赖颂宁 (Sony)

聚宽量化研究员 可信 AI / 概念瓶颈模型 / 鲁棒性

可信 AI 概念瓶颈模型 可编辑 CBM 持续学习 可解释性 鲁棒性

我本科毕业于山东大学信息科学与工程学院(崇新学堂),导师为刘治教授。之后,我在香港科技大学(广州)AI Thrust 与 INFO Hub 担任研究助理,导师为岳玉涛教授

我的研究聚焦于可信 AI,尤其是概念瓶颈模型(CBMs)。近期工作覆盖可编辑与持续学习 CBM、多模态可解释性、概念层安全、医疗 AI、自动驾驶、可靠时间序列预测以及大语言模型可解释性。代表性论文发表于 ICLR 2024NeurIPS 2024ACM MM 2025TMLR 2026ECCV 2026MICCAI 2026ECML-PKDD 2025ICASSP 2026

除 CBM 之外,我也关注时间序列预测中的鲁棒性与忠实性、持续学习、计算机视觉、多模态情感分析和图学习。贯穿这些工作的共同目标,是构建在开放世界部署时依然可靠、可检查且有用的学习系统。

如果你对我的任何研究方向感兴趣,欢迎交流与合作。可以通过 lais0328eee@gmail.com 联系我。

研究方向

可信 AI

面向需要被检查和信任的学习系统,研究可解释性、鲁棒性、忠实性与安全性。

概念瓶颈模型

为视觉、语言、多模态、医疗和自动驾驶场景构建可编辑、可持续学习且安全的概念层接口。

可靠时间序列

构建能够表达不确定性、拒绝不可靠预测,并在分布变化下保持可用的预测系统。

动态

代表性论文

2026

ECCV 2026
Dynamic-V2C

Dynamic-V2C: Editable and Continual Vision-to-Concept Bottleneck Models via Influence Functions

Songning Lai, Shaofeng Liang, Jiayu Yang, Ninghui Feng, Yuxuan Fan, Wenshuo Chen

European Conference on Computer Vision ECCV 2026 CCF B. Accepted.

Dynamic-V2C 将视觉可落地的 V2C tokenization 与 influence-function 编辑引擎结合,使概念瓶颈模型能够在无需完整重训的情况下进行模型编辑、伪相关调试、数据遗忘和持续概念扩展。

项目页

ECCV 2026
AnaPFL

AnaPFL: When Closed-Form Solutions Meet Generalization and Personalization in Personalized Federated Learning

Kejia Fan, Jianheng Tang, Zhirui Yang, Feijiang Han, Yajiang Huang, Run He, Jiaxu Li, Songning Lai, Anfeng Liu, Houbing Herbert Song, Yunhuai Liu, Huiping Zhuang

European Conference on Computer Vision ECCV 2026 CCF B. Accepted.

AnaPFL 从解析视角研究个性化联邦学习,连接闭式解与异质客户端所需的泛化和个性化能力。

MICCAI 2026
SANT-CBM

SANT-CBM: Structurally-Aware and Noise-Tolerant Semi-supervised Concept Bottleneck Models

HongWei Liu, Jia Liu, Songning Lai~

Medical Image Computing and Computer Assisted Intervention MICCAI 2026 CCF B. Provisionally accepted.

SANT-CBM 面向医学图像分类中的半监督概念瓶颈模型,通过 GMM 动态加权降低噪声伪标签影响,并用结构一致性损失对齐临床先验中的概念相关关系。

项目页

TMLR 2026
CAT

Multimodal Deception in Explainable AI: Concept-Level Backdoor Attacks on Concept Bottleneck Models

Songning Lai, Jiayu Yang, Yu Huang, Lijie Hu, Tianlang Xue, Zhangyi Hu, Jiaxu Li, Haicheng Liao, Zongyang Liu, Yutao Yue.

Transactions on Machine Learning Research TMLR 2026.

CAT 与 CAT+ 是首个针对概念瓶颈模型的概念层后门攻击,揭示多模态可解释流程在保持干净样本性能的同时仍可能被语义触发器操纵。

项目页 · 代码

ICLR 2026
ACE

ACE: Attribution-Controlled Knowledge Editing for Multi-hop Factual Recall

Jiayu Yang†, Yuxuan Fan†, Songning Lai†, Shengen Wu, Jiaqi Tang, Chun Kang, Zhijiang Guo, Yutao Yue.

International Conference on Learning Representations ICLR 2026 CCF A Top Tier Core A*.

ACE 基于神经元归因定位并修正 Transformer 内部推理链中的关键 Q-V 路径,解决多跳知识编辑中隐式中间主体失效的问题。

项目页 · 代码

ICASSP 2026
Reliable Time Series

Towards Reliable Time Series Forecasting under Future Uncertainty: Ambiguity and Novelty Rejection Mechanisms

Ninghui Feng†, Songning Lai†, Xin Zhou, Jiayu Yang, Kunlong Feng, Zhenxiao Yin, Fobao Zhou, Zhangyi Hu, Yutao Yue, Yuxuan Liang, Boyu Wang, Hang Zhao

The Conference on ICASSP 2026 CCF B Core A.

该工作结合歧义拒绝和新颖性拒绝,在无需未来真实值的情况下识别低置信预测和分布变化,从而提升时间序列预测可靠性。

项目页

2025

ACM MM 2025
CONCIL

Learning New Concepts, Remembering the Old: Continual Learning for Multimodal Concept Bottleneck Models

Songning Lai, Mingqian Liao, Zhangyi Hu, Jiayu Yang, Wenshuo Chen, Hongru Xiao, Jianheng Tang, Haicheng Liao, Yutao Yue~

The Conference on ACM MM 2025 BNI Track CCF A Top Tier Core A* Oral Outstanding.

CONCIL 首次定义 CBM 中的持续学习问题,并通过递归解析解同时持续学习概念和类别,理论与实验均验证了效率和绝对记忆性质。

项目页 · 代码

ACM MM 2025
FTS

From Guesswork to Guarantee: Towards Faithful Multimedia Web Forecasting with TimeSieve

Songning Lai, Ninghui Feng, Jiechao Gao, Hao Wang, Haochen Sui, Xin Zou, Jiayu Yang, Wenshuo Chen, Lijie Hu, Hang Zhao, Xuming Hu, Yutao Yue

The Conference on ACM MM 2025 CCF A Top Tier Core A*.

FTS 系统检测并缓解 TimeSieve 对随机种子、输入扰动、层扰动和参数扰动的不忠实性,在多个基准上提升稳定性与鲁棒性。

项目页 · 代码

ICRA 2025
DRIVE

DRIVE: Dependable Robust Interpretable Visionary Ensemble Framework in Autonomous Driving

Songning Lai, Tianlang Xue, Hongru Xiao, Lijie Hu, Jiemin Wu, Ruiqiang Xiao, Ninghui Feng, Haicheng Liao, Zhenning Yang, Yutao Yue~

The Conference on ICRA 2025 CCF B Core A*.

DRIVE 提升端到端无监督自动驾驶模型解释的可靠性和稳定性,定义专门指标评估概念式可解释自动驾驶系统的可信程度。

项目页 · 代码

ECML-PKDD 2025
SVCT

Stable Vision Concept Transformers for Medical Diagnosis

Lijie Hu†, Songning Lai†, Yuan Hua, Shu Yang, Jingfeng Zhang, Di Wang

The Conference on ECML-PKDD 2025 CCF B Core A.

SVCT 将视觉 Transformer 与概念特征、去噪扩散平滑结合,在保持医学影像诊断准确率的同时提供稳定可解释的概念层解释。

项目页 · 代码

ICASSP 2025
PEPL

PEPL: Precision-Enhanced Pseudo-Labeling for Fine-Grained Image Classification in Semi-Supervised Learning

Bowen Tian†, Songning Lai†, Lujundong Li, Zhihao Shuai, Runwei Guan, Tian Wu, Yutao Yue~

The Conference on ICASSP 2025 CCF B Core B.

PEPL 利用 CAM 生成并细化伪标签,增强细粒度图像分类中的半监督学习,改善困难视觉类别的标签质量。

项目页

2024

ICLR 2024
FVLC

Faithful Vision-Language Interpretation via Concept Bottleneck Models

Songning Lai, Lijie Hu, Junxiao Wang, Laure Berti and Di Wang

The Twelfth International Conference on Learning Representations ICLR 2024 CCF A Top Tier Core A*.

FVLC 解决 label-free CBM 的不稳定问题,在输入扰动和概念集扰动下显著提升解释和预测稳定性,同时保持接近标准 CBM 的准确率。

项目页 · 代码

NeurIPS 2024
Med-MICN

Towards Multi-dimensional Explanation Alignment for Medical Classification

Lijie Hu†, Songning Lai†, Wenshuo Chen† (equal contribution), Hongru Xiao, Hongbin Lin, Lu Yu, Jingfeng Zhang, and Di Wang

The Conference on Neural Information Processing Systems NeurIPS 2024 CCF A Top Tier Core A*.

Med-MICN 将概念模型、神经符号方法、显著图和概念语义整合到端到端框架中,实现多维解释对齐并提升医学分类性能。

项目页 · 代码

完整论文列表

论文统计: 正在加载...

2026

  • Dynamic-V2C: Editable and Continual Vision-to-Concept Bottleneck Models via Influence Functions, Songning Lai, Shaofeng Liang, Jiayu Yang, Ninghui Feng, Yuxuan Fan, Wenshuo Chen, European Conference on Computer Vision ECCV 2026 (CCF B, Accepted). 项目页
  • AnaPFL: When Closed-Form Solutions Meet Generalization and Personalization in Personalized Federated Learning, Kejia Fan, Jianheng Tang, Zhirui Yang, Feijiang Han, Yajiang Huang, Run He, Jiaxu Li, Songning Lai, Anfeng Liu, Houbing Herbert Song, Yunhuai Liu, Huiping Zhuang, European Conference on Computer Vision ECCV 2026 (CCF B, Accepted).
  • SANT-CBM: Structurally-Aware and Noise-Tolerant Semi-supervised Concept Bottleneck Models, HongWei Liu, Jia Liu, Songning Lai~, Medical Image Computing and Computer Assisted Intervention MICCAI 2026 (CCF B, Provisionally Accepted). 项目页
  • Concept-Consistent Semi-Supervised Learning for Concept Bottleneck Models via Confidence-Guided Pseudo-Label Propagation, Yayue Mai, Songning Lai~, International Conference on Artificial Neural Networks ICANN 2026 (CCF C, Accepted). 论文
  • Multimodal Deception in Explainable AI: Concept-Level Backdoor Attacks on Concept Bottleneck Models, Songning Lai, Jiayu Yang, Yu Huang, Lijie Hu, Tianlang Xue, Zhangyi Hu, Jiaxu Li, Haicheng Liao, Zongyang Liu, Yutao Yue, TMLR 2026 (Accepted).
  • ACE: Attribution-Controlled Knowledge Editing for Multi-hop Factual Recall, Jiayu Yang†, Yuxuan Fan†, Songning Lai†, Shengen Wu, Jiaqi Tang, Chun Kang, Zhijiang Guo, Yutao Yue, ICLR 2026 (CCF A).
  • TOWARDS RELIABLE TIME SERIES FORECASTING UNDER FUTURE UNCERTAINTY: AMBIGUITY AND NOVELTY REJECTION MECHANISMS, Ninghui Feng†, Songning Lai†, Xin Zou, ..., Hang Zhao, ICASSP 2026 (CCF B).
  • TPTD: A Trusted Privacy-Preserving Truth Discovery Scheme for Quality Enhancement in Team-based Mobile Crowd Sensing, Yajiang Huang, ..., Songning Lai, ..., Houbing Herbert Song, Knowledge-Based Systems (KBS) (JCR Q1, IF: 7.2).

2025

  • Learning New Concepts, Remembering the Old: Continual Learning for Multimodal Concept Bottleneck Models, Songning Lai, Mingqian Liao, Zhangyi Hu, Jiayu Yang, Wenshuo Chen, Hongru Xiao, Jianheng Tang, Haicheng Liao, Yutao Yue, ACM MM 2025 Brave New Idea Track (CCF A, Core A*; BNI papers are considered outstanding ACM MM full papers and appear in the main proceedings).
  • From Guesswork to Guarantee: Towards Faithful Multimedia Web Forecasting with TimeSieve, Songning Lai, Ninghui Feng, Jiechao Gao, Hao Wang, Haochen Sui, Xin Zou, Jiayu Yang, Wenshuo Chen, Hang Zhao, Xuming Hu, Yutao Yue, ACM MM 2025 (CCF A, Core A*).
  • DRIVE: Dependable Robust Interpretable Visionary Ensemble Framework in Autonomous Driving, Songning Lai, Ninghui Feng, Jiechao Gao, Hao Wang, Haochen Sui, Xin Zou, Jiayu Yang, Wenshuo Chen, Hang Zhao, Xuming Hu, Yutao Yue, ICRA 2025 (CCF B, Core A*).
  • Stable Vision Concept Transformers for Medical Diagnosis, Lijie Hu†, Songning Lai†, Yuan Hua†, Jingfeng Zhang, Pan Zhou, Di Wang, ECML-PKDD 2025 (CCF B, Core A).
  • PEPL: Precision-Enhanced Pseudo-Labeling for Fine-Grained Image Classification in Semi-Supervised Learning, Bowen Tian†, Songning Lai†, Lujundong Li, Zhihao Shuai, Runwei Guan, Tian Wu, Yutao Yue, ICASSP 2025 (CCF B, Core B).
  • IMTS is Worth Time X Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction, Zhangyi Hu, Jiemin Wu, Hua Xu, Minqian Liao, Ninghui Feng, Bo Gao, Songning Lai, Yutao Yue, ICML 2025 (CCF A, Core A*).
  • Physics-Informed Representation Alignment for Sparse Radio-Map Reconstruction, Jia Haozhe, Wenshuo Chen, Huang Zhihui, Lei Wang, Hongru Xiao, Jia Nanqian, Keming Wu, Songning Lai, Bowen Tian, Yutao Yue, ACM MM 2025 Brave New Idea Track (CCF A, Core A*).
  • Can Audio Language Models Listen Between the Lines? A Study on Metaphorical Reasoning via Unspoken, Hongru Xiao, Xiang Li, Duyi Pan, Longfei Zhang, ZhixueSong, Jiale Han, Songning Lai, Wenshuo Chen, Jing Tang, Benyou Wang, ACM MM 2025 Brave New Idea Track (CCF A, Core A*).
  • ANT: Adaptive Neural Temporal-Aware Text-to-Motion Model, Wenshuo Chen, Kuimou Yu, Jia Haozhe, Kaishen Yuan, Zexu Huang, Bowen Tian, Songning Lai, Hongru Xiao, Erhang Zhang, Lei Wang, Yutao Yue, ACM MM 2025 (CCF A, Core A*).
  • Text2Weight: Bridging Natural Language and Neural Network Weight Spaces, Bowen Tian, Wenshuo Chen, Zexi Li, Songning Lai, Jiemin Wu, Yutao Yue, ACM MM 2025 (CCF A, Core A*).
  • CFSSeg: Closed-Form Solution for Class-Incremental Semantic Segmentation of 2D Images and 3D Point Clouds, Jiaxu Li, Rui Li, Jianyu Qi, Songning Lai, Linpu Lv, Kejia Fan, Jianheng Tang, Yutao Yue, Dongzhan Zhou, Yunhuai Liu, Huiping Zhuang, ACM MM 2025 (CCF A, Core A*).
  • Beyond Patterns: Harnessing Causal Logic for Autonomous Driving Trajectory Prediction, Bonan Wang, Haicheng Liao, Chengyue Wang, Bin Rao, Yanchen Guan, Guyang Yu, Jiaxun Zhang, Songning Lai, Chengzhong Xu, Zhenning Li, IJCAI 2025 (CCF A, Core A*).
  • Boosting Expertise and Efficiency in LLM: A Knowledge-Enhanced Framework for Construction Support, Bin Yang, Hongru Xiao, Zixuan Zeng, Songning Lai, Jiale Han, Yanke Tan and Yiqing Ni, Alexandria Engineering Journal (JCR Q1, IF: 6.8).
  • Generative Knowledge-Guided Review System for Construction Disclosure Documents, Hongru Xiao, Jiankun Zhuanga, Bin Yanga, Jiale Hanb, Yantao Yu and Songning Lai, Advanced Engineering Informatics (JCR Q1, IF: 9.9, CCF B).
  • Automated Detection of Complex Construction Scenes Using a Lightweight Transformer-based Method, Hongru Xiao, Bin Yang, Yujie Lu, Wenshuo Chen, Songning Lai, Biaoli Gao, Automation in Construction (JCR Q1, IF: 9.6).
  • Enhancing domain adaptation for plant diseases detection through Masked Image Consistency in Multi-Granularity Alignment, Guinan Guo, Songning Lai, Qingyang Wu, Yuntao Shou, Wenxu Shi, Expert Systems With Applications (JCR Q1, IF: 8.4, CCF C).
  • Da Yu: Towards USV-Based Image Captioning for Waterway Surveillance and Scene Understanding, Runwei Guan, ...., Songning Lai, ... ,Hui Xiong, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY TCSVT. (IF: 11.1, JCR Q1, CCF B)

2024

  • Faithful Vision-Language Interpretation via Concept Bottleneck Models, Songning Lai, Lijie Hu, Junxiao Wang, Laure Berti and Di Wang, The Twelfth International Conference on Learning Representations ICLR 2024 (CCF A).
  • Towards Multi-dimensional Explanation Alignment for Medical Classification, Lijie Hu†, Songning Lai†, Wenshuo Chen†, Hongru Xiao, Hongbin Lin, Lu Yu, Jingfeng Zhang, and Di Wang, The Conference on Neural Information Processing Systems NeurIPS 2024 (CCF A).
  • Shared and private information learning in multimodal sentiment analysis with deep modal alignment and self-supervised multi-task learning, Songning Lai†, Jiakang Li, Guinan Guo, Xifeng Hu, Yulong Li, Yuan Tan, Zichen Song, Yutong Liu, Zhaoxia Ren~, Chun Wang~, Danmin Miao~ and Zhi Liu~, International Joint Conference on Neural Networks IJCNN 2024 (CCF C).
  • A Comprehensive Review of Community Detection in Graphs, Jiakang Li†, Songning Lai†, Zhihao Shuai, Yuan Tan, Yifan Jia, Mianyang Yu, Zichen Song, Xiaokang Peng, Ziyang Xu, Yongxin Ni, Haifeng Qiu, Jiayu Yang, Yutong Liu, Yonggang Lu~, Neurocomputing (JCR Q1 (IF: 6.0) CCF C).
  • Multimodal Sentiment Analysis: A Survey, Songning Lai, Haoxuan Xu, Xifeng Hu, Zhaoxia Ren~ and Zhi Liu~, Displays (JCR Q1 (IF: 4.3)).
  • Cross-domain car detection model with integrated convolutional block attention mechanism, Haoxuan Xu†, Songning Lai† and Yang Yang~, Image and Vision Computing (JCR Q1 (IF: 4.7) CCF C).
  • Predicting Lysine Phosphoglycerylation Sites using Bidirectional Encoder Representations with Transformers & Protein Feature Extraction and Selection, Songning Lai, Xifeng Hu, Jing Han, Chun Wang, Subhas Mukhopadhyay, Zhi Liu~ and Lan Ye~, 2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics CISP-BMEI 2022 (Tsinghua B).

荣誉与奖励

🏆
NIPS 2024 Travel AwardsConference Award
🏆
ICRA 2025 Travel AwardsConference Award
IEEE/EI (CISP-BMEI 2022) 最佳论文奖Best Paper
🥇
全国大学生数学建模竞赛国家一等奖Top 0.6%
🥇
MathorCup 高校数学建模挑战赛国家一等奖Top 3%
🥈
全国大学生电子设计竞赛山东省二等奖Provincial
🥈
全国密码数学挑战赛华东赛区二等奖Regional
🎓
山东省优秀毕业生Provincial
🎓
山东大学优秀毕业生University
📊
40 余项校级奖励Multiple Categories

覆盖学科竞赛、社会实践、创新创业、体育、美育、志愿服务、奖学金等多个方面。

教育与科研经历

🔬
2024 年 4 月 - 2025 年 9 月
香港科技大学(广州)- 研究助理
AI Thrust & INFO Hub
🌍
2023 年 4 月 - 2024 年 3 月
KAUST - 访问学生
国际科研经历
🎓
2020 年 9 月 - 2024 年 6 月
山东大学 - 理学学士
信息科学与工程学院(EECS)

服务与领导力

📝
会议与期刊审稿人
ECAI2024ICML2024KDD2024ICLR2025CVPR2025ICCV2025NIPS2025ACM MM 2025IJCAI2025Expert Systems+ More
👨‍💼
崇新学堂班长
山东省先进班集体山东大学十佳班级
❤️
优秀志愿者
130h 志愿服务总时长

合作者

👨‍💻
科研合作者
👨‍💻
科研合作者
👨‍💻
科研合作者
👨‍💻
科研合作者
👨‍💻
科研合作者
👨‍💻
科研合作者

留言板

欢迎留下你的想法、建议或合作意向。

  • 💬 分享你的想法和反馈
  • 🎉 留下祝福和鼓励
  • 🤝 提出合作或交流建议
  • 📝 分享你的学术见解

说明:留言板使用 GitHub Discussions,因此需要登录 GitHub。