71 citations · 237 across the 19 of their papers we have counts for
19 papers
Neuro-Symbolic Contrastive Learning for Cross-domain Inference
Mingyue Liu, Ryo Ueda, Zhen Wan +2
Pre-trained language models (PLMs) have made significant advances in natural language inference (NLI) tasks, however their sensitivity to textual perturbations and dependence on la…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1167
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
Repeat and Concatenate: 2D to 3D Image Translation with 3D to 3D Generative Modeling
Abril Corona-Figueroa, Hubert P. H. Shum, Chris G. Willcocks
This paper investigates a 2D to 3D image translation method with a straightforward technique, enabling correlated 2D X-ray to 3D CT-like reconstruction. We observe that existing ap…
Unaligned 2D to 3D Translation with Conditional Vector-Quantized Code Diffusion using Transformers
Abril Corona-Figueroa, Sam Bond-Taylor, Neelanjan Bhowmik +4
Generating 3D images of complex objects conditionally from a few 2D views is a difficult synthesis problem, compounded by issues such as domain gap and geometric misalignment. For…
-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
Sam Bond-Taylor, Chris G. Willcocks
This paper introduces -Diff, a generative diffusion model defined in an infinite-dimensional Hilbert space, which can model infinite resolution data. By training on randoml…
Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields
Brian K. S. Isaac-Medina, Chris G. Willcocks, Toby P. Breckon
Neural Radiance Fields (NeRF) have attracted significant attention due to their ability to synthesize novel scene views with great accuracy. However, inherent to their underlying f…