activity
20232025
most citedLarge Language Models and Causal Inference in Collaboration: A Survey

14 citations · 21 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2025

Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings

Aakriti Agrawal, Gouthaman KV, Rohith Aralikatti +6

Hallucinations in Large Vision-Language Models (LVLMs) remain a persistent challenge, often stemming from inadequate integration of visual information during multimodal reasoning.…

cs.CL2024★ 3 cited

Ensuring Safety and Trust: Analyzing the Risks of Large Language Models in Medicine

Yifan Yang, Qiao Jin, Robert Leaman +15

The remarkable capabilities of Large Language Models (LLMs) make them increasingly compelling for adoption in real-world healthcare applications. However, the risks associated with…

cs.IR2024

CSRec: Rethinking Sequential Recommendation from A Causal Perspective

Xiaoyu Liu, Jiaxin Yuan, Yuhang Zhou +3

The essence of sequential recommender systems (RecSys) lies in understanding how users make decisions. Most existing approaches frame the task as sequential prediction based on use…

cs.LG2024

FMint: Bridging Human Designed and Data Pretrained Models for Differential Equation Foundation Model

Zezheng Song, Jiaxin Yuan, Haizhao Yang

The fast simulation of dynamical systems is a key challenge in many scientific and engineering applications, such as weather forecasting, disease control, and drug discovery. With…

cs.CL2024★ 14 cited

Large Language Models and Causal Inference in Collaboration: A Survey

Xiaoyu Liu, Paiheng Xu, Junda Wu +10

Causal inference has shown potential in enhancing the predictive accuracy, fairness, robustness, and explainability of Natural Language Processing (NLP) models by capturing causal…

cs.LG2023★ 1 cited

C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder

Xiaoyu Liu, Jiaxin Yuan, Bang An +3

Representation learning assumes that real-world data is generated by a few semantically meaningful generative factors (i.e., sources of variation) and aims to discover them in the…

cs.LG2023★ 3 cited

DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization

Guowei Xu, Ruijie Zheng, Yongyuan Liang +12

Visual reinforcement learning (RL) has shown promise in continuous control tasks. Despite its progress, current algorithms are still unsatisfactory in virtually every aspect of the…

math.OC2023

Optimal control for sampling the transition path process and estimating rates

Jiaxin Yuan, Amar Shah, Channing Bentz +1

Many processes in nature such as conformal changes in biomolecules and clusters of interacting particles, genetic switches, mechanical or electromechanical oscillators with added n…