12 citations · 15 across the 5 of their papers we have counts for
5 papers
CaLM: Contrasting Large and Small Language Models to Verify Grounded Generation
I-Hung Hsu, Zifeng Wang, Long T. Le +4
Grounded generation aims to equip language models (LMs) with the ability to produce more credible and accountable responses by accurately citing verifiable sources. However, existi…
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Zilong Wang, Hao Zhang, Chun-Liang Li +8
Table-based reasoning with large language models (LLMs) is a promising direction to tackle many table understanding tasks, such as table-based question answering and fact verificat…
Transformers as Graph-to-Graph Models
James Henderson, Alireza Mohammadshahi, Andrei C. Coman +1
We argue that Transformers are essentially graph-to-graph models, with sequences just being a special case. Attention weights are functionally equivalent to graph edges. Our Graph-…
Summarization with Precise Length Control
Lesly Miculicich, Yujia Xie, Song Wang +1
Many applications of text generation such as summarization benefit from accurately controlling the text length. Existing approaches on length-controlled summarization either result…
Document Summarization with Text Segmentation
Lesly Miculicich, Benjamin Han
In this paper, we exploit the innate document segment structure for improving the extractive summarization task. We build two text segmentation models and find the most optimal str…