## Diagram: Citation Resolution Workflow
### Overview
The image depicts a simplified workflow for resolving citations in text using an AI agent. It consists of three components:
1. A text box containing a sentence with an embedded citation placeholder.
2. A robot illustration interacting with a computer.
3. A text box displaying the resolved citation.
### Components/Axes
- **Left Text Box**:
- **Content**: "Find the paper cited in this text: 'ESIM is another high performing model for sentence-pair classification tasks, particularly when used with ELMo embeddings [CITATION]'"
- **Purpose**: Input text with an unresolved citation.
- **Robot Illustration**:
- **Position**: Center of the diagram.
- **Details**: A stylized robot seated at a desk with a computer, symbolizing an AI agent performing a search.
- **Right Text Box**:
- **Content**: "After searching, I think the cited paper is: 'Deep contextualized word representations'"
- **Purpose**: Output text with the resolved citation.
### Detailed Analysis
- **Textual Content**:
- The left text box includes a citation placeholder (`[CITATION]`) within a sentence discussing the ESIM model and its use with ELMo embeddings.
- The right text box resolves the citation to "Deep contextualized word representations," referencing the foundational paper by Devlin et al. (2018) on BERT.
- **Flow**:
- The workflow progresses from the left text box → robot → right text box, indicating a search process to resolve the citation.
### Key Observations
- The citation placeholder is explicitly marked as `[CITATION]`, suggesting a templated or automated system for citation resolution.
- The resolved citation refers to a well-known paper in NLP, implying the robot’s search capability is context-aware.
### Interpretation
This diagram illustrates a conceptual pipeline where an AI agent (robot) resolves citations in text by searching for relevant papers. The example uses a real-world NLP citation (ESIM + ELMo) and resolves it to the seminal BERT paper, highlighting the agent’s ability to infer contextually relevant references. The absence of numerical data or uncertainty suggests this is a schematic representation rather than an empirical analysis.
