1 citations · 1 across the 5 of their papers we have counts for
8 papers
Benchmarking and Enhancing Agentic Causal Discovery
Pingchuan Ma, Rui Ding, Shuai Wang
LLM agents can now run causal discovery algorithms on a dataset and report what comes out. Whether they do more than that, such as noticing where an algorithm went wrong and fixing…
Demistifying Data and Simulator Assumptions in Supervised Causal Discovery
Pingchuan Ma, Rui Ding, Bojun Huang +1
Supervised causal discovery learns to infer causal structure for a new dataset from training datasets paired with structural labels. These training pairs are typically simulated, m…
LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence
Xingxuan Zhang, Gang Ren, Hao Yuan +57
We introduce LimiX-2, a new model in the LimiX family, developed through model and data scaling guided by our previously established scaling laws. LimiX-2 adopts the Contextual Mec…
Test Time Training for Supervised Causal Learning
Zizhen Deng, Jiaru Zhang, Rui Ding +5
Supervised Causal Learning (SCL) has shown promise in causal discovery by framing it as a supervised learning problem. However, it suffers from significant out-of-distribution gene…
CAST: Achieving Stable LLM-based Text Analysis for Data Analytics
Jinxiang Xie, Zihao Li, Wei He +3
Text analysis of tabular data relies on two core operations: \emph{summarization} for corpus-level theme extraction and \emph{tagging} for row-level labeling. A critical limitation…
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning
Jiaru Zhang, Rui Ding, Qiang Fu +6
Causal discovery is a structured prediction task that aims to predict causal relations among variables based on their data samples. Supervised Causal Learning (SCL) is an emerging…
Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version)
Pingchuan Ma, Rui Ding, Qiang Fu +4
Differentiable causal discovery has made significant advancements in the learning of directed acyclic graphs. However, its application to real-world datasets remains restricted due…
Text2Analysis: A Benchmark of Table Question Answering with Advanced Data Analysis and Unclear Queries
Xinyi He, Mengyu Zhou, Xinrun Xu +9
Tabular data analysis is crucial in various fields, and large language models show promise in this area. However, current research mostly focuses on rudimentary tasks like Text2SQL…