[HTML][HTML] Advancing Chinese biomedical text mining with community challenges
Objective This study aims to review the recent advances in community challenges for
biomedical text mining in China. Methods We collected information of evaluation tasks …
biomedical text mining in China. Methods We collected information of evaluation tasks …
Alora: Allocating low-rank adaptation for fine-tuning large language models
Parameter-efficient fine-tuning (PEFT) is widely studied for its effectiveness and efficiency in
the era of large language models. Low-rank adaptation (LoRA) has demonstrated …
the era of large language models. Low-rank adaptation (LoRA) has demonstrated …
Milora: Efficient mixture of low-rank adaptation for large language models fine-tuning
Low-rank adaptation (LoRA) and its mixture-of-experts (MOE) variants are highly effective
parameter-efficient fine-tuning (PEFT) methods. However, they introduce significant latency …
parameter-efficient fine-tuning (PEFT) methods. However, they introduce significant latency …
Meddm: Llm-executable clinical guidance tree for clinical decision-making
B Li, T Meng, X Shi, J Zhai, T Ruan - arxiv preprint arxiv:2312.02441, 2023 - arxiv.org
It is becoming increasingly emphasis on the importance of LLM participating in clinical
diagnosis decision-making. However, the low specialization refers to that current medical …
diagnosis decision-making. However, the low specialization refers to that current medical …
Overview of the promptCBLUE shared task in CHIP2023
This paper presents an overview of the PromptCBLUE shared task (http://cips-chip. org.
cn/2023/eval1) held in the CHIP-2023 Conference. This shared task reformulates the …
cn/2023/eval1) held in the CHIP-2023 Conference. This shared task reformulates the …
Generative Models for Automatic Medical Decision Rule Extraction from Text
Medical decision rules play a key role in many clinical decision support systems (CDSS).
However, these rules are conventionally constructed by medical experts, which is expensive …
However, these rules are conventionally constructed by medical experts, which is expensive …
Text2MDT: extracting medical decision trees from medical texts
Knowledge of the medical decision process, which can be modeled as medical decision
trees (MDTs), is critical to build clinical decision support systems. However, the current MDT …
trees (MDTs), is critical to build clinical decision support systems. However, the current MDT …
Advancing Biomedical Text Mining with Community Challenges
The field of biomedical research has witnessed a significant increase in the accumulation of
vast amounts of textual data from various sources such as scientific literatures, electronic …
vast amounts of textual data from various sources such as scientific literatures, electronic …
PARA: Parameter-Efficient Fine-tuning with Prompt Aware Representation Adjustment
In the realm of parameter-efficient fine-tuning (PEFT) methods, while options like LoRA are
available, there is a persistent demand in the industry for a PEFT approach that excels in …
available, there is a persistent demand in the industry for a PEFT approach that excels in …
ECNU-LLM@ CHIP-PromptCBLUE: Prompt Optimization and In-Context Learning for Chinese Medical Tasks
H Zheng, M Guan, Y Mei, Y Li, Y Wu - China Health Information Processing …, 2023 - Springer
Our team, ECNU-LLM, presents a method of in-context learning for enhancing the
performance of large language models without fine-tuning in the 9th China Health …
performance of large language models without fine-tuning in the 9th China Health …