | Tianxing He, Jasha Droppo |
| 2015 | ICASSP | Recurrent neural network language model with structured word embeddings for speech recognition. | Tianxing He, Xu Xiang, Yanmin Qian, Kai Yu |
| 2015 | IJCNN | Automatic model redundancy reduction for fast back-propagation for deep neural networks in speech recognition. | Yanmin Qian, Tianxing He, Wei Deng, Kai Yu |
| 2015 | Interspeech | Paragraph vector based topic model for language model adaptation. | Wengong Jin, Tianxing He, Yanmin Qian, Kai Yu |
| 2014 | ICASSP | Reshaping deep neural network for fast decoding by node-pruning. | Tianxing He, Yuchen Fan, Yanmin Qian, Tian Tan, Kai Yu |