35 citations · 49 across the 12 of their papers we have counts for
11 papers · 1 filter
Towards Improving Interpretability of Language Model Generation through a Structured Knowledge Discovery Approach
Shuqi Liu, Han Wu, Guanzhi Deng +3
Knowledge-enhanced text generation aims to enhance the quality of generated text by utilizing internal or external knowledge sources. While language models have demonstrated impres…
Fact-and-Reflection (FaR) Improves Confidence Calibration of Large Language Models
Xinran Zhao, Hongming Zhang, Xiaoman Pan +4
For a LLM to be trustworthy, its confidence level should be well-calibrated with its actual performance. While it is now common sense that LLM performances are greatly impacted by…
MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning
Fuxiao Liu, Xiaoyang Wang, Wenlin Yao +5
With the rapid development of large language models (LLMs) and their integration into large multimodal models (LMMs), there has been impressive progress in zero-shot completion of…
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning
Xuansheng Wu, Wenlin Yao, Jianshu Chen +4
Large Language Models (LLMs) have achieved remarkable success, where instruction tuning is the critical step in aligning LLMs with user intentions. In this work, we investigate how…
ZeroKBC: A Comprehensive Benchmark for Zero-Shot Knowledge Base Completion
Pei Chen, Wenlin Yao, Hongming Zhang +4
Knowledge base completion (KBC) aims to predict the missing links in knowledge graphs. Previous KBC tasks and approaches mainly focus on the setting where all test entities and rel…
Join-Chain Network: A Logical Reasoning View of the Multi-head Attention in Transformer
Jianyi Zhang, Yiran Chen, Jianshu Chen
Developing neural architectures that are capable of logical reasoning has become increasingly important for a wide range of applications (e.g., natural language processing). Toward…