Jingang Wang
Principal Engineer & Director · Meituan LLM Team

About Me

I am a Principal Engineer and Director of the Large Language Model team at Meituan. Before that, I was a senior algorithm engineer at Alibaba DAMO Academy. I obtained my Ph.D. degree in computer science from the joint Ph.D. program between Beijing Institute of Technology and Purdue University in 2016. My research interests include natural language processing, information retrieval, and machine translation.

My team is currently working on recursive self-improvement and automated research for large language models. We are looking for motivated interns and full-time researchers to join us. Please feel free to reach out if you are interested.

RSI Research · First Work

Beyond Final Scores

Our first step toward Recursive Self-Improvement: evaluating not only whether AI agents improve results, but whether they learn how to conduct better research. Across seven frontier models and 36 long-horizon AutoResearch tasks, we find that current agents are already capable engineering optimizers, while reliability and methodological novelty remain key bottlenecks. Their observed capability emerges from the interaction among the model, accumulated experience, and the surrounding harness.

7frontier models
36long-horizon tasks
3 / 252methodologically novel
Model × Experience × Harness Read the paper ↗

Publication List

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2026
Yiwei Li, Wanli Yang, Hexiang Tan, Xiangzhou Huang, Zhengyu Chen, Ziran Li, Borun Chen, Shanglin Lei, Huaisheng Zhu, Hao Tian, Fei Sun, Xunliang Cai and Jingang Wang. Beyond Final Scores: A Systematic Evaluation of Agents for Long-Horizon AI Research and Development. arXiv preprint arXiv:2608.13417. 2026.
Ziran Li, Qiang Wang, Zhengyu Chen, Shanglin Lei, Borun Chen, Jingang Wang and Xunliang Cai. What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs. arXiv preprint arXiv:2608.00013. 2026.
Wanxu Cai, Zhengyu Chen, Huaisheng Zhu, Wei Wang, Jingang Wang and Qiang Xu. Distilling Temporal Search and Reasoning: Evolving LLMs for Future Prediction via Harness-Assisted Efficient Data Synthesis. arXiv preprint arXiv:2607.25554. 2026.
Zhengyu Chen, Teng Xiao, Huaisheng Zhu, Yige Yuan, Luan Zhang and Jingang Wang. Co-Harness: Co-Evolving Harnesses and Model Weights for LLM Agents. arXiv preprint arXiv:2607.22688. 2026.
Peiguang Li, Yongwei Zhou, Juncheng Diao, Yuchun Fan, Jian Yang, Jianxiao Yang, Zhongda Su, Shuguang Jiao, Xiao Wei, Zhiye Zou, Gan Dong, Zhizhao Zeng, Rongxiang Weng, Jingang Wang and Xunliang Cai. CuraWeb: Joint Optimization of Quality, Redundancy, and Diversity for Web-Scale Pretraining Data. arXiv preprint arXiv:2607.22662. 2026.
Junhao Ruan, Yuan Ge, Bei Li, Yongjing Yin, Yuchun Fan, Xin Chen, Jingang Wang, Chenglong Wang, Jingbo Zhu and Tong Xiao. ToFu: A White-Box, Token-Efficient Agent Harness for Researchers. arXiv preprint arXiv:2607.11423. 2026.
Zihao Wei, Liang Pang, Jiahao Liu, Wenjie Shi, Jingcheng Deng, Shicheng Xu, Zenghao Duan, Jingang Wang, Fei Sun, Huawei Shen and Xueqi Cheng. The Evolution of Thought: Tracking LLM Overthinking via Reasoning Dynamics Analysis. ACL 2026.
Zhengyu Chen, Yudong Wang, Teng Xiao, Ruochen Zhou, Xuesheng Yang, Wei Wang, Zhifang Sui and Jingang Wang. From Mathematical Reasoning to Code: Generalization of Process Reward Models in Test-Time Scaling. AAAI 2026.
Deyang Kong, Qi Guo, Xiangyu Xi, Wei Wang, Jingang Wang, Xunliang Cai, Shikun Zhang and Wei Ye. Rethinking the Sampling Criteria in Reinforcement Learning for LLM Reasoning: A Competence-Difficulty Alignment Perspective. AAAI 2026.
Siqi Wang, Zhengyu Chen, Teng Xiao, Zheqi Lv, Jinluan Yang, Xunliang Cai, Jingang Wang and Xiaomeng Li. Scaling and Transferability of Annealing Strategies in Large Language Model Training. AAAI 2026.
Tianyuan Shi, Canbin Huang, Bei Li, Xin Chen, Xiaojun Quan, Jingang Wang and Qifan Wang. Beyond Trajectory Imitation: Strategy-Guided Policy Optimization for LLM Reasoning. arXiv preprint arXiv:2606.24064. 2026.
Zihao Wei, Wenjie Shi, Liang Pang, Jingcheng Deng, Shicheng Xu, Shasha Guo, Zenghao Duan, Jiahao Liu, Jingang Wang, Huawei Shen and Xueqi Cheng. Dynamic Rollout Editing for Reducing Overthinking in RL-Trained Reasoning Models. arXiv preprint arXiv:2606.17890. 2026.
Juncheng Diao, Zhicong Lu, Peiguang Li, Yongwei Zhou, Changyuan Tian, Qingbin Li, Rongxiang Weng, Jingang Wang and Xunliang Cai. HIPIF: Hierarchical Planning and Information Folding for Long-Horizon LLM Agent Learning. arXiv preprint arXiv:2606.10507. 2026.
Canbin Huang, Tianyuan Shi, Xiaojun Quan, Jingang Wang, Jianfei Zhang and Qifan Wang. When Model Merging Breaks Routing: Training-Free Calibration for MoE. arXiv preprint arXiv:2606.03391. 2026.
Han Li, Xinyu Peng, Yaoming Wang, Zelin Peng, Xin Chen, Rongxiang Weng, Jingang Wang, Xunliang Cai, Wenrui Dai and Hongkai Xiong. OneCAT: Decoder-Only Auto-Regressive Model for Unified Understanding and Generation. CVPR 2026.
Deli Huang, Cunguang Wang, Hongyin Tang, Zhe Tang, Linsen Guo, Dongyu Ru, Ruoshi Yuan, Ziyue Zhu, Xiaoyu Li, Ziwen Wang, Chen Zhang, Anchun Gui, Jingang Wang and others. ATLAS: All-round Testing of Long-context Abilities across Scales. arXiv preprint arXiv:2605.28079. 2026.
Yuchun Fan, Bei Li, Peiguang Li, Yilin Wang, Yongyu Mu, Jian Yang, Xin Chen, Rongxiang Weng, Jingang Wang, Xunliang Cai, Jingbo Zhu and Tong Xiao. LANG: Reinforcement Learning for Multilingual Reasoning with Language-Adaptive Hint Guidance. ACL 2026.
Junhao Ruan, Abudukeyumu Abudula, Bei Li, Yongjing Yin, Xinyu Liu, Kechen Jiao, Xin Chen, Jingang Wang, Xunliang Cai, Tong Xiao and Jingbo Zhu. MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks. ACL 2026.
Xuemiao Zhang, Can Ren, Chengying Tu, Rongxiang Weng, Hongfei Yan, Jingang Wang and Xunliang Cai. LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points. ACL 2026.
Xuemiao Zhang, Chengying Tu, Can Ren, Rongxiang Weng, Hongfei Yan, Jingang Wang and Xunliang Cai. Large-Scale Diverse Synthesis for Mid-Training. Findings of ACL 2026.
Yang Bai, Kaiyuan Liu, Ziyuan Zhuang, Jiahong Zhou, Rongxiang Weng, Xin Chen, Jingang Wang and Xunliang Cai. Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization. arXiv preprint arXiv:2605.13641. 2026.
Xinyu Liu, Kechen Jiao, Chunyang Xiao, Runsong Zhao, Junhao Ruan, Bei Li, Jiahao Liu, Qifan Wang, Xin Chen, Jingang Wang, Chenglong Wang, Tong Xiao and Jingbo Zhu. Teacher-Guided Policy Optimization for On-Policy Reasoning Distillation under Large Policy Divergence. arXiv preprint arXiv:2605.13230. 2026.
Wanli Yang, Hongyu Zang, Junwei Zhang, Wenjie Shi, Du Su, Jingang Wang, Xueqi Cheng and Fei Sun. Beyond Reasoning: Reinforcement Learning Unlocks Parametric Knowledge in LLMs. arXiv preprint arXiv:2605.07153. 2026.
Jianing Wang, Jianfei Zhang, Qi Guo, Linsen Guo, Rumei Li, Chao Zhang, Chong Peng, Cunguang Wang, Dengchang Zhao, Jiarong Shi, Jingang Wang and others. LongCat-Flash-Prover: Advancing Native Formal Reasoning via Agentic Tool-Integrated Reinforcement Learning. arXiv preprint arXiv:2603.21065. 2026.
Qi Guo, Jianing Wang, Deyang Kong, Xiangyu Xi, Jianfei Zhang, Yi Lu, Jingang Wang, Wei Wang, Shikun Zhang and Wei Ye. OPE: Overcoming Information Saturation in Parallel Thinking via Outline-Guided Path Exploration. arXiv preprint arXiv:2602.08344. 2026.
Chao Wang, Bei Li, Jiaqi Zhang, Xinyu Liu, Yuchun Fan, Linkun Lyu, Xin Chen, Jingang Wang, Tong Xiao, Peng Pei and Xunliang Cai. SpanNorm: Reconciling Training Stability and Performance in Deep Transformers. arXiv preprint arXiv:2601.22580. 2026.
Junhao Ruan, Bei Li, Yongjing Yin, Pengcheng Huang, Xin Chen, Jingang Wang, Xunliang Cai, Tong Xiao and Jingbo Zhu. Causal Autoregressive Diffusion Language Model. arXiv preprint arXiv:2601.22031. 2026.
Shiyu Liu, Yongjing Yin, Jianhao Yan, Yunbo Tang, Qinggang Zhang, Bei Li, Xin Chen, Jingang Wang, Xunliang Cai and Jinsong Su. BAPO: Boundary-Aware Policy Optimization for Reliable Agentic Search. Findings of ACL 2026.
Zhihao Xu, Rumei Li, Jiahuan Li, Rongxiang Weng, Jingang Wang, Xunliang Cai and Xiting Wang. Unlocking Implicit Experience: Synthesizing Tool-Use Trajectories from Text. ACL 2026.
Hexiang Tan, Wanli Yang, Junwei Zhang, Xin Chen, Rui Tang, Du Su, Jingang Wang, Yuanzhuo Wang, Fei Sun and Xueqi Cheng. BaseCal: Unsupervised Confidence Calibration via Base Model Signals. ACL 2026.
Team, Meituan LongCat, Gui Anchun, Li Bei, Tao Bingyang, Zhou Bole, Chen Borun, Zhang Chao, Gao Chen, Zhang Chen, Han Chengcheng, Jingang Wang and others. LongCat-Flash-Thinking-2601 Technical Report. arXiv preprint arXiv:2601.16725. 2026.
Shihan Dou, Haoxiang Jia, Shenxi Wu, Huiyuan Zheng, Muling Wu, Yunbo Tao, Ming Zhang, Mingxu Chai, Jessica Fan, Zhiheng Xi, Jingang Wang and others. What is wrong with your code generated by large language models? An extensive study. Science China Information Sciences 69(1):112107. 2026.
2025
Chen Zhang, Bai Yang, Jiahuan Li, Anchun Gui, Keheng Wang, Feifan Liu, Guanyu Wu, Yuwei Jiang, Defei Bu, Li Wei and others. Efficient Context Scaling with LongCat ZigZag Attention. arXiv preprint arXiv:2512.23966. 2025.
Team, Meituan LongCat, Wang Bairui, Xiao Bin, Zhang Bo, Rong Bolin, Chen Borun, Wan Chang, Zhang Chao, Huang Chen, Chen Chen and others. Longcat-flash-omni technical report. arXiv preprint arXiv:2511.00279. 2025.
Team, Meituan LongCat, Gui Anchun, Li Bei, Tao Bingyang, Zhou Bole, Chen Borun, Zhang Chao, Han Chengcheng, Yang Chenhui, Zhang Chi and others. Introducing LongCat-Flash-Thinking: A Technical Report. arXiv preprint arXiv:2509.18883. 2025.
Team, Meituan LongCat, Li Bei, Lei Bingye, Wang Bo, Rong Bolin, Wang Chao, Zhang Chao, Gao Chen, Zhang Chen, Sun Cheng and others. Longcat-flash technical report. arXiv preprint arXiv:2509.01322. 2025.
Xiangyu Xi, Deyang Kong, Jian Yang, Jiawei Yang, Zhengyu Chen, Wei Wang, Jingang Wang, Xunliang Cai, Shikun Zhang and Wei Ye. SampleMix: A Sample-wise Pre-training Data Mixing Strategy by Coordinating Data Quality and Diversity. Findings of EMNLP 2025.
Ruichen Shao, Bei Li, Gangao Liu, Yang Chen, Xiang Zhou, Jingang Wang, Xunliang Cai and Peng Li. Earlier Tokens Contribute More: Learning Direct Preference Optimization From Temporal Decay Perspective. ICLR 2025.
Danlong Yuan, Jiahao Liu, Bei Li, Huishuai Zhang, Jingang Wang, Xunliang Cai and Dongyan Zhao. ReMamba: Equip Mamba with Effective Long-Sequence Modeling. Findings of EMNLP 2025.
2024
Siqi Wang, Zhengyu Chen, Bei Li, Keqing He, Min Zhang and Jingang Wang. Scaling laws across model architectures: A comparative analysis of dense and MoE models in large language models. EMNLP 2024.
Yejie Wang, Keqing He, Dayuan Fu, Zhuoma GongQue, Heyang Xu, Yanxu Chen, Zhexu Wang, Yujia Fu, Guanting Dong, Muxi Diao and others. How do your code LLMs perform? Empowering code instruction tuning with really good data. EMNLP 2024.
Zhengyu Hu, Linxin Song, Jieyu Zhang, Zheyuan Xiao, Jingang Wang, Zhenyu Chen, Jieyu Zhao and Hui Xiong. Rethinking LLM-based Preference Evaluation. CoRR 2024.
Zhengyu Hu, Yichuan Li, Zhengyu Chen, Jingang Wang, Han Liu, Kyumin Lee and Kaize Ding. Let’s ask GNN: Empowering large language model for graph in-context learning. Findings of EMNLP 2024.
Zhuocheng Gong, Jiahao Liu, Jingang Wang, Xunliang Cai, Dongyan Zhao and Rui Yan. What makes quantization for large language model hard? An empirical study from the lens of perturbation. AAAI 2024.
Ying Mo, Jiahao Liu, Jian Yang, Qifan Wang, Shun Zhang, Jingang Wang and Zhoujun Li. C-ICL: Contrastive in-context learning for information extraction. Findings of EMNLP 2024.
Zhiheng Xi, Dingwen Yang, Jixuan Huang, Jiafu Tang, Guanyu Li, Yiwen Ding, Wei He, Boyang Hong, Shihan Do, Wenyu Zhan and others. Enhancing LLM reasoning via critique models with test-time and training-time supervision. arXiv preprint arXiv:2411.16579. 2024.
Jiahao Liu, Qifan Wang, Jingang Wang and Xunliang Cai. Speculative decoding via early-exiting for faster LLM inference with Thompson sampling control mechanism. Findings of ACL 2024.
Bei Li, Tong Zheng, Rui Wang, Jiahao Liu, Junliang Guo, Xu Tan, Tong Xiao, JingBo Zhu, Jingang Wang and Xunliang Cai. Predictor-corrector enhanced transformers with exponential moving average coefficient learning. NeurIPS 2024.
Hongyin Tang, Di Xiu, Lanrui Wang, Xiurui Geng, Jingang Wang and Xunliang Cai. Ltri-LLM: Streaming long context inference for LLMs with training-free dynamic triangular attention pattern. arXiv preprint arXiv:2412.04757. 2024.
Yaoyuan Liang, Xiao Liang, Yansong Tang, Zhao Yang, Ziran Li, Jingang Wang, Wenbo Ding and Shao-Lun Huang. Costa: End-to-end comprehensive space-time entanglement for spatio-temporal video grounding. AAAI 2024.
Ying Mo, Jian Yang, Jiahao Liu, Qifan Wang, Ruoyu Chen, Jingang Wang, Zhoujun Li. MCL-NER: Cross-Lingual Named Entity Recognition via Multi-View Contrastive Learning. AAAI 2024 (CCF-A).
Yejie Wang, Keqing He, Guanting Dong, Pei Wang, Weihao Zeng, Muxi Diao, Yutao Mou, Mengdi Zhang, Jingang Wang, Xunliang Cai, Weiran Xu. DolphCoder: Echo-Locating Code Large Language Models with Diverse and Multi-Objective Instruction Tuning. ACL 2024 (CCF-A).
Pei Wang, Keqing He, Yejie Wang, Xiaoshuai Song, Yutao Mou, Jingang Wang, Yunsen Xian, Xunliang Cai, Weiran Xu. Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection. LREC-COLING 2024.
2023
Xiaoshuai Song, Keqing He, Pei Wang, Guanting Dong, Yutao Mou, Jingang Wang, Yunsen Xian, Xunliang Cai and Weiran Xu. Large language models meet open-world intent discovery and recognition: An evaluation of ChatGPT. EMNLP 2023.
Pei Wang, Keqing He, Yutao Mou, Xiaoshuai Song, Yanan Wu, Jingang Wang, Yunsen Xian, Xunliang Cai and Weiran Xu. APP: Adaptive prototypical pseudo-labeling for few-shot OOD detection. Findings of EMNLP 2023.
Chen Zhang, Yang Yang, Jiahao Liu, Jingang Wang, Yunsen Xian, Benyou Wang and Dawei Song. Lifting the Curse of Capacity Gap in Distilling Language Models. ACL 2023 (CCF-A).
Yutao Mou, Xiaoshuai Song, Keqing He, Chen Zeng, Pei Wang, Jingang Wang, Yunsen Xian and Weiran Xu. Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery. ACL 2023 (CCF-A).
Weihao Zeng, Lulu Zhao, Keqing He, Ruotong Geng, Jingang Wang, Wei Wu and Weiran Xu. Seen to Unseen: Exploring Compositional Generalization of Multi-Attribute Controllable Dialogue Generation. ACL 2023 (CCF-A).
Weihao Zeng, Keqing He, Yejie Wang, Chen Zeng, Jingang Wang, Yunsen Xian and Weiran Xu. FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented Dialogue. ACL 2023 (CCF-A).
Rongyi Sun, Ziran Li, Yifeng Ding, Qifan Wang, Jingang Wang, Haitao Zheng, Wei Wu and Yunsen Xian. Fusion or Defusion? A Flexible Vision-and-Language Pre-Training Model. Findings of ACL 2023.
Zhuocheng Gong, Jiahao Liu, Qifan Wang, Yang Yang, Jingang Wang, Wei Wu, Yunsen Xian, Dongyan Zhao and Rui Yan. PreQuant: A Task-agnostic Quantization Approach for Pre-trained Language Models. Findings of ACL 2023.
Jiduan Liu, Jiahao Liu, Qifan Wang, Jingang Wang, Wei Wu, Yunsen Xian, Dongyan Zhao, Kai Chen and Rui Yan. RankCSE: Unsupervised Sentence Representations Learning via Learning to Rank. ACL 2023 (CCF-A).
Li Yang, Qifan Wang, Jingang Wang, Xiaojun Quan, Fuli Feng, Yu Chen, Madian Khabsa, Sinong Wang, Zenglin Xu and Dongfang Liu. MixPAVE: Mix-Prompt Tuning for Few-shot Product Attribute Value Extraction. Findings of ACL 2023.
Qifan Wang, Jingang Wang, Xiaojun Quan, Fuli Feng, Zenglin Xu, Shaoliang Nie, Sinong Wang, Madian Khabsa, Hamed Firooz and Dongfang Liu. MUSTIE: Multimodal Structural Transformer for Web Information Extraction. ACL 2023 (CCF-A).
2022
Liqi Yan, Qifan Wang, Siqi Ma, Jingang Wang and Changbin Yu. Solve the Puzzle of Instance Segmentation in Videos: A Weakly Supervised Framework with Spatio-Temporal Collaboration. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2022. (CCF-A)
Jiduan Liu, Jiahao Liu, Yang Yang, Jingang Wang, Wei Wu, Dongyan Zhao and Rui Yan. GNN-Encoder: Learning a Dual-encoder Architecture via Graph Neural Networks for Dense Passage Retrieval. Findings of EMNLP 2022.
Qifan Wang, Li Yang, Jingang Wang, Jitin Krishnan, Bo Dai, Sinong Wang, Zenglin Xu, Madian Khabsa and Hao Ma. SMUTPAVE: Structured Multimodal Transformer for Product Attribute Value Extraction. Findings of EMNLP 2022.
Dan Li, Yang Yang, Hongying Tang, Jingang Wang, Tong Xu, Wei Wu, Enhong Chen. VIRT: Improving Representation-based Models for Text Matching through Virtual Interaction. EMNLP 2022. (CCF-B)
Chen Zhang, Lei Ren, Jingang Wang, Wei Wu and Dawei Song. Making Pre-trained Language Models Good Long-tailed Learners. EMNLP 2022. (CCF-B)
Fang Ma, Chen Zhang, Lei Ren, Jingang Wang, Qifan Wang, Wei Wu, Xiaojun Quan and Dawei Song. XPrompt: Exploring the Extreme of Prompt Tuning. EMNLP 2022. (CCF-B)
Yutao Mou, Pei Wang, Keqing He, Yanan Wu, Jingang Wang, Wei Wu and Weiran Xu. UniNL: Aligning Representation Learning with Scoring Function for OOD Detection via Unified Neighborhood Learning. EMNLP 2022. (CCF-B)
Yutao Mou, Keqing He, Pei Wang, Yanan Wu, Jingang Wang, Wei Wu and Weiran Xu. Watch The Neighbors: A Unified K-Nearest Neighbor Contrastive Learning Framework for OOD Intent Discovery. EMNLP 2022. (CCF-B)
Keqing He, Jingang Wang, Chaobo Sun, Wei Wu. Unified Knowledge Prompt Pre-training for Customer Service Dialogues. CIKM 2022. (short) (CCF-B)
Biru Zhu, Yujia Qin, Ganqu Cui, Yangyi Chen, Weilin Zhao, Chong Fu, Yangdong Deng, Zhiyuan Liu, Jingang Wang, Wei Wu, Maosong Sun and Ming Gu. Moderate-fitting as a Natural Backdoor Defender for Pre-trained Language Models. NeurIPS 2022. (CCF-A)
Borun Chen, Hongyin Tang, Jingang Wang*, Wei Wu, Qifan Wang, Haitao Zheng and Liqian Yu. CLOWER: A Pre-trained Language Model with Contrastive Learning over Word and Character Representations. COLING 2022. (CCF-B)
Chen Zhang, Lei Ren, Fang Ma, Jingang Wang*, Wei Wu and Dawei Song. Structural Bias for Aspect Sentiment Triplet Extraction. COLING 2022. (CCF-B)
Yutao Mou, Keqing He, Yanan Wu, Pei Wang, Jingang Wang, Wei Wu, Yi Huang, Junlan Feng and Weiran Xu. Generalized Intent Discovery: Learning from Open World Dialogue System. COLING 2022. (CCF-B)
Mengxue Zhao, Yang Yang, Miao Li, Jingang Wang, Wei Wu, Pengjie Ren, Maarten de Rijke, Zhaochun Ren. Personalized Abstractive Opinion Tagging. SIGIR 2022. (CCF-A)
Qifang Wang, Yi Fang, Anirudh Ravula, Ruining He, Bin Shen, Jingang Wang, Xiaojun Quan, Dongfang Liu. Deep Partial Multiplex Network Embedding. The First Workshop on Graph Learning @The ACM Web Conference 2022.
Shengding Hu, Ning Ding, Huadong Wang, Zhiyuan Liu, Jingang Wang, Juanzi Li, Wei Wu, Maosong Sun. Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification. ACL 2022. (CCF-A)
2021
Hongyin Tang, Xingwu Sun, Beihong Jin, Jingang Wang, Fuzheng Zhang, Wei Wu. Improving Document Representations by Generating Pseudo Query Embeddings for Dense Retrieval. ACL 2021. (CCF-A)
Jiahao Bu, Lei Ren, Shuang Zheng, Yang Yang, Jingang Wang*, Fuzheng Zhang, Wei Wu. ASAP: A Chinese Review Dataset Towards Aspect Category Sentiment Analysis and Rating Prediction. NAACL 2021. (CCF-B)
2020
Yang Yang, Junmei Hao, Canjia Li, Zili Wang, Jingang Wang*, Fuzheng Zhang, Rao Fu, Peixu Hou, Gong Zhang, Zhongyuan Wang. Query-aware Tip Generation for Vertical Search. CIKM 2020 Applied Science Track. (CCF-B)
2019
Bowen Xing, Dandan Song, Lejian Liao, Jingang Wang, Fuzheng Zhang, Zhongyuan Wang, Heyan Huang. Earlier Attention? Aspect-Aware LSTM for Aspect-based Sentiment Analysis. IJCAI 2019. (CCF-A)
Lerong Ma, Dandan Song, Lejian Liao, Jingang Wang. A Hybrid Discriminative Mixture Model for Cumulative Citation Recommendation. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2019 (CCF-A)
2018
Lerong Ma, Lejian Liao, Dandan Song and Jingang Wang. A Latent Entity-Document Class Mixture of Experts Model for Cumulative Citation Recommendation. Tsinghua Science and Technology. 2018
Yongchao Deng, Shanbo Cheng, Jun Lu, Kai Song, Jingang Wang, Shenglan Wu, Liang Yao, Guchun Zhang, Haibo Zhang, Pei Zhang, Changfeng Zhu, Boxing Chen. Alibaba's Neural Machine Translation Systems for WMT 2018. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers (pp. 368-376).
Jingang Wang, Junfeng Tian, Long Qiu, Sheng Li, Jun Lang, Luo Si and Man Lan. A Multi-Task Learning Approach for Improving Product Title Compression With User Search Log Data. Proceedings of 32th AAAI Conference on Artificial Intelligence, AAAI 2018. (CCF-A)
2017
Lerong Ma, Dandan Song, Lejian Liao and Jingang Wang. PSVM: a preference-enhanced SVM model using preference data for classification. Science China Information Sciences 60.12 (2017): 122103. (CCF-B)
2016
Jingang Wang, Jingtian Jiang, Lejian Liao, Dandan Song, Zhiwei Zhang, Chin-Yew Lin. Cold Start Cumulative Citation Recommendation for Knowledge Base Acceleration. Proceedings of 38th European Conference on IR Research, ECIR 2016. (Poster) (CCF-C)
Zhiwei Zhang, Jingang Wang, Tao Wu, Pengjie Ren, Zhumin Chen, Luo Si. Supervised Local Contexts Aggregation for Effective Session Search. Proceedings of 38th European Conference on IR Research, ECIR 2016. (CCF-C)
2015
Jingang Wang, Dandan Song, Zhiwei Zhang, Luo Si, Lejian Liao and Chin-Yew Lin. LDTM: A Latent Document Type Model for Cumulative Citation Recommendation. Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP), Lisboa, Portugal, September 2015. (Short) (CCF-B)
Jingang Wang, Qifan Wang, Dandan Song, Zhiwei Zhang, Luo Si, Lejian Liao and Chin-Yew Lin. An Entity Class-Dependent Discriminative Mixture Model for Cumulative Citation Recommendation. SIGIR 2015. (CCF-A)
Jingang Wang, Lejian Liao, Dandan Song, Lerong Ma, Chin-Yew Lin and Yong Rui. Resorting Relevance Evidences to Cumulative Citation Recommendation for Knowledge Base Acceleration. Proceedings of 16th International Conference on Web-Age Information Management (WAIM), Qingdao, China, Jun. 2015. (CCF-C)
2014
Jingang Wang, Ning Zhang, Zhiwei Zhang, Dandan Song, Luo Si and Lejian Liao. BIT and Purdue at TREC-KBA-CCR Track 2014. Proceedings of 23rd Text Retrieval Conference (TREC), Gaithersburg, MD, US, Nov. 2014.
2013
Jingang Wang, Dandan Song, Chin-Yew Lin and Lejian Liao. BIT and MSRA at TREC KBA CCR Track 2013. Proceedings of 22nd Text Retrieval Conference (TREC), Gaithersburg, MD, US, Nov. 2013. (The 1st place team at KBA-CCR task.)
Guoqiang Li, Lejian Liao, Dandan Song, Jingang Wang, Fuzhen Sun and Guangcheng Liang. A Self-healing Framework for QoS-aware Web Service Composition via Case-based Reasoning. Proceedings of 15th Asia-Pacific Web Conference (AP-Web), Sydney, Australia, Apr. 2013. (CCF-C)
2012
Jingang Wang, Dandan Song, Lejian Liao and Wei Zou. The Chinese Bag-of-opinions Method for Hot-Topic-Oriented Sentiment Analysis on Weibo. Proceedings of Jointed Conference of 6th Chinese Semantic Web Symposium and The 1st Chinese Web Science Conference (CSWS), Shenzhen, China, Nov. 2012.

Education / Experience

  • 2022.12 ~ Present Research Scientist at LongCat LLM Team, Meituan, Beijing.
  • 2018.10 ~ 2022.12 Research Scientist at NLP Center, Meituan, Beijing. Collaborate with Dr Fuzheng Zhang and Dr. Zhongyuang Wang.
  • 2016.04 ~ 2018.09 Research Engineer at NLP Group, iDST, Alibaba Group, Beijing. Collaborate with Dr. Long Qiu and Dr. Luo Si.
  • 2015.03 ~ 2015.12 Research Intern at Knowledge Mining Group, Microsoft Research Asia, Beijing. Mentor: Dr. Chin-Yew Lin and Dr. Yunbo Cao.
  • 2013.11 ~ 2014.11 Visiting Student at Information Retrieval Lab, Purdue University, West Lafayette, IN, US. Advisor: Prof. Luo Si.
  • 2012.12 ~ 2013.10 Research Intern at Knowledge Mining Group, Microsoft Research Asia, Beijing. Mentor: Dr. Chin-Yew Lin.
  • 2010.09 ~ 2016.04 PhD in School of Computer Science, Beijing Institute of Technology, Beijing
  • 2006.09 ~ 2010.06 B.E. in School of Computer Science, Beijing Institute of Technology, Beijing

Blog

Notes, ideas, and technical write-ups.

From AI4AI to RSI
A technical map of AI4AI and recursive self-improvement: system loops, the Gödel Machine lineage, evaluation standards, and the teams advancing bounded RSI.
August 25, 2026 · Technical Overview
Loop Transformers: A Third Scaling Axis
An evidence-led overview of recurrent depth, from model-loop and layer-loop pretraining to stability, scaling ladders, and test-time adaptation.
July 22, 2026 · Technical Overview
Do Larger Reasoning Models Actually Use Tokens More Efficiently?
Starting from an interview claim: a systematic test with open-weight reasoning models.
July 17, 2026 · Research Notes

View all posts

Selected Honors & Services

  • Senior Member, China Computer Federation (CCF)
  • Executive Committee Member, Youth Working Committee, Chinese Information Processing Society of China (CIPS)
  • 2025, Beijing Science and Technology Award for Scientific and Technological Progress
  • 2025, Beijing Role Model: Most Beautiful Internet Practitioner
  • 2023, Beijing Haiying Talent Program (Young Talent)
  • 2023, CCF Science and Technology Achievement Award
  • 2022, Beijing Nova Program (Innovation Nova)
  • 2022, Wu Wenjun Artificial Intelligence Science and Technology Award

Professional Activities

Program Committees & Area Chairs: ACL, EMNLP, NAACL, CIKM, SIGIR, ECIR, IJCAI, AAAI, NeurIPS, ICLR, CVPR