activity
20232026
most citedCompressing Context to Enhance Inference Efficiency of Large Language Models

3 citations · 13 across the 19 of their papers we have counts for

collaborators
Showing 2023Show all

7 papers · 1 filter

cs.CL2023

A Cross-Attention Augmented Model for Event-Triggered Context-Aware Story Generation

Chen Tang, Tyler Loakman, Chenghua Lin

Despite recent advancements, existing story generation systems continue to encounter difficulties in effectively incorporating contextual and event features, which greatly influenc…

cs.CL2023★ 1 cited

The Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm Generation

Tyler Loakman, Aaron Maladry, Chenghua Lin

Human evaluation is often considered to be the gold standard method of evaluating a Natural Language Generation system. However, whilst its importance is accepted by the community…

cs.CL2023★ 1 cited

ACL Anthology Helper: A Tool to Retrieve and Manage Literature from ACL Anthology

Chen Tang, Frank Guerin, Chenghua Lin

The ACL Anthology is an online repository that serves as a comprehensive collection of publications in the field of natural language processing (NLP) and computational linguistics…

cs.CL2023★ 1 cited

Enhancing Biomedical Lay Summarisation with External Knowledge Graphs

Tomas Goldsack, Zhihao Zhang, Chen Tang +2

Previous approaches for automatic lay summarisation are exclusively reliant on the source article that, given it is written for a technical audience (e.g., researchers), is unlikel…

cs.CL2023

Improving Biomedical Abstractive Summarisation with Knowledge Aggregation from Citation Papers

Chen Tang, Shun Wang, Tomas Goldsack +1

Abstracts derived from biomedical literature possess distinct domain-specific characteristics, including specialised writing styles and biomedical terminologies, which necessitate…

cs.CL2023★ 3 cited

Compressing Context to Enhance Inference Efficiency of Large Language Models

Yucheng Li, Bo Dong, Chenghua Lin +1

Large language models (LLMs) achieved remarkable performance across various tasks. However, they face challenges in managing long documents and extended conversations, due to signi…

cs.CL2023★ 2 cited

Improving Medical Dialogue Generation with Abstract Meaning Representations

Bohao Yang, Chen Tang, Chenghua Lin

Medical Dialogue Generation serves a critical role in telemedicine by facilitating the dissemination of medical expertise to patients. Existing studies focus on incorporating textu…