Neural Topic Model with Attention for Supervised Learning. - Xinyi Wang 003; Yi Yang 042 (AISTATS, 2020)

Modeling Disclosive Transparency in NLP Application Descriptions. - Michael Saxon; Sharon Levy; Xinyi Wang 003; Alon Albalak; William Yang Wang (EMNLP (1), 2021)

RefBERT: Compressing BERT by Referencing to Pre-computed Representations. - Xinyi Wang 003; Haiqin Yang; Liang Zhao; Yang Mo; Jianping Shen (IJCNN, 2021)

A Dataset for Answering Time-Sensitive Questions. - Wenhu Chen; Xinyi Wang 003; William Yang Wang (NeurIPS Datasets and Benchmarks, 2021)

Counterfactual Maximum Likelihood Estimation for Training Deep Networks. - Xinyi Wang 003; Wenhu Chen; Michael Saxon; William Yang Wang (NeurIPS, 2021)

Dimensions of Transparency in NLP Applications. - Michael Saxon; Sharon Levy; Xinyi Wang 003; Alon Albalak; William Yang Wang (CoRR, 2021)

Automatically Identifying Semantic Bias in Crowdsourced Natural Language Inference Datasets. - Michael Saxon; Xinyi Wang 003; William Yang Wang (CoRR, 2021)

PECO: Examining Single Sentence Label Leakage in Natural Language Inference Datasets through Progressive Evaluation of Cluster Outliers. - Michael Saxon; Xinyi Wang 003; Wenda Xu; William Yang Wang (EACL, 2023)

TheoremQA: A Theorem-driven Question Answering Dataset. - Wenhu Chen; Ming Yin; Max Ku; Pan Lu; Yixin Wan; Xueguang Ma; Jianyu Xu; Xinyi Wang 003; Tony Xia (EMNLP, 2023)

Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning. - Liangming Pan; Alon Albalak; Xinyi Wang 003; William Yang Wang (EMNLP (Findings), 2023)

Collaborative Generative AI: Integrating GPT-k for Efficient Editing in Text-to-Image Generation. - Wanrong Zhu; Xinyi Wang 003; Yujie Lu; Tsu-Jui Fu; Xin Wang 061; Miguel P. Eckstein; William Wang 001 (EMNLP, 2023)

Causal Balancing for Domain Generalization. - Xinyi Wang 003; Michael Saxon; Jiachen Li; Hongyang Zhang 001; Kun Zhang 001; William Yang Wang (ICLR, 2023)

Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning. - Xinyi Wang 003; Wanrong Zhu; Michael Saxon; Mark Steyvers; William Yang Wang (NeurIPS, 2023)

Large Language Models Are Implicitly Topic Models: Explaining and Finding Good Demonstrations for In-Context Learning. - Xinyi Wang 003; Wanrong Zhu; William Yang Wang (CoRR, 2023)

Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies. - Liangming Pan; Michael Saxon; Wenda Xu; Deepak Nathani; Xinyi Wang 003; William Yang Wang (CoRR, 2023)

Guiding Language Model Reasoning with Planning Tokens. - Xinyi Wang 003; Lucas Caccia; Oleksiy Ostapenko; Xingdi Yuan; Alessandro Sordoni (CoRR, 2023)

Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks. - Wenhu Chen; Xueguang Ma; Xinyi Wang 003; William W. Cohen (Trans. Mach. Learn. Res., 2023)

Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation. - Xinyi Wang 003; Alfonso Amayuelas; Kexun Zhang; Liangming Pan; Wenhu Chen; William Yang Wang (ICML, 2024)

Position: AI/ML Influencers Have a Place in the Academic Process. - Iain Weissburg; Mehir Arora; Xinyi Wang 003; Liangming Pan; William Yang Wang (ICML, 2024)

T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback. - Jiachen Li; Weixi Feng; Tsu-Jui Fu; Xinyi Wang 003; Sugato Basu; Wenhu Chen; William Yang Wang (NeurIPS, 2024)

Gödel Agent: A Self-Referential Agent Framework for Recursive Self-Improvement. - Xunjian Yin; Xinyi Wang 003; Liangming Pan; Xiaojun Wan 001; William Yang Wang (CoRR, 2024)

Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models. - Sitao Cheng; Liangming Pan; Xunjian Yin; Xinyi Wang 003; William Yang Wang (CoRR, 2024)

Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies. - Liangming Pan; Michael Saxon; Wenda Xu; Deepak Nathani; Xinyi Wang 003; William Yang Wang (Trans. Assoc. Comput. Linguistics, 2024)

A Survey on Data Selection for Language Models. - Alon Albalak; Yanai Elazar; Sang Michael Xie; Shayne Longpre; Nathan Lambert 001; Xinyi Wang 003; Niklas Muennighoff; Bairu Hou; Liangming Pan; Haewon Jeong; Colin Raffel; Shiyu Chang; et al. (Trans. Mach. Learn. Res., 2024)

Disentangling Memory and Reasoning Ability in Large Language Models. - Mingyu Jin; Weidi Luo; Sitao Cheng; Xinyi Wang 003; Wenyue Hua; Ruixiang Tang; William Yang Wang; Yongfeng Zhang (ACL (1), 2025)

Gödel Agent: A Self-Referential Agent Framework for Recursively Self-Improvement. - Xunjian Yin; Xinyi Wang 003; Liangming Pan; Li Lin 014; Xiaojun Wan 001; William Yang Wang (ACL (1), 2025)

Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data. - Xinyi Wang 003; Antonis Antoniades; Yanai Elazar; Alfonso Amayuelas; Alon Albalak; Kexun Zhang; William Yang Wang (ICLR, 2025)

Do Larger Language Models Imply Better Reasoning? A Pretraining Scaling Law for Reasoning. - Xinyi Wang 003; Shawn Tan; Mingyu Jin; William Yang Wang; Rameswar Panda; Yikang Shen (CoRR, 2025)

LEDOM: An Open and Fundamental Reverse Language Model. - Xunjian Yin; Sitao Cheng; Yuxi Xie; Xinyu Hu 001; Li Lin 014; Xinyi Wang 003; Liangming Pan; William Yang Wang; Xiaojun Wan 001 (CoRR, 2025)