6 papers
GRASP: Graph-Reasoning Aided Survey Planning for High-Fidelity Related Work Generation
Haoming Li, Jessica Ouyang
Writing a literature review requires a deep understanding of the relationships among cited papers: how they build on, challenge, or offer alternative perspectives to one another. W…
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…
Multi-round, Chain-of-thought Post-editing for Unfaithful Summaries
Yi-Hui Lee, Xiangci Li, Jessica Ouyang
Recent large language models (LLMs) have demonstrated a remarkable ability to perform natural language understanding and generation tasks. In this work, we investigate the use of L…
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…