Unleashing Artificial Cognition: Integrating Multiple AI Systems
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Abstract (arXiv)
In this study, we present an innovative fusion of language models and query analysis techniques to unlock cognition in artificial intelligence. The introduced open-source AI system seamlessly integrates a Chess engine with a language model, enabling it to predict moves and provide strategic explanations. Leveraging a vector database to achieve retrievable answer generation, our AI system elucidates its decision-making process, bridging the gap between raw computation and human-like understanding. Our choice of Chess as the demonstration environment underscores the versatility of our approach. Beyond Chess, our system holds promise for diverse applications, from medical diagnostics to financial forecasting. Our AI system is available at https://github.com/TheOpenSI/CoSMIC.git
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 15 of its 33 references that are in the map. First posted on arXiv 9 Aug 2024.
Builds on
15 of 33 references.
References · 15
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
- 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
- 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,418
- 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,218
- 2022Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Taskscited by 868
- 2024RAFT: Adapting Language Model to Domain Specific RAGcited by 262
- 2024Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?cited by 232
- 2023Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessmentcited by 230
- 2023Orca 2: Teaching Small Language Models How to Reasoncited by 159
- 2024The Impact of Reasoning Step Length on Large Language Modelscited by 153
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Citing papers per year: 2026: 3.
3 papers.