Knowledge Tree
GPT 3.5
Facts (10)
Sources
Building Trustworthy NeuroSymbolic AI Systems - arXiv arxiv.org 5 facts
referenceZiems et al. (2022) conducted experiments on seven different Large Language Models using a moral integrity dataset comprising 20,000 samples and instructions to investigate whether GPT-3.5's behavior regarding moral questions is unique.
claimThe authors of 'Building Trustworthy NeuroSymbolic AI Systems' plan to automate user-level explanations without dependence on pre-trained LLMs like GPT-3.5.
measurementIn a performance comparison on the PRIMATE dataset, the knowledge-powered CREST framework showed an improvement of 6% in PHQ-9 answerability and 21% in BLEURT scores compared to GPT-3.5.
claimGPT-3.5, Claude, and GPT-4.0 adhere more closely to instructions than LLama2 (Touvron et al. 2023), Vicuna (Chiang et al. 2023), and Falcon (Penedo et al. 2023).
claimGPT 3.5 exhibits fragility in its safety and instruction-following capabilities, as paraphrased versions of an initial query can disrupt the model's performance.
The construction and refined extraction techniques of knowledge ... nature.com Feb 10, 2026 2 facts
claimGPT-3.5 is a language model capable of natural language understanding and generation, though it performs with more limitations compared to GPT-4.
claimThe study compares a fine-tuned DeepSeek-R1 70B LoRA model against baseline models including the original DeepSeek-R1 70B, GPT-4, GPT-3.5, and LLaMA3 70B to assess task performance improvements.
Large Language Models Meet Knowledge Graphs for Question ... arxiv.org Sep 22, 2025 1 fact
referenceThe ODA method, proposed by Sun et al. in 2024, uses ODA-based knowledge graph retrieval with GPT-4 and GPT-3.5 models to perform KBQA tasks, evaluated using Hits@1 and Acc metrics on the QALD10-en dataset.
Track: Poster Session 3 - aistats 2026 virtual.aistats.org 1 fact
claimAdversarial attacks on Large Language Models (LLMs) for time series forecasting lead to more severe performance degradation than random noise across models including LLMTime with GPT-3.5, GPT-4, LLaMa, Mistral, TimeGPT, and TimeLLM.
Unknown source 1 fact
claimThe research paper 'Towards the Automation of Knowledge Graph Construction Using ...' explores the semi-automatic and automatic construction of knowledge graphs using state-of-the-art large language models including Mixtral 8x22B Instruct v0.1, GPT-4o, and GPT-3.5.