4 papers
When Reasoning Meets Information Aggregation: A Case Study with Sports Narratives
Yebowen Hu, Kaiqiang Song, Sangwoo Cho +5
Reasoning is most powerful when an LLM accurately aggregates relevant information. We examine the critical role of information aggregation in reasoning by requiring the LLM to anal…
Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models
Jiaao Chen, Xiaoman Pan, Dian Yu +4
We investigate how to elicit compositional generalization capabilities in large language models (LLMs). Compositional generalization empowers LLMs to solve complex problems by comb…
SportsMetrics: Blending Text and Numerical Data to Understand Information Fusion in LLMs
Yebowen Hu, Kaiqiang Song, Sangwoo Cho +4
Large language models hold significant potential for integrating various data types, such as text documents and database records, for advanced analytics. However, blending text and…
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…