Data Boost: Text Data Augmentation Through Reinforcement Learning Guided Conditional Generation. - Ruibo Liu; Guangxuan Xu; Chenyan Jia; Weicheng Ma; Lili Wang; Soroush Vosoughi (EMNLP (1), 2020)

Enhanced Offensive Language Detection Through Data Augmentation. - Ruibo Liu; Guangxuan Xu; Soroush Vosoughi (CoRR, 2020)

Mitigating Political Bias in Language Models through Reinforced Calibration. - Ruibo Liu; Chenyan Jia; Jason Wei; Guangxuan Xu; Lili Wang; Soroush Vosoughi (AAAI, 2021)

On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark. - Hao Sun 012; Guangxuan Xu; Jiawen Deng; Jiale Cheng; Chujie Zheng; Hao Zhou 012; Nanyun Peng 001; Xiaoyan Zhu 001; Minlie Huang (ACL (Findings), 2022)

EnDex: Evaluation of Dialogue Engagingness at Scale. - Guangxuan Xu; Ruibo Liu; Fabrice Harel-Canada; Nischal Reddy Chandra; Nanyun Peng 001 (EMNLP (Findings), 2022)

Non-Parallel Text Style Transfer with Self-Parallel Supervision. - Ruibo Liu; Chongyang Gao; Chenyan Jia; Guangxuan Xu; Soroush Vosoughi (ICLR, 2022)

Quantifying and alleviating political bias in language models. - Ruibo Liu; Chenyan Jia; Jason Wei; Guangxuan Xu; Soroush Vosoughi (Artif. Intell., 2022)

Can Model Compression Improve NLP Fairness. - Guangxuan Xu; Qingyuan Hu (CoRR, 2022)

NECE: Narrative Event Chain Extraction Toolkit. - Guangxuan Xu; Paulina Toro Isaza; Moshi Li; Akintoye Oloko; Bingsheng Yao; Aminat Adebiyi; Yufang Hou 001; Nanyun Peng 001; Dakuo Wang (CoRR, 2022)

Are Fairy Tales Fair? Analyzing Gender Bias in Temporal Narrative Event Chains of Children's Fairy Tales. - Paulina Toro Isaza; Guangxuan Xu; Toye Oloko; Yufang Hou 001; Nanyun Peng 001; Dakuo Wang (ACL (1), 2023)

Are Fairy Tales Fair? Analyzing Gender Bias in Temporal Narrative Event Chains of Children's Fairy Tales. - Paulina Toro Isaza; Guangxuan Xu; Akintoye Oloko; Yufang Hou 001; Nanyun Peng 001; Dakuo Wang (CoRR, 2023)

A Grounded Preference Model for LLM Alignment. - Tahira Naseem; Guangxuan Xu; Sarathkrishna Swaminathan; Asaf Yehudai; Subhajit Chaudhury; Radu Florian; Ramón Fernandez Astudillo; Asim Munawar (ACL (Findings), 2024)

BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback. - Gaurav Pandey 001; Yatin Nandwani; Tahira Naseem; Mayank Mishra; Guangxuan Xu; Dinesh Raghu; Sachindra Joshi; Asim Munawar; Ramón Fernandez Astudillo (ICML, 2024)

CDR: Customizable Density Ratios of Strong-over-weak LLMs for Preference Annotation. - Guangxuan Xu; Kai Xu 016; Shivchander Sudalairaj; Hao Wang; Akash Srivastava (CoRR, 2024)

Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs. - Aldo Pareja; Nikhil Shivakumar Nayak; Hao Wang; Krishnateja Killamsetty; Shivchander Sudalairaj; Wenlong Zhao 001; Seungwook Han; Abhishek Bhandwaldar; Guangxuan Xu; Kai Xu 016; Ligong Han; Luke Inglis; et al. (ICLR, 2025)

A Probabilistic Inference Approach to Inference-Time Scaling of LLMs using Particle-Based Monte Carlo Methods. - Isha Puri; Shivchander Sudalairaj; Guangxuan Xu; Kai Xu 016; Akash Srivastava (CoRR, 2025)