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3,462 papers
Middle-layer Attention Prediction (MAP), which uses Question Contrastive Teacher Selection to identify a sample-specific teacher layer by contrasting attention under the original and reference questions, and distills attention from the selected layer into a lightweight predictor that estimates visual token importance f...
It is suggested that while they may be able to approximate rank-orderings of human attractiveness, current off-the-shelf commercial MLLMs systematically overrate the beauty of human faces.
This work introduces VTOS (Vision Tools Orchestration Search), a framework for adaptive visual tool orchestration through joint solution-observer search that outperforms static tool pipelines and agentic visual-programming baselines in complex settings such as dense, occluded scenes and out-of-distribution segmentation...
A controlled diagnostic framework with two synthetic tasks that disentangle perception from reasoning reveals a consistent perception-reasoning asymmetry: post-training improves reasoning more substantially than perception, though the underlying mechanism differs across training paradigms.
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SignBind-LLM, a modular framework that addresses limitations of sign language translation systems through three dedicated expert streams: one for continuous signing, one for fingerspelling, and one for lipreading, confirms that the gains are architectural rather than a consequence of scaling the language model.
ShallowStream is a novel framework that leverages the shallow layers of an MLLM to simultaneously perform frame encoding and retrieval index building and achieves performance on par with the strongest existing streaming methods, while reducing per-frame prefill latency and 10-second end-to-end latency by up to 52.1x an...
LeakageBench provides a diagnostic benchmark for high-recall, spatially grounded PII redaction in document images and shows that stronger detection and tool assistance improve localization without making most pages safe for release.
This synthesis shows that the open frontier of reasoning in driving agents lies in intermediate representations that can be grounded in the real world, coupled to real-time action, and verified under safety-critical systems.
This work introduces MemeCULT-1K, a multilingual benchmark of 1,000 South Asian memes in Bengali, English, and Hindi, where each meme is paired with a cultural context note and three human-written explanations, along with a supplementary set of 54 Bengali regional dialect memes.
CAFNet is presented, a lightweight cross-attentive architecture that fuses MFCC, LFCC, and Chroma-STFT features to jointly classify audio as real, fully fake, or half-truth, and regress the temporal boundaries of the synthesised region, at approximately 14 ms CPU latency.
This work proposes Conditional Diffusion Posterior Alignment (CDPA) to enable scalable 3D sparse-view CT reconstruction to large 3D volumes by combining conditional diffusion with explicit data consistency, and shows that the same principles also strengthen fast denoising U-Nets, yielding near-diffusion quality at a fr...
DynaTokens, a transformer-based token generator that dynamically produces fine-tuning tokens on demand, enabling task-adaptive prompt updates through shared generation weights is introduced, enabling task-adaptive prompt updates through shared generation weights.
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
A Blog post by H company on Hugging Face
A Blog post by Liquid AI on Hugging Face
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
Human-Computer Interaction and Visualization
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