Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv:2603.01865v4 Announce Type: replace Abstract: LLM-as-judge evaluation has become standard practice for open-ended model assessment; however, judges exhibit systematic biases that cannot be aver...
arXiv:2605.09252v3 Announce Type: replace Abstract: Tool-augmented LLM agents tend to call tools indiscriminately, even when the model can answer directly. Each unnecessary call wastes API fees and l...
arXiv:2606.18902v3 Announce Type: replace Abstract: Context engineering has emerged as a primary lever for improving AI systems without parameter updates. Recent work showing that textual gradients d...
arXiv:2606.19544v2 Announce Type: replace Abstract: LLM-as-a-Judge has become the dominant evaluation paradigm for language models, but judge validation in practice relies on exact-match agreement, a...
arXiv:2611.05570v1 Announce Type: new Abstract: Remote sensing change detection is typically formulated as Siamese feature comparison, where two images are encoded independently and a decoder determi...
arXiv:2611.05648v1 Announce Type: new Abstract: Adversarial diffusion distillation has conventionally relied on image features for discrimination. We revisit this choice for multimodal diffusion tran...
arXiv:2611.05689v1 Announce Type: new Abstract: Coarse-to-fine stereo matching enables efficient disparity estimation but remains sensitive to errors in propagated disparity, which may place ground-t...
arXiv:2611.05734v1 Announce Type: new Abstract: Owing to the prohibitive cost of manual annotation for enormous medical images, self-supervised learning (SSL) has gained substantial attention and sho...
arXiv:2611.05737v1 Announce Type: new Abstract: Multimodal brain MRI provides complementary anatomical, tissue, and pathological information to support downstream artificial intelligence (AI) applica...
arXiv:2611.05969v1 Announce Type: new Abstract: Single Image Reflection Removal (SIRR) seeks to recover the transmitted scene from a photograph captured through glass. Recent latent restoration metho...
arXiv:2611.06015v1 Announce Type: new Abstract: High-content multi-channel imaging, from Cell Painting assays to remote sensing, is central to modern scientific pipelines. Because these channels are...
arXiv:2611.06020v1 Announce Type: new Abstract: A 3D Gaussian Splatting (3DGS) reconstruction inherits arbitrary units from structure-from-motion, so it cannot be measured or used to place AR content...
arXiv:2611.06042v1 Announce Type: new Abstract: Universal image restoration aims to handle diverse degradations within a single model, but a reliable scaling strategy remains underexplored. Increasin...
arXiv:2611.06047v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have recently been extended to handle multiple input images, but this extension dramatically increases the visual...
arXiv:2611.06070v1 Announce Type: new Abstract: While single-image 3D texture generation has advanced significantly, conditioning texture synthesis on multi-view reference images remains largely unde...
arXiv:2611.06083v1 Announce Type: new Abstract: Omni models answer questions about videos by jointly processing sampled frames and audio in one turn, with progress driven largely by scaling model siz...
arXiv:2611.06089v1 Announce Type: new Abstract: In this study, we focus on service robots that retrieve and transport everyday objects based on free-form instructions that may refer to visual feature...
arXiv:2611.06105v1 Announce Type: new Abstract: Self-supervised pre-training on synthetic aperture radar (SAR) imagery enables transferable representations, but the optical-SAR domain gap and speckle...
arXiv:2611.06141v1 Announce Type: new Abstract: High-fidelity 3D geometry generation requires maintaining global structural coherence alongside fine-grained surface details. While recent coarse-to-fi...
arXiv:2611.06160v1 Announce Type: new Abstract: Existing reasoning segmentation frameworks typically employ multimodal large language models (MLLMs) with broad world knowledge to extract semantics in...