GPT Unable to Find Research Articles

Hi All -

I used to be able to have ChatGPT help me with research, but using both GPT4 and Plugins is no longer able to access research articles (or at least read the abstracts so I can be pointed to the right place). Is there a reason this is no longer allowed? Now ChatGPT just tells me which prompts to enter into IEExplore or Google Scholar rather than just indexing and pulling back the relevant results.

Can you be more specific.

Are you using ChatGPT Plus?

Are you using a custom GPT?

What prompt are you using?

Can you show an example of what you used that did not work and what you expected?

Also actual screen shots along with the text posted as text help. The screen shot can be used to identify information that you might not think is relevant, the text is useful for searching to find the post again in the future.

Are you using ChatGPT Plus?


Are you using a custom GPT?


What prompt are you using?

Prompt: Is there any research or papers that demonstrate the mathematical models that explain impact of cpu and ram utilization on defects in embedded devices?

I attempted to access several academic papers and articles that could provide detailed information on efficient logging systems for embedded devices with low CPU and memory utilization. However, I encountered access restrictions and was unable to retrieve the content from these sources.

To find relevant academic papers or detailed examples, I recommend exploring databases such as IEEE Xplore, Springer, ResearchGate, and Semantic Scholar. You might also find valuable information in specialized journals related to embedded systems, computer engineering, and IoT (Internet of Things) technologies. Accessing these resources might require institutional access or individual subscriptions.

For specific studies or implementations, you might want to search for terms like “low-overhead logging in embedded systems”, “efficient data logging for IoT devices”, “resource-efficient logging methods in embedded computing”, or “lightweight logging protocols for microcontrollers”. These queries are likely to lead you to relevant research papers or case studies in this domain.

Can you show an example of what you used that did not work and what you expected?

I expected to see that ChatGPT would return some research articles in the response that I could read.


That is a reproducible problem.

Tried your prompt with ChatGPT Plus

using both GPT-3.5

and GPT-4 models

and also using custom GPT - Web Browser

and get similar replies with no hyperlinks.

If I find something similar to what you seek with hyperlinks will reply back.

If you are willing to use preprints then modifying the prompt with an instruction like

Please search arXiv also.

is returning hyperlinks.

Using ChatGPT Plus with GPT-4


Is there any research or papers that demonstrate the mathematical models that explain impact of cpu and ram utilization on defects in embedded devices? Please search arXiv also.


I found a paper titled “D-Box: DMA-enabled Compartmentalization for Embedded Applications” that discusses the impact of Direct Memory Access (DMA) on the security and performance of embedded devices. The paper presents a systematic approach called D-Box to enable secure DMA operations in embedded applications using real-time operating systems. D-Box seeks to provide explicit protections, holistic DMA support, and ensure power and performance efficiency while maintaining compatibility and applicability for legacy applications. The study emphasizes the importance of DMA in improving the power and performance requirements of embedded applications while addressing security challenges associated with resource isolation in microcontrollers【18†source】【19†source】【20†source】. You can access the full text for more detailed information and mathematical models through the DOI: 10.14722/ndss.2022.24053.

Clicking the link

[2201.05199] D-Box: DMA-enabled Compartmentalization for Embedded Applications

The DOI in the clicked link leads to

Using GPTs Hunter

searched for research papers, found and tried


Is there any research or papers that demonstrate the mathematical models that explain impact of cpu and ram utilization on defects in embedded devices?

Research Papers

I found some research papers that address aspects of CPU and RAM utilization and their potential impacts on systems, which may include defects in embedded devices. Here are a few relevant papers:

  1. Debian Package Usage Profiler for Debian Based Systems: This paper discusses optimizing Debian-based systems, like Ubuntu, for embedded/automotive platforms. It focuses on identifying unused/redundant content in the system to reduce the general purpose distribution to an application-specific distribution. This involves collecting usage data to suggest parts of the system that can be removed without impacting functionality. This paper might provide insights into how CPU and RAM utilization could be optimized in embedded devices to reduce defects or inefficiencies.

  2. Load-Balancing for Improving User Responsiveness on Multicore Embedded Systems: This research focuses on improving real-time performance by reducing user waiting time on multicore systems that use a partitioned per-CPU run queue scheduling technique. It aims to minimize the cost of task migration by considering the importance level of running tasks and optimizing per-CPU utilization on multicore embedded systems.

  3. Using Learned Indexes to Improve Time Series Indexing Performance on Embedded Sensor Devices: This paper demonstrates how applying learned indexes that develop space-efficient summaries of the data can dramatically improve the query performance and predictability on embedded sensor and IoT devices with very limited memory and CPU resources.

  4. Parallelizing Workload Execution in Embedded and High-Performance Heterogeneous Systems: This paper introduces a software-defined framework enabling the parallel utilization of all programmable processing resources available in heterogeneous system-on-chip (SoC), including FPGA-based hardware accelerators and CPUs. It provides insights into distributing tasks among all resources to exploit all computing devices while minimizing load unbalance.

These papers cover a range of approaches and methodologies for handling CPU and RAM utilization in embedded systems and the potential impact on system defects. They might not directly answer the question of mathematical models for CPU and RAM utilization impacts on defects, but they provide a foundational understanding and methodologies that might be relevant to the topic. For more detailed and specific information, further research and reading into these papers and related citations might be necessary.

Clicking on Read More for the first entry is a valid link to

There are many custom GPTs, you might find one that works or even create your own custom GPT.