Naiqiang Tan

According to our database, Naiqiang Tan authored at least 26 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Compress the Easy, Explore the Hard: Difficulty-Aware Entropy Regularization for Efficient LLM Reasoning.

Qin-Wen Luo, Sheng Ren, Xiang Chen, Rui Liu, Jun Fang, Naiqiang Tan, Sheng-Jun Huang

CoRR, February, 2026

Who Deserves the Reward? SHARP: Shapley Credit-based Optimization for Multi-Agent System.

Yanming Li, Xuelin Zhang, Wenjie Lu, Ziye Tang, Maodong Wu, Haotian Luo, Tongtong Wu, Zijie Peng, Hongze Mi, Yibo Feng, Naiqiang Tan, Chao Huang, Hong Chen, Li Shen

CoRR, February, 2026

Agent-Omit: Training Efficient LLM Agents for Adaptive Thought and Observation Omission via Agentic Reinforcement Learning.

Yansong Ning, Jun Fang, Naiqiang Tan, Hao Liu

CoRR, February, 2026

Mitigating Safety Tax via Distribution-Grounded Refinement in Large Reasoning Models.

Yingsha Xie, Tiansheng Huang, Enneng Yang, Rui Min, Wenjie Lu, Xiaochun Cao, Naiqiang Tan, Li Shen

CoRR, February, 2026

Darwinian Memory: A Training-Free Self-Regulating Memory System for GUI Agent Evolution.

Hongze Mi, Yibo Feng, Wenjie Lu, Song Cao, Jinyuan Li, Yanming Li, Xuelin Zhang, Haotian Luo, Songyang Peng, He Cui, Tengfei Tian, Jun Fang, Hua Chai, Naiqiang Tan

CoRR, January, 2026

SafeThinker: Reasoning about Risk to Deepen Safety Beyond Shallow Alignment.

Xianya Fang, Xianying Luo, Yadong Wang, Xiang Chen, Yu Tian, Zequn Sun, Rui Liu, Jun Fang, Naiqiang Tan, Yuanning Cui, Sheng-Jun Huang

CoRR, January, 2026

2025

DeepTravel: An End-to-End Agentic Reinforcement Learning Framework for Autonomous Travel Planning Agents.

Yansong Ning, Rui Liu, Jun Wang, Kai Chen, Wei Li, Jun Fang, Kan Zheng, Naiqiang Tan, Hao Liu

CoRR, September, 2025

D-Artemis: A Deliberative Cognitive Framework for Mobile GUI Multi-Agents.

Hongze Mi, Yibo Feng, Wenjie Lu, Yuqi Wang, Jinyuan Li, Song Cao, He Cui, Tengfei Tian, Xuelin Zhang, Haotian Luo, Di Sun, Naiqiang Tan, Gang Pan

CoRR, September, 2025

UltraHorizon: Benchmarking Agent Capabilities in Ultra Long-Horizon Scenarios.

Haotian Luo, Huaisong Zhang, Xuelin Zhang, Haoyu Wang, Zeyu Qin, Wenjie Lu, Guozheng Ma, Haiying He, Yingsha Xie, Qiyang Zhou, Zixuan Hu, Hongze Mi, Yibo Wang, Naiqiang Tan, Hong Chen, Yi R. Fung, Chun Yuan, Li Shen

CoRR, September, 2025

R1-Compress: Long Chain-of-Thought Compression via Chunk Compression and Search.

Yibo Wang, Li Shen, Huanjin Yao, Tiansheng Huang, Rui Liu, Naiqiang Tan, Jiaxing Huang, Kai Zhang, Dacheng Tao

CoRR, May, 2025

Not All Thoughts are Generated Equal: Efficient LLM Reasoning via Multi-Turn Reinforcement Learning.

Yansong Ning, Wei Li, Jun Fang, Naiqiang Tan, Hao Liu

CoRR, May, 2025

AdaR1: From Long-CoT to Hybrid-CoT via Bi-Level Adaptive Reasoning Optimization.

Haotian Luo, Haiying He, Yibo Wang, Jinluan Yang, Rui Liu, Naiqiang Tan, Xiaochun Cao, Dacheng Tao, Li Shen

CoRR, April, 2025

Bag of Tricks for Inference-time Computation of LLM Reasoning.

Fan Liu, Wenshuo Chao, Naiqiang Tan, Hao Liu

CoRR, February, 2025

O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning.

Haotian Luo, Li Shen, Haiying He, Yibo Wang, Shiwei Liu, Wei Li, Naiqiang Tan, Xiaochun Cao, Dacheng Tao

CoRR, January, 2025

Automatic Instruction Data Selection for Large Language Models via Uncertainty-Aware Influence Maximization.

Jindong Han, Hao Liu, Jun Fang, Naiqiang Tan, Hui Xiong

Proceedings of the ACM on Web Conference 2025, 2025

Panacea: Mitigating Harmful Fine-tuning for Large Language Models via Post-fine-tuning Perturbation.

Yibo Wang, Tiansheng Huang, Li Shen, Huanjin Yao, Haotian Luo, Rui Liu, Naiqiang Tan, Jiaxing Huang, Dacheng Tao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Bag of Tricks for Inference-time Computation of LLM Reasoning.

Fan Liu, Wen-Shuo Chao, Naiqiang Tan, Hao Liu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

DiMA: An LLM-Powered Ride-Hailing Assistant at DiDi.

Yansong Ning, Shuowei Cai, Wei Li, Jun Fang, Naiqiang Tan, Hua Chai, Hao Liu

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

2024

Real-World Large-Scale Cellular Localization for Pickup Position Recommendation at Black-Hole.

Ruipeng Gao, Shuli Zhu, Lingkun Li, Xuyu Wang, Yuqin Jiang, Naiqiang Tan, Hua Chai, Peng Qi, Jiqiang Liu, Dan Tao

IEEE Trans. Mob. Comput., December, 2024

Improving First-stage Retrieval of Point-of-interest Search by Pre-training Models.

Lang Mei, Jiaxin Mao, Juan Hu, Naiqiang Tan, Hua Chai, Ji-Rong Wen

ACM Trans. Inf. Syst., May, 2024

BigST: Linear Complexity Spatio-Temporal Graph Neural Network for Traffic Forecasting on Large-Scale Road Networks.

Jindong Han, Weijia Zhang, Hao Liu, Tao Tao, Naiqiang Tan, Hui Xiong

Proc. VLDB Endow., January, 2024

Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction.

Wenzhao Jiang, Jindong Han, Hao Liu, Tao Tao, Naiqiang Tan, Hui Xiong

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

2023

Travel Time Distribution Estimation by Learning Representations Over Temporal Attributed Graphs.

Wanyi Zhou, Xiaolin Xiao, Yue-Jiao Gong, Jia Chen, Jun Fang, Naiqiang Tan, Nan Ma, Qun Li, Hua Chai, Sang-Woon Jeon, Jun Zhang

IEEE Trans. Intell. Transp. Syst., May, 2023

Behavior Modeling for Point of Interest Search.

Haitian Chen, Qingyao Ai, Zhijing Wu, Zhihong Wang, Yiqun Liu, Min Zhang, Shaoping Ma, Juan Hu, Naiqiang Tan, Hua Chai

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

iETA: A Robust and Scalable Incremental Learning Framework for Time-of-Arrival Estimation.

Jindong Han, Hao Liu, Shui Liu, Xi Chen, Naiqiang Tan, Hua Chai, Hui Xiong

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2020

Context-aware Route Recommendation with Weight Learning through Deep Neural Networks.

Huiwen Jia, Jun Fang, Naiqiang Tan, Xinyue Liu, Zengwei Huo, Nan Ma, Guobin Wu, Hua Chai, Xiaohu Qie, Bo Zhang, Yafeng Yin, Siqian Shen

Proceedings of the 2020 American Control Conference, 2020