Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation. - Guangyi Liu 005; Zichao Yang; Tianhua Tao; Xiaodan Liang; Zhen Li 026; Bowen Zhou 001; Shuguang Cui; Zhiting Hu (CoRR, 2021)

On the Learning of Non-Autoregressive Transformers. - Fei Huang 005; Tianhua Tao; Hao Zhou 012; Lei Li 005; Minlie Huang (ICML, 2022)

Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation. - Guangyi Liu 005; Zichao Yang; Tianhua Tao; Xiaodan Liang; Junwei Bao 001; Zhen Li 026; Xiaodong He 001; Shuguang Cui; Zhiting Hu (NAACL-HLT, 2022)

Language Models Meet World Models: Embodied Experiences Enhance Language Models. - Jiannan Xiang; Tianhua Tao; Yi Gu; Tianmin Shu; Zirui Wang; Zichao Yang; Zhiting Hu (NeurIPS, 2023)

SlimPajama-DC: Understanding Data Combinations for LLM Training. - Zhiqiang Shen; Tianhua Tao; Liqun Ma; Willie Neiswanger; Zhengzhong Liu 001; Hongyi Wang 001; Bowen Tan; Joel Hestness; Natalia Vassilieva; Daria Soboleva; Eric P. Xing (CoRR, 2023)

LLM360: Towards Fully Transparent Open-Source LLMs. - Zhengzhong Liu 001; Aurick Qiao; Willie Neiswanger; Hongyi Wang 001; Bowen Tan; Tianhua Tao; Junbo Li; Yuqi Wang; Suqi Sun; Omkar Pangarkar; Richard Fan; Yi Gu 002; et al. (CoRR, 2023)

SciCode: A Research Coding Benchmark Curated by Scientists. - Minyang Tian; Luyu Gao; Shizhuo Dylan Zhang; Xinan Chen; Cunwei Fan; Xuefei Guo; Roland Haas; Pan Ji; Kittithat Krongchon; Yao Li; Shengyan Liu; Di Luo; et al. (NeurIPS, 2024)

Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs. - Sukmin Yun; Haokun Lin; Rusiru Thushara; Mohammad Qazim Bhat; Yongxin Wang; Zutao Jiang; Mingkai Deng; Jinhong Wang; Tianhua Tao; Junbo Li; Haonan Li 002; Preslav Nakov; et al. (NeurIPS, 2024)

Pandora: Towards General World Model with Natural Language Actions and Video States. - Jiannan Xiang; Guangyi Liu 005; Yi Gu 002; Qiyue Gao; Yuting Ning; Yuheng Zha; Zeyu Feng; Tianhua Tao; Shibo Hao; Yemin Shi 003; Zhengzhong Liu 001; Eric P. Xing; et al. (CoRR, 2024)

SciCode: A Research Coding Benchmark Curated by Scientists. - Minyang Tian; Luyu Gao; Shizhuo Dylan Zhang; Xinan Chen; Cunwei Fan; Xuefei Guo; Roland Haas; Pan Ji; Kittithat Krongchon; Yao Li; Shengyan Liu; Di Luo; et al. (CoRR, 2024)

Crystal: Illuminating LLM Abilities on Language and Code. - Tianhua Tao; Junbo Li; Bowen Tan; Hongyi Wang 001; William Marshall; Bhargav Kanakiya; Joel Hestness; Natalia Vassilieva; Zhiqiang Shen; Eric P. Xing; Zhengzhong Liu 001 (CoRR, 2024)

LLM360 K2: Building a 65B 360-Open-Source Large Language Model from Scratch. - Zhengzhong Liu 001; Bowen Tan; Hongyi Wang 001; Willie Neiswanger; Tianhua Tao; Haonan Li 002; Fajri Koto; Yuqi Wang; Suqi Sun; Omkar Pangarkar; Richard Fan; Yi Gu 002; et al. (CoRR, 2025)