Page 52 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

4 Sequence Diagram

5 References

[1] Towards Automatic Evaluation for LLMs’ Clinical Capabilities: Metric, Data, and Algorithm.
2024. arXiv. https:// arxiv .org/ abs/ 2403 .16446.
[2] Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge
Graphs. 2024. arXiv. https:// arxiv .org/ abs/ 2406 .14282.
[3] Towards Structured Understanding of Marketer Demands with Analogical Reasoning
Augmented LLMs. 2024. arXiv. https:// arxiv .org/ abs/ 2401 .04319.
[4] KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents. 2024. arXiv. https://
arxiv .org/ abs/ 2403 .03101.
[5] RJUA-MedDQA: A Multimodal Benchmark for Medical Document Question Answering
and Clinical Reasoning. 2024. ACM Digital Library. https:// dl .acm .org/ doi/ 10 .1145/
3637528 .3671644.
[6] Effectively PAIRing LLMs with Online Marketing via Progressive Prompting Augmentation.
2023. arXiv. https:// arxiv .org/ pdf/ 2312 .05276.
[7] FoRAG: Factuality-Optimized Retrieval Augmented Generation for Web-Enhanced Long-
form Question Answering. 2024. ACM Digital Library. https:// dl .acm .org/ doi/ 10 .1145/
3637528 .3672065.
[8] EDiT: A Local-SGD-Based Efficient Distributed Training Method for Large Language
Models. 2024. OpenReview. https:// openreview .net/ forum ?id = xtlMtbVfWu.
[9] Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning. 2023.
arXiv. https:// arxiv .org/ abs/ 2312 .03248.
[10] Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs.
2025. arXiv. https:// arxiv .org/ abs/ 2503 .05139.
[11] Alipay. 2024. “RJUA_Ant_QA.” GitHub. https:// github .com/ alipay/ RJU _Ant _QA.
[12] Alipay-Med. 2024. “medDQA_benchmark.” GitHub. https:// github .com/ Alipay -Med/
medDQA _benchmark.
[13] Alipay-Med. 2024. “SPs_benchmark.” GitHub. https:// github .com/ Alipay -Med/ SPs
_benchmark.

16