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