Pixel-Stega: Generative Image Steganography Based on Autoregressive Models. - Si-yu Zhang 001; Zhongliang Yang; Haoqin Tu; Jinshuai Yang; Yongfeng Huang 001 (CoRR, 2021)

AdaVAE: Exploring Adaptive GPT-2s in Variational Auto-Encoders for Language Modeling. - Haoqin Tu; Zhongliang Yang; Jinshuai Yang; Si-yu Zhang 001; Yongfeng Huang 001 (CoRR, 2022)

An Overview on Controllable Text Generation via Variational Auto-Encoders. - Haoqin Tu; Yitong Li (CoRR, 2022)

PCAE: A framework of plug-in conditional auto-encoder for controllable text generation. - Haoqin Tu; Zhongliang Yang; Jinshuai Yang; Si-yu Zhang 001; Yongfeng Huang 001 (Knowl. Based Syst., 2022)

SeSy: Linguistic Steganalysis Framework Integrating Semantic and Syntactic Features. - Jinshuai Yang; Zhongliang Yang; Si-yu Zhang 001; Haoqin Tu; Yongfeng Huang 001 (IEEE Signal Process. Lett., 2022)

ReSee: Responding through Seeing Fine-grained Visual Knowledge in Open-domain Dialogue. - Haoqin Tu; Yitong Li; Fei Mi; Zhongliang Yang (EMNLP, 2023)

ZeroGen: Zero-Shot Multimodal Controllable Text Generation with Multiple Oracles. - Haoqin Tu; Bowen Yang; Xianfeng Zhao (NLPCC (2), 2023)

How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs. - Haoqin Tu; Chenhang Cui; Zijun Wang; Yiyang Zhou; Bingchen Zhao; Junlin Han; Wangchunshu Zhou; Huaxiu Yao; Cihang Xie (CoRR, 2023)

Linguistic Steganalysis Toward Social Network. - Jinshuai Yang; Zhongliang Yang; Jiajun Zou; Haoqin Tu; Yongfeng Huang 001 (IEEE Trans. Inf. Forensics Secur., 2023)

How Many Are in This Image A Safety Evaluation Benchmark for Vision LLMs. - Haoqin Tu; Chenhang Cui; Zijun Wang; Yiyang Zhou; Bingchen Zhao; Junlin Han; Wangchunshu Zhou; Huaxiu Yao; Cihang Xie (ECCV (51), 2024)

Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning. - Bingchen Zhao; Haoqin Tu; Chen Wei 005; Jieru Mei; Cihang Xie (ICLR, 2024)

VHELM: A Holistic Evaluation of Vision Language Models. - Tony Lee; Haoqin Tu; Chi Heem Wong; Wenhao Zheng; Yiyang Zhou; Yifan Mai 001; Josselin Somerville Roberts; Michihiro Yasunaga; Huaxiu Yao; Cihang Xie; Percy Liang (NeurIPS, 2024)

Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence. - Bo Peng; Daniel Goldstein; Quentin Anthony; Alon Albalak; Eric Alcaide; Stella Biderman; Eugene Cheah; Xingjian Du; Teddy Ferdinan; Haowen Hou; Przemyslaw Kazienko; Kranthi Kiran GV; et al. (CoRR, 2024)

How Far Are We From AGI. - Tao Feng; Chuanyang Jin; Jingyu Liu; Kunlun Zhu; Haoqin Tu; Zirui Cheng; Guanyu Lin; Jiaxuan You (CoRR, 2024)

What If We Recaption Billions of Web Images with LLaMA-3? - Xianhang Li; Haoqin Tu; Mude Hui; Zeyu Wang 008; Bingchen Zhao; Junfei Xiao; Sucheng Ren; Jieru Mei; Qing Liu 017; Huangjie Zheng; Yuyin Zhou; Cihang Xie (CoRR, 2024)

MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation? - Zhaorun Chen; Yichao Du; Zichen Wen; Yiyang Zhou; Chenhang Cui; Zhenzhen Weng; Haoqin Tu; Chaoqi Wang; Zhengwei Tong; Qinglan Huang; Canyu Chen; Qinghao Ye; et al. (CoRR, 2024)

A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor? - Yunfei Xie; Juncheng Wu; Haoqin Tu; Siwei Yang; Bingchen Zhao; Yongshuo Zong; Qiao Jin; Cihang Xie; Yuyin Zhou (CoRR, 2024)

Code-Survey: An LLM-Driven Methodology for Analyzing Large-Scale Codebases. - Yusheng Zheng; Yiwei Yang 002; Haoqin Tu; Yuxi Huang 006 (CoRR, 2024)

Libra-Leaderboard: Towards Responsible AI through a Balanced Leaderboard of Safety and Capability. - Haonan Li 002; Xudong Han; Zenan Zhai; Honglin Mu; Hao Wang; Zhenxuan Zhang; Yilin Geng; Shom Lin; Renxi Wang; Artem Shelmanov; Xiangyu Qi; Yuxia Wang; et al. (CoRR, 2024)

How Far Are We From AGI: Are LLMs All We Need? - Tao Feng; Chuanyang Jin; Jingyu Liu; Kunlun Zhu; Haoqin Tu; Zirui Cheng; Guanyu Lin; Jiaxuan You (Trans. Mach. Learn. Res., 2024)

Sight Beyond Text: Multi-Modal Training Enhances LLMs in Truthfulness and Ethics. - Haoqin Tu; Bingchen Zhao; Chen Wei 005; Cihang Xie (Trans. Mach. Learn. Res., 2024)

FET-LM: Flow-Enhanced Variational Autoencoder for Topic-Guided Language Modeling. - Haoqin Tu; Zhongliang Yang; Jinshuai Yang; Linna Zhou; Yongfeng Huang 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Language Models Can See Better: Visual Contrastive Decoding For LLM Multimodal Reasoning. - Yuqi Pang; Bowen Yang; Haoqin Tu; Yun Cao; Zeyu Zhang (ICASSP, 2025)

Autoregressive Pretraining with Mamba in Vision. - Sucheng Ren; Xianhang Li; Haoqin Tu; Feng Wang; Fangxun Shu; Lei Zhang; Jieru Mei; Linjie Yang; Peng Wang; Heng Wang; Alan L. Yuille; Cihang Xie (ICLR, 2025)

AttnGCG: Enhancing Jailbreaking Attacks on LLMs with Attention Manipulation. - Zijun Wang; Haoqin Tu; Jieru Mei; Bingchen Zhao; Yisen Wang 001; Cihang Xie (Trans. Mach. Learn. Res., 2025)

ViLBench: A Suite for Vision-Language Process Reward Modeling. - Haoqin Tu; Weitao Feng; Hardy Chen; Hui Liu 031; Xianfeng Tang; Cihang Xie (CoRR, 2025)

STAR-1: Safer Alignment of Reasoning LLMs with 1K Data. - Zijun Wang; Haoqin Tu; Yuhan Wang; Juncheng Wu; Jieru Mei; Brian R. Bartoldson; Bhavya Kailkhura; Cihang Xie (CoRR, 2025)

SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models. - Hardy Chen; Haoqin Tu; Fali Wang; Hui Liu 031; Xianfeng Tang; Xinya Du; Yuyin Zhou; Cihang Xie (CoRR, 2025)

OpenVision: A Fully-Open, Cost-Effective Family of Advanced Vision Encoders for Multimodal Learning. - Xianhang Li; Yanqing Liu; Haoqin Tu; Hongru Zhu; Cihang Xie (CoRR, 2025)

Knowledge or Reasoning? A Close Look at How LLMs Think Across Domains. - Juncheng Wu; Sheng Liu; Haoqin Tu; Hang Yu; Xiaoke Huang; James Y. Zou; Cihang Xie; Yuyin Zhou (CoRR, 2025)