Cover Image

Multimodal Negative Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gong, Baoquan, Gao, Xiyuan, Zhu, Pengfei, Hu, Qinghua, Cao, Bing
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Time-Series Contrastive Learning against False Negatives and Class Imbalance
by: Jin, Xiyuan, et al.
Published: (2023)

Every Node is Different: Dynamically Fusing Self-Supervised Tasks for Attributed Graph Clustering
by: Zhu, Pengfei, et al.
Published: (2024)

A Closer Look at the Application of Causal Inference in Graph Representation Learning
by: Gao, Hang, et al.
Published: (2026)

On Limitation of Transformer for Learning HMMs
by: Hu, Jiachen, et al.
Published: (2024)

Robust Multimodal Representation Learning in Healthcare
by: Zhu, Xiaoguang, et al.
Published: (2026)

ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection
by: Bai, Yichen, et al.
Published: (2023)

Geometric Mixture-of-Experts with Curvature-Guided Adaptive Routing for Graph Representation Learning
by: Cao, Haifang, et al.
Published: (2026)

Temporal Imbalance of Positive and Negative Supervision in Class-Incremental Learning
by: Ma, Jinge, et al.
Published: (2026)

Multimodal Representation Learning Conditioned on Semantic Relations
by: Qiao, Yang, et al.
Published: (2025)

Differentially Private Federated Clustering with Random Rebalancing
by: Yang, Xiyuan, et al.
Published: (2025)

On the Completeness of Invariant Geometric Deep Learning Models
by: Li, Zian, et al.
Published: (2024)

Is Distance Matrix Enough for Geometric Deep Learning?
by: Li, Zian, et al.
Published: (2023)

Provably Efficient Action-Manipulation Attack Against Continuous Reinforcement Learning
by: Luo, Zhi, et al.
Published: (2024)

Multimodal Fusion on Low-quality Data: A Comprehensive Survey
by: Zhang, Qingyang, et al.
Published: (2024)

Momentum Contrastive Learning with Enhanced Negative Sampling and Hard Negative Filtering
by: Hoang, Duy, et al.
Published: (2025)

GILT: An LLM-Free, Tuning-Free Graph Foundational Model for In-Context Learning
by: Ma, Weishuo, et al.
Published: (2025)

OCN: Effectively Utilizing Higher-Order Common Neighbors for Better Link Prediction
by: Wang, Juntong, et al.
Published: (2025)

Towards Multimodal Active Learning: Efficient Learning with Limited Paired Data
by: Zhang, Jiancheng, et al.
Published: (2025)

A Layer-wise Analysis of Supervised Fine-Tuning
by: Zhao, Qinghua, et al.
Published: (2026)

MAny: Merge Anything for Multimodal Continual Instruction Tuning
by: Gao, Zijian, et al.
Published: (2026)

Selective Learning: Towards Robust Calibration with Dynamic Regularization
by: Han, Zongbo, et al.
Published: (2024)

Not All Negative Samples Are Equal: LLMs Learn Better from Plausible Reasoning
by: Di, Zixiang, et al.
Published: (2026)

Neuro-Inspired Hierarchical Multimodal Learning
by: Xiao, Xiongye, et al.
Published: (2023)

One Node Per User: Node-Level Federated Learning for Graph Neural Networks
by: Gao, Zhidong, et al.
Published: (2024)

Utilizing Autoregressive Networks for Full Lifecycle Data Generation of Rolling Bearings for RUL Prediction
by: Wang, Junliang, et al.
Published: (2024)

Mimic In-Context Learning for Multimodal Tasks
by: Jiang, Yuchu, et al.
Published: (2025)

BalanceBenchmark: A Survey for Multimodal Imbalance Learning
by: Xu, Shaoxuan, et al.
Published: (2025)

Negative Feedback System as Optimizer for Machine Learning Systems
by: Hasan, Md Munir, et al.
Published: (2021)

Balancing Multimodal Learning through Label Space Reshaping
by: Ma, Xiaoyu, et al.
Published: (2026)

Translation from Wearable PPG to 12-Lead ECG
by: Ji, Hui, et al.
Published: (2025)

One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification
by: Gao, Mengzhou, et al.
Published: (2026)

Reconsidering the Performance of GAE in Link Prediction
by: Ma, Weishuo, et al.
Published: (2024)

Ratio law: mathematical descriptions for a universal relationship between AI performance and input samples
by: Kang, Boming, et al.
Published: (2024)

Seeking the Sufficiency and Necessity Causal Features in Multimodal Representation Learning
by: Chen, Boyu, et al.
Published: (2024)

Multimodal Federated Learning in Healthcare: a Review
by: Thrasher, Jacob, et al.
Published: (2023)

ReCQR: Incorporating conversational query rewriting to improve Multimodal Image Retrieval
by: Hu, Yuan, et al.
Published: (2026)

MINT: Multimodal Instruction Tuning with Multimodal Interaction Grouping
by: Shan, Xiaojun, et al.
Published: (2025)

MedInsightBench: Evaluating Medical Analytics Agents Through Multi-Step Insight Discovery in Multimodal Medical Data
by: Zhu, Zhenghao, et al.
Published: (2025)

Meta-Learn Unimodal Signals with Weak Supervision for Multimodal Sentiment Analysis
by: Mai, Sijie, et al.
Published: (2024)

Autonomous Learning From Success and Failure: Goal-Conditioned Supervised Learning with Negative Feedback
by: Zhang, Zeqiang, et al.
Published: (2025)