1 Image, 2*2 Stitching

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

No dataset record in the archive lists this task.

Subtasks archive 2025-07-28

2 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

6 shown of 6 papers with code (8 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Visual Instruction Tuning
  17 Apr 2023 13 repositories listed Syntology ran 16 of 51 samples · 35 unverified
  Instruction tuning large language models (LLMs) using machine-generated instruction-following data has improved zero-shot capabilities on new tasks, but the idea is less explored in the multimodal field.
• CogVLM: Visual Expert for Pretrained Language Models
  6 Nov 2023 4 repositories listed
  We introduce CogVLM, a powerful open-source visual language foundation model.
• InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
  11 May 2023 4 repositories listed
  Large-scale pre-training and instruction tuning have been successful at creating general-purpose language models with broad competence.
• mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration
  7 Nov 2023 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  Multi-modal Large Language Models (MLLMs) have demonstrated impressive instruction abilities across various open-ended tasks.
• Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
  8 Mar 2024 1 repository listed
  In this report, we introduce the Gemini 1.
• Gemini: A Family of Highly Capable Multimodal Models
  19 Dec 2023 1 repository listed
  This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.