30 citations · 61 across the 20 of their papers we have counts for
7 papers · 1 filter
How Does Knowledge Selection Help Retrieval Augmented Generation?
Xiangci Li, Jessica Ouyang
Retrieval-augmented generation (RAG) is a powerful method for enhancing natural language generation by integrating external knowledge into a model's output. While prior work has de…
Improving Citation Text Generation: Overcoming Limitations in Length Control
Biswadip Mandal, Xiangci Li, Jessica Ouyang
A key challenge in citation text generation is that the length of generated text often differs from the length of the target, lowering the quality of the generation. While prior wo…
Minimal Evidence Group Identification for Claim Verification
Xiangci Li, Sihao Chen, Rajvi Kapadia +2
Claim verification in real-world settings (e.g. against a large collection of candidate evidences retrieved from the web) typically requires identifying and aggregating a complete…
Related Work and Citation Text Generation: A Survey
Xiangci Li, Jessica Ouyang
To convince readers of the novelty of their research paper, authors must perform a literature review and compose a coherent story that connects and relates prior works to the curre…
A Knowledge Plug-and-Play Test Bed for Open-domain Dialogue Generation
Xiangci Li, Linfeng Song, Lifeng Jin +3
Knowledge-based, open-domain dialogue generation aims to build chit-chat systems that talk to humans using mined support knowledge. Many types and sources of knowledge have previou…
Contextualizing Generated Citation Texts
Biswadip Mandal, Xiangci Li, Jessica Ouyang
Abstractive citation text generation is usually framed as an infilling task, where a sequence-to-sequence model is trained to generate a citation given a reference paper and the co…
Explaining Relationships Among Research Papers
Xiangci Li, Jessica Ouyang
Due to the rapid pace of research publications, keeping up to date with all the latest related papers is very time-consuming, even with daily feed tools. There is a need for automa…