Keqin Bao

According to our database, Keqin Bao authored at least 43 papers between 2022 and 2026.

Collaborative distances:

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

2026

ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning.

Xiaoyuan Li, Keqin Bao, Moxin Li, Yubo Ma, Yichang Zhang, Wenjie Wang, Fuli Feng, Dayiheng Liu

CoRR, May, 2026

Unified Data Selection for LLM Reasoning.

Xiaoyuan Li, Yubo Ma, Chengpeng Li, Fengbin Zhu, Yiyao Yu, Keqin Bao, Wenjie Wang, Fuli Feng, Dayiheng Liu

CoRR, May, 2026

SkillGraph: Skill-Augmented Reinforcement Learning for Agents via Evolving Skill Graphs.

Xiaoyuan Li, Moxin Li, Keqin Bao, Yubo Ma, Wenjie Wang, Dayiheng Liu, Fuli Feng

CoRR, May, 2026

SAGE: Scalable Automated Robustness Augmentation for LLM Knowledge Evaluation.

Xiaoyuan Li, Yuzhe Wang, Moxin Li, Keqin Bao, Rui Men, Yichang Zhang, Dayiheng Liu, Wenjie Wang, Fuli Feng

CoRR, May, 2026

On Predicting the Post-training Potential of Pre-trained LLMs.

Xiaoyuan Li, Yubo Ma, Kexin Yang, Moxin Li, Keqin Bao, Wenie Wang, Fuli Feng, Dayiheng Liu

CoRR, May, 2026

Towards Sample-Efficient and Stable Reinforcement Learning for LLM-based Recommendation.

Hongxun Ding, Keqin Bao, Jizhi Zhang, Yi Fang, Wenxin Xu, Fuli Feng, Xiangnan He

CoRR, February, 2026

MTR-Bench: A Comprehensive Benchmark for Multi-Turn Reasoning Evaluation.

Xiaoyuan Li, Keqin Bao, Yubo Ma, Moxin Li, Wenjie Wang, Rui Men, Yichang Zhang, Fuli Feng, Dayiheng Liu

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems.

Keqin Bao, Jizhi Zhang, Wenjie Wang, Yang Zhang, Zhengyi Yang, Yanchen Luo, Chong Chen, Fuli Feng, Qi Tian

Trans. Recomm. Syst., December, 2025

Chain of Execution Supervision Promotes General Reasoning in Large Language Models.

Nuo Chen, Zehua Li, Keqin Bao, Junyang Lin, Dayiheng Liu

CoRR, October, 2025

Teaching Language Models to Reason with Tools.

Chengpeng Li, Zhengyang Tang, Ziniu Li, Mingfeng Xue, Keqin Bao, Tian Ding, Ruoyu Sun, Benyou Wang, Xiang Wang, Junyang Lin, Dayiheng Liu

CoRR, October, 2025

Teaching LLM to Reason: Reinforcement Learning from Algorithmic Problems without Code.

Keqin Bao, Nuo Chen, Xiaoyuan Li, Binyuan Hui, Bowen Yu, Fuli Feng, Xiangnan He, Dayiheng Liu

CoRR, July, 2025

Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning.

Shanle Zheng, Keqin Bao, Jizhi Zhang, Yang Zhang, Fuli Feng, Xiangnan He

CoRR, July, 2025

CoRT: Code-integrated Reasoning within Thinking.

Chengpeng Li, Zhengyang Tang, Ziniu Li, Mingfeng Xue, Keqin Bao, Tian Ding, Ruoyu Sun, Benyou Wang, Xiang Wang, Junyang Lin, Dayiheng Liu

CoRR, June, 2025

CoLLM: Integrating Collaborative Embeddings Into Large Language Models for Recommendation.

Yang Zhang, Fuli Feng, Jizhi Zhang, Keqin Bao, Qifan Wang, Xiangnan He

IEEE Trans. Knowl. Data Eng., May, 2025

MTR-Bench: A Comprehensive Benchmark for Multi-Turn Reasoning Evaluation.

Xiaoyuan Li, Keqin Bao, Yubo Ma, Moxin Li, Wenjie Wang, Rui Men, Yichang Zhang, Fuli Feng, Dayiheng Liu, Junyang Lin

CoRR, May, 2025

Envisioning Recommendations on an LLM-Based Agent Platform.

Jizhi Zhang, Keqin Bao, Wenjie Wang, Yang Zhang, Wentao Shi, Wanhong Xu, Fuli Feng, Tat-Seng Chua

Commun. ACM, May, 2025

Fair Recommendation with Biased-Limited Sensitive Attribute.

Jizhi Zhang, Haoyu Shen, Tianhao Shi, Keqin Bao, Xin Chen, Yang Zhang, Fuli Feng

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Agentic Feedback Loop Modeling Improves Recommendation and User Simulation.

Shihao Cai, Jizhi Zhang, Keqin Bao, Chongming Gao, Qifan Wang, Fuli Feng, Xiangnan He

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Navigating Large Language Models for Recommendation: From Architecture to Learning Paradigms and Deployment.

Xinyu Lin, Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Decoding in Latent Spaces for Efficient Inference in LLM-based Recommendation.

Chengbing Wang, Yang Zhang, Zhicheng Wang, Tianhao Shi, Keqin Bao, Fuli Feng, Tat-Seng Chua

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

HellaSwag-Pro: A Large-Scale Bilingual Benchmark for Evaluating the Robustness of LLMs in Commonsense Reasoning.

Xiaoyuan Li, Moxin Li, Rui Men, Yichang Zhang, Keqin Bao, Wenjie Wang, Fuli Feng, Dayiheng Liu, Junyang Lin

Proceedings of the Findings of the Association for Computational Linguistics, 2025

K-order Ranking Preference Optimization for Large Language Models.

Shihao Cai, Chongming Gao, Yang Zhang, Wentao Shi, Jizhi Zhang, Keqin Bao, Qifan Wang, Fuli Feng

Proceedings of the Findings of the Association for Computational Linguistics, 2025

Customizing In-context Learning for Dynamic Interest Adaption in LLM-based Recommendation.

Keqin Bao, Ming Yan, Yang Zhang, Jizhi Zhang, Wenjie Wang, Fuli Feng, Xiangnan He

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

Qwen2.5 Technical Report.

An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, Huan Lin, Jian Yang, Jianhong Tu, Jianwei Zhang, Jianxin Yang, Jiaxi Yang, Jingren Zhou, Junyang Lin, Kai Dang, Keming Lu, Keqin Bao, Kexin Yang, Le Yu, Mei Li, Mingfeng Xue, Pei Zhang, Qin Zhu, Rui Men, Runji Lin, Tianhao Li, Tingyu Xia, Xingzhang Ren, Xuancheng Ren, Yang Fan, Yang Su, Yichang Zhang, Yu Wan, Yuqiong Liu, Zeyu Cui, Zhenru Zhang, Zihan Qiu

CoRR, 2024

Real-Time Personalization for LLM-based Recommendation with Customized In-Context Learning.

Keqin Bao, Ming Yang, Yang Zhang, Jizhi Zhang, Wenjie Wang, Fuli Feng, Xiangnan He

CoRR, 2024

Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendation.

Yang Zhang, Juntao You, Yimeng Bai, Jizhi Zhang, Keqin Bao, Wenjie Wang, Tat-Seng Chua

CoRR, 2024

FLOW: A Feedback LOop FrameWork for Simultaneously Enhancing Recommendation and User Agents.

Shihao Cai, Jizhi Zhang, Keqin Bao, Chongming Gao, Fuli Feng

CoRR, 2024

Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation.

Keqin Bao, Jizhi Zhang, Yang Zhang, Xinyue Huo, Chong Chen, Fuli Feng

CoRR, 2024

Text-like Encoding of Collaborative Information in Large Language Models for Recommendation.

Yang Zhang, Keqin Bao, Ming Yang, Wenjie Wang, Fuli Feng, Xiangnan He

CoRR, 2024

Prospect Personalized Recommendation on Large Language Model-based Agent Platform.

Jizhi Zhang, Keqin Bao, Wenjie Wang, Yang Zhang, Wentao Shi, Wanhong Xu, Fuli Feng, Tat-Seng Chua

CoRR, 2024

Large Language Models for Recommendation: Progresses and Future Directions.

Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Item-side Fairness of Large Language Model-based Recommendation System.

Meng Jiang, Keqin Bao, Jizhi Zhang, Wenjie Wang, Zhengyi Yang, Fuli Feng, Xiangnan He

Proceedings of the ACM on Web Conference 2024, 2024

Large Language Models for Recommendation: Past, Present, and Future.

Keqin Bao, Jizhi Zhang, Xinyu Lin, Yang Zhang, Wenjie Wang, Fuli Feng

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation.

Shihao Cai, Keqin Bao, Hangyu Guo, Jizhi Zhang, Jun Song, Bo Zheng

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Decoding Matters: Addressing Amplification Bias and Homogeneity Issue in Recommendations for Large Language Models.

Keqin Bao, Jizhi Zhang, Yang Zhang, Xinyue Huo, Chong Chen, Fuli Feng

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Text-like Encoding of Collaborative Information in Large Language Models for Recommendation.

Yang Zhang, Keqin Bao, Ming Yan, Wenjie Wang, Fuli Feng, Xiangnan He

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems.

Keqin Bao, Jizhi Zhang, Wenjie Wang, Yang Zhang, Zhengyi Yang, Yancheng Luo, Fuli Feng, Xiangnan He, Qi Tian

CoRR, 2023

Towards Fine-Grained Information: Identifying the Type and Location of Translation Errors.

Keqin Bao, Yu Wan, Dayiheng Liu, Baosong Yang, Wenqiang Lei, Xiangnan He, Derek F. Wong, Jun Xie

CoRR, 2023

Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation.

Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation.

Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

2022

Alibaba-Translate China's Submission for WMT 2022 Metrics Shared Task.

Yu Wan, Keqin Bao, Dayiheng Liu, Baosong Yang, Derek F. Wong, Lidia S. Chao, Wenqiang Lei, Jun Xie

CoRR, 2022

Alibaba-Translate China's Submission for WMT2022 Metrics Shared Task.

Yu Wan, Keqin Bao, Dayiheng Liu, Baosong Yang, Derek F. Wong, Lidia S. Chao, Wenqiang Lei, Jun Xie

Proceedings of the Seventh Conference on Machine Translation, 2022

Alibaba-Translate China's Submission for WMT 2022 Quality Estimation Shared Task.

Keqin Bao, Yu Wan, Dayiheng Liu, Baosong Yang, Wenqiang Lei, Xiangnan He, Derek F. Wong, Jun Xie

Proceedings of the Seventh Conference on Machine Translation, 2022