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Methodology
← Learning Types
Machine Learning
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Learning Types
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Weakly Supervised Learning
3895 directly classified papers
Papers per year
2002: 5
2003: 3
2004: 3
2005: 1
2006: 7
2007: 8
2008: 7
2009: 13
2010: 20
2011: 7
2012: 11
2013: 43
2014: 35
2015: 66
2016: 74
2017: 133
2018: 194
2019: 388
2020: 388
2021: 566
2022: 469
2023: 588
2024: 435
2025: 350
2026: 81
Papers
Categorical Attention: Fine-grained Language-guided Noise Filtering Network for Occluded Person Re-Identification
IJCAI 2025
Weakly-Supervised Movie Trailer Generation Driven by Multi-Modal Semantic Consistency
IJCAI 2025
Ask-Before-Detection: Identifying and Mitigating Conformity Bias in LLM-Powered Error Detector for Math Word Problem Solutions
ACL 2025
Crowd Comparative Reasoning: Unlocking Comprehensive Evaluations for LLM-as-a-Judge
ACL 2025
Pattern Recognition or Medical Knowledge? The Problem with Multiple-Choice Questions in Medicine
ACL 2025
Self-Taught Agentic Long Context Understanding
ACL 2025
Disentangling Biased Knowledge from Reasoning in Large Language Models via Machine Unlearning
ACL 2025
Instance-Selection-Inspired Undersampling Strategies for Bias Reduction in Small and Large Language Models for Binary Text Classification
ACL 2025
Mitigating Confounding in Speech-Based Dementia Detection through Weight Masking
ACL 2025
Lost in Literalism: How Supervised Training Shapes Translationese in LLMs
ACL 2025
Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback
ACL 2025
QAEval: Mixture of Evaluators for Question-Answering Task Evaluation
ACL 2025
Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge?
ACL 2025
How to Mitigate Overfitting in Weak-to-strong Generalization?
ACL 2025
Can’t See the Forest for the Trees: Benchmarking Multimodal Safety Awareness for Multimodal LLMs
ACL 2025
Revealing the Deceptiveness of Knowledge Editing: A Mechanistic Analysis of Superficial Editing
ACL 2025
OmniAlign-V: Towards Enhanced Alignment of MLLMs with Human Preference
ACL 2025
Synergistic Weak-Strong Collaboration by Aligning Preferences
ACL 2025
Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets
ACL 2025
Safety Alignment via Constrained Knowledge Unlearning
ACL 2025
CheXalign: Preference fine-tuning in chest X-ray interpretation models without human feedback
ACL 2025
Are the Values of LLMs Structurally Aligned with Humans? A Causal Perspective
ACL 2025
RAEmoLLM: Retrieval Augmented LLMs for Cross-Domain Misinformation Detection Using In-Context Learning Based on Emotional Information
ACL 2025
Graphically Speaking: Unmasking Abuse in Social Media with Conversation Insights
ACL 2025
Hard Negatives, Hard Lessons: Revisiting Training Data Quality for Robust Information Retrieval with LLMs
EMNLP 2025
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