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20242026
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cs.CL2026

A Principle-Driven Adaptive Policy for Group Cognitive Stimulation Dialogue for Elderly with Cognitive Impairment

Jiyue Jiang, Yanyu Chen, Pengan Chen +7

Cognitive impairment is becoming a major public health challenge. Cognitive Stimulation Therapy (CST) is an effective intervention for cognitive impairment, but traditional methods…

cs.CL2025

Benchmarking Large Language Models on Multiple Tasks in Bioinformatics NLP with Prompting

Jiyue Jiang, Pengan Chen, Jiuming Wang +13

Large language models (LLMs) have become important tools in solving biological problems, offering improvements in accuracy and adaptability over conventional methods. Several bench…

cs.CL2025

Developing and Utilizing a Large-Scale Cantonese Dataset for Multi-Tasking in Large Language Models

Jiyue Jiang, Alfred Kar Yin Truong, Yanyu Chen +7

High-quality data resources play a crucial role in learning large language models (LLMs), particularly for low-resource languages like Cantonese. Despite having more than 85 millio…

cs.CL2025

How Well Do LLMs Handle Cantonese? Benchmarking Cantonese Capabilities of Large Language Models

Jiyue Jiang, Pengan Chen, Liheng Chen +5

The rapid evolution of large language models (LLMs) has transformed the competitive landscape in natural language processing (NLP), particularly for English and other data-rich lan…

cs.CL2024

Diffusion of Thoughts: Chain-of-Thought Reasoning in Diffusion Language Models

Jiacheng Ye, Shansan Gong, Liheng Chen +8

Recently, diffusion models have garnered significant interest in the field of text processing due to their many potential advantages compared to conventional autoregressive models.…

cs.CL2024

Forewarned is Forearmed: Leveraging LLMs for Data Synthesis through Failure-Inducing Exploration

Qintong Li, Jiahui Gao, Sheng Wang +6

Large language models (LLMs) have significantly benefited from training on diverse, high-quality task-specific data, leading to impressive performance across a range of downstream…