:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Yu, Jianxing, Wang, Shiqi, Yin, Han, Sun, Zhenlong, Xie, Ruobing, Zhang, Bo, Rao, Yanghui
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2410.07673
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial Network
by: Zhao, Yonghe, et al.
Published: (2023)

Detecting Emotional Incongruity of Sarcasm by Commonsense Reasoning
by: Qiu, Ziqi, et al.
Published: (2024)

Clickbait Detection via Large Language Models
by: Wang, Han, et al.
Published: (2023)

iTFKAN: Interpretable Time Series Forecasting with Kolmogorov-Arnold Network
by: Liang, Ziran, et al.
Published: (2025)

How does Bayesian Sampling help Membership Inference Attacks?
by: Liu, Zhenlong, et al.
Published: (2025)

Causal Debiasing Medical Multimodal Representation Learning with Missing Modalities
by: Zhu, Xiaoguang, et al.
Published: (2025)

Disentangled Representation Learning for Causal Inference with Instruments
by: Cheng, Debo, et al.
Published: (2024)

Deep Causal Learning: Representation, Discovery and Inference
by: Deng, Zizhen, et al.
Published: (2022)

On the Representation of Pairwise Causal Background Knowledge and Its Applications in Causal Inference
by: Fang, Zhuangyan, et al.
Published: (2022)

Refinement Provenance Inference: Detecting LLM-Refined Training Prompts from Model Behavior
by: Yin, Bo, et al.
Published: (2026)

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor
by: Ji, Han, et al.
Published: (2025)

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

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

Recency Biased Causal Attention for Time-series Forecasting
by: Hegazy, Kareem, et al.
Published: (2025)

De Novo Molecular Generation from Mass Spectra via Many-Body Enhanced Diffusion
by: Sun, Xichen, et al.
Published: (2026)

Causal Neighbourhood Learning for Invariant Graph Representations
by: Job, Simi, et al.
Published: (2026)

Hierarchical Active Inference using Successor Representations
by: Rangarajan, Prashant, et al.
Published: (2026)

Self-Distillation for Multi-Token Prediction
by: Zhao, Guoliang, et al.
Published: (2026)

Mitigating Clickbait: An Approach to Spoiler Generation Using Multitask Learning
by: Pal, Sayantan, et al.
Published: (2024)

Language Models "Grok" to Copy
by: Lv, Ang, et al.
Published: (2024)

Individual Causal Inference with Structural Causal Model
by: Chang, Daniel T.
Published: (2025)

Personality-guided Public-Private Domain Disentangled Hypergraph-Former Network for Multimodal Depression Detection
by: Fu, Changzeng, et al.
Published: (2025)

LacaDM: A Latent Causal Diffusion Model for Multiobjective Reinforcement Learning
by: Yan, Xueming, et al.
Published: (2025)

GuARD: Effective Anomaly Detection through a Text-Rich and Graph-Informed Language Model
by: Pang, Yunhe, et al.
Published: (2024)

Enhancing Unimodal Latent Representations in Multimodal VAEs through Iterative Amortized Inference
by: Oshima, Yuta, et al.
Published: (2024)

OMNIFLOW: A Physics-Grounded Multimodal Agent for Generalized Scientific Reasoning
by: Wu, Hao, et al.
Published: (2026)

Local Causal Discovery for Statistically Efficient Causal Inference
by: Schubert, Mátyás, et al.
Published: (2025)

Exploratory Causal Inference in SAEnce
by: Mencattini, Tommaso, et al.
Published: (2025)

MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference
by: Li, Bo, et al.
Published: (2026)

Boosting Fine-Grained Visual Anomaly Detection with Coarse-Knowledge-Aware Adversarial Learning
by: Fang, Qingqing, et al.
Published: (2024)

Integrating Unstructured Text into Causal Inference: Empirical Evidence from Real Data
by: Zhou, Boning, et al.
Published: (2026)

A General Causal Inference Framework for Cross-Sectional Observational Data
by: Zhao, Yonghe, et al.
Published: (2024)

Do Large Language Models Show Biases in Causal Learning?
by: Carro, Maria Victoria, et al.
Published: (2024)

Revealing Multimodal Causality with Large Language Models
by: Li, Jin, et al.
Published: (2025)

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

Thermodynamic-Inspired Explainable GeoAI: Uncovering Regime-Dependent Mechanisms in Heterogeneous Spatial Systems
by: Lim, Sooyoung, et al.
Published: (2026)

Deconfounded Time Series Forecasting: A Causal Inference Approach
by: Gao, Wentao, et al.
Published: (2024)

BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning
by: Lin, Haohong, et al.
Published: (2024)

Entropic Causal Inference: Graph Identifiability
by: Compton, Spencer, et al.
Published: (2025)

Out of Context: Reliability in Multimodal Anomaly Detection Requires Contextual Inference
by: Wilkinghoff, Kevin, et al.
Published: (2026)