CNShanghai Jiao Tong UniversitySchool of Integrated Circuits (Information and Electronic Engineering)
Xiangzhong Fang
教授
Works on 3D video and image processing, with recent work on few-shot class-incremental learning and domain generalization.
Xiangzhong Fang's lab at SJTU works on learning theory & optimization. 24 papers since 2023, 10 at top venues, mostly ICME and AAAI. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 42%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 3 papers2026 · T1 2 · collecting
- 7 papers2025 · T1 5
- 8 papers2024 · T1 2
- 6 papers2023 · T1 1
T1 venuesOtherVenues: ICME, AAAI, EMNLP, ACL, CVPR
Research focuspaper titles that use each topic's words
- Learning theory & optimization8 papers
- few-shot7 papers
- domain4 papers
- generalization3 papers
- recent0 papers
Paper list
From DBLP.
20263 papers
- AAAI (T1)FastFLUX: Pruning FLUX with Block-wise Replacement and Sandwich Training (opens in a new tab)
- ACL (T1)Reasoning with OmniThought: A Large CoT Dataset with Verbosity and Cognitive Difficulty Annotations (opens in a new tab)
- J. Syst. Sci. Complex.Testing Zero-Inflation in Binomial Regression Models with an Application to Electrocardiogram Monitoring on Atrial Fibrillation (opens in a new tab)
20257 papers
- EMNLP (T1)Enhancing Reasoning Abilities of Small LLMs with Cognitive Alignment (opens in a new tab)
- IEEE Trans. Circuits Syst. Video Technol.Few-Shot Class-Incremental Learning via Asymmetric Supervised Contrastive Learning (opens in a new tab)
- ICML (T1)Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization (opens in a new tab)
- ICLR (T1)Linear Multistep Solver Distillation for Fast Sampling of Diffusion Models (opens in a new tab)
- AAAI (T1)Neural Block Compression: Variable Bitrates Feature Blocks for Texture Representation (opens in a new tab)
- CGITask-Adaptive Channel Attention Graph Network for Few-Shot 3D Point Cloud Classification (opens in a new tab)
- EMNLP (T1)Thinking with DistilQwen: A Tale of Four Distilled Reasoning and Reward Model Series (opens in a new tab)
20248 papers
- ICASSP (T1)COPHTC: Contrastive Learning with Prompt Tuning for Hierarchical Text Classification (opens in a new tab)
- ICMEDistillation Excluding Positives for Few-Shot Class-Incremental Learning (opens in a new tab)
- J. Multivar. Anal.Efficient calibration of computer models with multivariate output (opens in a new tab)
- ECCV (T1)Learning Quantized Adaptive Conditions for Diffusion Models (opens in a new tab)
- ICMEMix background and foreground separately: Transformer-based Augmentation Strategies for Domain Generalization (opens in a new tab)
- LREC/COLINGNER-guided Comprehensive Hierarchy-aware Prompt Tuning for Hierarchical Text Classification (opens in a new tab)
- Commun. Stat. Simul. Comput.Sparse calibration based on adaptive lasso penalty for computer models (opens in a new tab)
- Inf.Task-Adaptive Multi-Source Representations for Few-Shot Image Recognition (opens in a new tab)
20236 papers
- Knowl. Based Syst.Boosting domain generalization by domain-aware knowledge distillation (opens in a new tab)
- ICONIPEfficient Attention for Domain Generalization (opens in a new tab)
- CVPR (T1)Few-Shot Class-Incremental Learning via Class-Aware Bilateral Distillation (opens in a new tab)
- ICDM WorkshopLearning and Adapting Diverse Representations for Cross-domain Few-shot Learning (opens in a new tab)
- ICMERethinking Self-Supervision for Few-Shot Class-Incremental Learning (opens in a new tab)
- J. Syst. Sci. Complex.Robust Calibration of Computer Models Based on Huber Loss (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to SJTUFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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