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4,009 papers
To the authors' knowledge this is the first description-based, open-vocabulary sign lookup from continuous signing without gloss supervision, and the first for JSL.
Results show that execution alone is insufficient to characterize realistic CAD modeling and that frontier models and agents differ substantially across executability, IoUs, and visual-semantic identity.
KnowVis is proposed, a framework that transforms linear video lectures into pedagogically grounded visual narratives, and generates more accurate and clear visuals that successfully reduce cognitive load and significantly improve student learning effectiveness and knowledge retention.
A benchmark score credits final answers, but not the route by which an item can be answered. In medical multimodal multiple-choice questions (MCQs), this distinction matters because a correct answer can be supported by the intended image finding or by benchmark-preserved cues in the wording of answers, non-visual clini...
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This work proposes a new intrinsic reward for learning tool use in MLLMs without the need for additional labels or warm-start SFT, and finds that recall is the metric that most strongly correlates the zoom-in region with final task performance.
Jina-OCR-v1 is presented, an end-to-end document parsing model built to serve on low-budget GPUs that combines the compressed-vision encoder and the 3B mixture-of-experts decoder of DeepSeek-OCR with a FastMTP speculative decoding head that shares a single draft block recursively across K=3 prediction steps.
HCS is introduced, a compact framework for AI-generated image detection that converts intermediate CNN activations into a structured 60-dimensional representation organized across three progressively deeper backbone stages that achieves 86.7% accuracy and 86.7% macro-F1 on the held-out test set.
This work proposes to model each neuron's activation as the steady-state response of a sinusoidally-forced damped harmonic oscillator, whose amplitude naturally governs the network's spectral selectivity during training, and achieves state-of-the-art or competitive results against established INRs, while requiring no t...
It is shown that synthetic data improves a real-data baseline when used as near-zero-human-annotation-cost augmentation alongside real anchors, while synthetic-only training remains substantially below real-only performance, highlighting the practical value of data-centric orchestration for low-data augmentation.
Heterogeneous memory and diversity-aware replay provide an effective basis for continual aerial VPR in mapped operating areas and introduce DBS-Hybrid, which combines prototype-based diversity trimming with representative-first feature-space coverage.
Cumulative Sample Loss (CSL) is computed as the mean annotation-conditioned loss of an audit frame across checkpoints trained on a *disjoint* reference set and acts as a dynamic fingerprint and captures the persistent disagreement between its annotation and learned visual-temporal structure.
A deep ensemble of the two co-first-place 2025 models is formed and a lightweight residual refiner trained on the ensemble's own outputs under an $\ell_1$ loss augmented with a structural-similarity term whose weight $\lambda$ the authors vary, which improves an already strong ensemble without any large-scale retrainin...
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
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.
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