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TopoBench: Benchmarking LLMs on Hard Topological Reasoning
Mayug Maniparambil, Nils Hoehing, Janak Kapuriya +5
Solving topological grid puzzles requires reasoning over global spatial invariants such as connectivity, loop closure, and region symmetry and remains challenging for even the most…
Underrepresented in Foundation Model Pretraining Data? A One-Shot Probe
Chris Vorster, Mayug Maniparambil, Noel E. O'Connor +2
Large-scale Vision-Language Foundation Models (VLFMs), such as CLIP, now underpin a wide range of computer vision research and applications. VLFMs are often adapted to various doma…
Hold-One-Shot-Out (HOSO) for Validation-Free Few-Shot CLIP Adapters
Chris Vorster, Mayug Maniparambil, Noel E. O'Connor +2
In many CLIP adaptation methods, a blending ratio hyperparameter controls the trade-off between general pretrained CLIP knowledge and the limited, dataset-specific supervision from…