activity
20232025
most citedMaking Pre-trained Language Models Great on Tabular Prediction

2 citations · 6 across the 11 of their papers we have counts for

collaborators
Showing 2024Show all

6 papers · 1 filter

cs.AI2024★ 1 cited

Vision Language Model is NOT All You Need: Augmentation Strategies for Molecule Language Models

Namkyeong Lee, Siddhartha Laghuvarapu, Chanyoung Park +1

Recently, there has been a growing interest among researchers in understanding molecules and their textual descriptions through molecule language models (MoLM). However, despite so…

cs.LG2024

Certifiably Byzantine-Robust Federated Conformal Prediction

Mintong Kang, Zhen Lin, Jimeng Sun +2

Conformal prediction has shown impressive capacity in constructing statistically rigorous prediction sets for machine learning models with exchangeable data samples. The siloed dat…

cs.CL2024

Contextualized Sequence Likelihood: Enhanced Confidence Scores for Natural Language Generation

Zhen Lin, Shubhendu Trivedi, Jimeng Sun

The advent of large language models (LLMs) has dramatically advanced the state-of-the-art in numerous natural language generation tasks. For LLMs to be applied reliably, it is esse…

cs.LG2024

Cross-Table Pretraining towards a Universal Function Space for Heterogeneous Tabular Data

Jintai Chen, Zhen Lin, Qiyuan Chen +1

Tabular data from different tables exhibit significant diversity due to varied definitions and types of features, as well as complex inter-feature and feature-target relationships.…

cs.CL2024★ 2 cited

Making Pre-trained Language Models Great on Tabular Prediction

Jiahuan Yan, Bo Zheng, Hongxia Xu +5

The transferability of deep neural networks (DNNs) has made significant progress in image and language processing. However, due to the heterogeneity among tables, such DNN bonus is…

cs.CL2024

Small Models are LLM Knowledge Triggers on Medical Tabular Prediction

Jiahuan Yan, Jintai Chen, Chaowen Hu +4

Recent development in large language models (LLMs) has demonstrated impressive domain proficiency on unstructured textual or multi-modal tasks. However, despite with intrinsic worl…