5 papers
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…
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…
SECRET: Towards Scalable and Efficient Code Retrieval via Segmented Deep Hashing
Wenchao Gu, Ensheng Shi, Yanlin Wang +5
Code retrieval, which retrieves code snippets based on users' natural language descriptions, is widely used by developers and plays a pivotal role in real-world software developmen…
CoCoST: Automatic Complex Code Generation with Online Searching and Correctness Testing
Xinyi He, Jiaru Zou, Yun Lin +4
Large Language Models have revolutionized code generation ability by converting natural language descriptions into executable code. However, generating complex code within real-wor…
TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning
Yuan Sui, Jiaru Zou, Mengyu Zhou +4
Table reasoning tasks have shown remarkable progress with the development of large language models (LLMs), which involve interpreting and drawing conclusions from tabular data base…