## Flow Diagram: Paper Citation Retrieval
### Overview
The image depicts a flow diagram outlining the steps to find a cited paper given a text excerpt. It involves a combination of observation, search actions, and reasoning.
### Components/Axes
* **Input:** A text excerpt citing a paper. The goal is to find the cited paper.
* Text: "You are given a text excerpt, which cites a paper. Your goal is to find the cited paper. In this section, we evaluate the localization ability of CAM when trained on the ILSVRC 2014 benchmark dataset [CITATION]"
* **Thought + Action (Red Boxes):** Represent the reasoning and actions taken to find the paper.
* **Observation (Blue Boxes):** Represent the information gathered from the search engine and references.
* **Search Engine:** Used to search for papers based on queries.
* **References:** A list of cited papers.
### Detailed Analysis
1. **Input:** The process starts with a text excerpt that cites a paper related to the ILSVRC 2014 benchmark dataset.
2. **Thought + Action:** The system hypothesizes that the cited paper is related to the ImageNet dataset and initiates a search using the query "ILSVRC 2014 benchmark" sorted by citations.
* `search(query="ILSVRC 2014 benchmark", sort="citations")`
3. **Observation:** The search engine returns a list of papers.
* Search Engine: ILSVRC 2014 benchmark
1. Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition, K He et al.
2. A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration, Y Li et al.
4. **Thought + Action:** The system identifies that Paper "1" directly mentions the ILSVRC 2014 benchmark in the abstract and decides to read the paper.
* `read_paper("1")`
5. **Observation:** The system observes that the text mentions attending the competition of ILSVRC 2014 and includes a reference.
* Based on this work, we attended the competition of ILSVRC 2014 [26]
* References: [26] O. Russakovsky et al., "Imagenet large scale visual recognition challenge"
6. **Thought + Action:** Based on the text and references, the system infers that the title is "ImageNet large scale visual recognition challenge" and initiates a search.
* `search(query="Imagenet large scale visual recognition challenge", sort="citations")`
7. **Observation:** The search engine returns a list of papers.
* Search Engine: Imagenet large scale visual recognition challenge
1. Imagenet large scale visual recognition challenge, O. Russakovsky et al.
8. **Thought + Action:** The system identifies Paper "1" as the target paper and selects it.
* `select("1")`
### Key Observations
* The system uses a combination of search queries and text analysis to identify the cited paper.
* The system prioritizes papers that directly mention the ILSVRC 2014 benchmark.
* The system uses references to refine the search query.
### Interpretation
The diagram illustrates an automated process for finding cited papers. The system starts with a broad search based on the initial citation and refines the search based on the context and references within the text. The process demonstrates a basic form of information retrieval and reasoning, mimicking how a researcher might manually search for a cited paper. The system's ability to infer the paper's title from the references is a key step in narrowing down the search results.
