3 citations · 4 across the 6 of their papers we have counts for
4 papers · 1 filter
ALR: A Retrieve-then-Reason Framework for Long-context Question Answering
Huayang Li, Pat Verga, Priyanka Sen +5
The context window of large language models (LLMs) has been extended significantly in recent years. However, while the context length that the LLM can process has grown, the capabi…
Change My Frame: Reframing in the Wild in r/ChangeMyView
Arturo Martínez Peguero, Taro Watanabe
Recent work in reframing, within the scope of text style transfer, has so far made use of out-of-context, task-prompted utterances in order to produce neutralizing or optimistic re…
On the Transformations across Reward Model, Parameter Update, and In-Context Prompt
Deng Cai, Huayang Li, Tingchen Fu +11
Despite the general capabilities of pre-trained large language models (LLMs), they still need further adaptation to better serve practical applications. In this paper, we demonstra…
JDocQA: Japanese Document Question Answering Dataset for Generative Language Models
Eri Onami, Shuhei Kurita, Taiki Miyanishi +1
Document question answering is a task of question answering on given documents such as reports, slides, pamphlets, and websites, and it is a truly demanding task as paper and elect…