DeepResearch might ignore or underutilize an image or PDF in a query due to technical limitations in processing unstructured data formats. While text-based inputs are straightforward to parse, images and PDFs require additional steps like optical character recognition (OCR) or layout analysis to extract meaningful information. For example, a scanned PDF with low resolution or handwritten text might fail OCR processing, leaving the system unable to interpret the content. Similarly, complex diagrams or charts in images may lack machine-readable labels or metadata, making their context unclear. If the system isn’t explicitly designed to handle these formats, it might default to prioritizing text-based inputs or skip the file altogether.
Another reason is content relevance or ambiguity. DeepResearch might prioritize parts of your query that are explicitly stated in plain text, especially if the image or PDF isn’t clearly referenced or its purpose isn’t obvious. For instance, if you attach a research paper PDF but don’t specify which sections or figures to focus on, the system might struggle to identify key points amid dense content. Similarly, an image with no caption or contextual explanation (e.g., a graph without axis labels) could be dismissed as uninterpretable. The system’s algorithms might also weigh text inputs more heavily due to training data biases, favoring language patterns over visual or document-based analysis.
Finally, resource constraints or configuration settings could limit processing. Analyzing large PDFs or high-resolution images demands significant computational power and memory. To maintain responsiveness, DeepResearch might truncate processing for files exceeding size limits or time thresholds. For example, a 50-page PDF might only have the first 10 pages analyzed, or an image might be downsampled, losing critical details. Users can mitigate this by preprocessing files (e.g., extracting text from PDFs, simplifying images) and explicitly directing the system to specific sections. Without such guidance, the tool may prioritize efficiency over thoroughness, leading to incomplete utilization of provided materials.