Haobo Wang
Assistant Professor
Works on weakly supervised learning, including partial-label and noisy-label learning.
Haobo Wang's lab at Zhejiang works in Machine Learning. 90 papers since 2023, 78 at top venues, mostly EMNLP and ACL. Applications close .
At a glance
- papers, 2023–2026
- 23/ year
- at T1 venues
- 87%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 29 papers2026 · T1 23 · collecting
- 24 papers2025 · T1 23
- 22 papers2024 · T1 18
- 15 papers2023 · T1 14
T1 venuesOtherVenues: EMNLP, ACL, NeurIPS, ICML, IJCAI
Research focuspaper titles that use each topic's words
- supervised2 papers
- supervised learning1 paper
- weakly0 papers
- weakly supervised0 papers
- software technology0 papers
Paper list
From the lab homepage.
202629 papers
- AAAI (T1)An Invariant Latent Space Perspective on Language Model Inversion
- ICML (T1)Awakening Visual Reasoning: Mitigating Post-Training Failure in Vision-Text Compression
- Findings of the Conference on Empirical Methods in Natural Language ProcessingCan LLMs Spot Data Anomalies That Make Table QA Impossible?
- SCISDataXman: Selecting and Mixing Pretraining Data via Bilingual Mixture-of-Experts Data Manager
- EMNLP (T1)DeltaMem: Towards Agentic Memory Management via Reinforcement Learning
- KDD (T1)DMind Benchmark: Toward a Holistic Assessment of LLM Capabilities across the Web3 Domain
- IJCAI (T1)Dual Branch Mutual Teaching for Long-Tailed Partial Label Learning
- AAAI (T1)Dual Graph Disambiguation for Multi-Instance Partial-Label Learning
- ACL (T1)Everyone is unique: Towards Behaviorally Heterogeneous Negotiation Dialogue Systems for Debt Collection
- ACL (T1)Fine-Grained Data Ordering Improves Fine-Tuning for Large Language Models
- ACL (T1)FinMRAGBench: A Realistic and Complex Benchmark for Multi-Modal RAG in Financial Document Analysis
- KDD (T1)FLaG: Fine-Grained Latent Grouping for Hallucination Detection
202524 papers
- IJCAI (T1)A Timestep-Adaptive Frequency-Enhancement Framework for Diffusion-based Image Super-Resolution
- ICLR (T1)Bridging the Semantic Gap Between Text and Table: A Case Study on NL2SQL
- MLJCaCOM: Customizing Text-to-Image Diffusion Models in the Wild via Continual Active Selection
- VLDB (T1)CoLA: Model Collaboration for Log-based Anomaly Detection
- EMNLP (T1)CrowdAgent: Multi-Agent Managed Multi-Source Annotation System
- EMNLP (T1)CYCLE-INSTRUCT: Fully Seed-Free Instruction Tuning via Dual Self-Training and Cycle Consistency
- NeurIPS (T1)Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning
- ICLR (T1)Enhance Multi-View Classification Through Multi-Scale Alignment and Expanded Boundary
- EMNLP (T1)Ensembling Prompting Strategies for Zero-Shot Hierarchical Text Classification with Large Language Models
- ICML (T1)How to Steer LLM Latents for Hallucination Detection?
- ACL (T1)Large Margin Representation Learning for Robust Cross-lingual Named Entity Recognition
- EMNLP (T1)LeTS: Learning to Think-and-Search via Process-and-Outcome Reward Hybridization
202422 papers
- AAAI (T1)A Separation and Alignment Framework for Black-box Domain Adaptation
- SCISAsyCo: An Asymmetric Dual-task Co-training Model for Partial-label Learning
- KDD (T1)CoMAL: Contrastive Active Learning for Multi-Label Text Classification
- IJCAI (T1)Common-Individual Semantic Fusion for Multi-View Multi-Label Learning
- VLDB-DemoCORAL: Collaborative Automatic Labeling System based on Large Language Models
- ACL (T1)Data Contamination Calibration for Black-box LLMs
- ICLR (T1)Energy-based Automated Model Evaluation
- COLING (T1)Fast Adaptation via Prompted Data: An Efficient Cross-Domain Fine-tuning Method for Large Language Models
- EMNLP (T1)FlowBench: Revisiting and Benchmarking Workflow-Guided Planning for LLM-based Agents
- ACL (T1)Learning Geometry-Aware Representations for New Intent Discovery
- TASLP (T1)Learning Label-Adaptive Representation for Large-Scale Multi-Label Text Classification
- NeurIPS (T1)Locating What You Need: Towards Adapting Diffusion Models to OOD Concepts In-the-Wild
202315 papers
- AAAI (T1)A Generalized Unbiased Risk Estimator for Learning with Augmented Classes
- ICCV (T1)CAME: Contrastive Automatic Model Evaluation
- WWW (T1)Catch: Collaborative Feature Set Search for Automated Feature Engineering
- NeurIPS (T1)Debiased and Denoised Entity Recognition from Distant Supervision
- IJCAI (T1)Deep Partial Multi-Label Learning with Graph Disambiguation
- EMNLP (T1)FreeAL: Towards Human-Free Active Learning in the Era of Large Language Models
- ICCV (T1)iDAG: Invariant DAG Searching for Domain Generalization
- IJCAI (T1)Latent Processes Identification From Multi-View Time Series
- ICLR (T1)Learning a Data-Driven Policy Network for Pre-Training Automated Feature Engineering
- MLJOnline Binary Classification from Similar and Dissimilar Data
- IJCAI (T1)ProMix: Combating Label Noise via Maximizing Clean Sample Utility
- NeurIPS (T1)Regression with Cost-based Rejection
Where alumni went
Alumni are not listed on the lab homepage.
Apply to ZhejiangFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
- —
- GRE
- See program page
- English
- Per ZJU language requirements
- Fee
- RMB 800
Not yet confirmed for this intake.
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