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3,315 papers
This paper presents a novel sparsity-driven continual learning framework that operates in two stages: it first identifies a sparse, task-critical parameter mask via a sparsity-inducing objective, then performs mask-constrained fine-tuning by only optimizing parameters selected by the mask.
Noise2Noise (N2N) trains denoisers on pairs of independently corrupted observations, eliminating clean references. We stress-test two natural conjectures about why the L1 loss outperforms L2 here. First, the hypothesis that the L1 loss confers robustness via parameter sparsity confuses the loss with Lasso regularizatio...
OPD-Aha is introduced, which reconstructs the distillation target directly from this isolated visual preference rather than relying on the fragile teacher-student discrepancy, yielding broad and consistent improvements across diverse fine-grained perception and complex multimodal reasoning benchmarks.
We present an efficient method to distill reasoning capabilities into compact video-language models (VLMs) for video question answering (VideoQA). Our approach fine-tunes a 2B-parameter model using only $\sim$900 uncertainty-selected examples, each augmented with synthetic chain-of-thought (CoT) rationales generated by...
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PaintCopilot lets AI autonomously act on an artwork whose direction is still open, through interruptible, revisable delegation mechanisms spanning individual strokes, extended sequences, bounded regions, and prior stroke history.
MedVA is presented, an end-to-end neuro-symbolic agentic system for medical volume visualization that addresses limitations through three complementary agents and provides more complete, clinically grounded ROI specifications than MLLM-only reasoning.
Most knowledge of graphical perception comes from behavioral studies. Understanding from a neural perspective is much more limited due in part to neuroimaging studies'expensiveness and difficulty to conduct. In this paper, we evaluate whether Meta's Tribe V2 neural encoding model can recover neural contrasts from a vis...
Congruency Score (CS), a lightweight calibration layer that maps image--text similarity evidence into a bounded score, is proposed, establishing long-text image--text congruence scoring as a calibrated score-estimation problem, where retrieval performance, human association, and threshold calibration must be evaluated...
MarKey is a training-free framework that formulates keyframe selection as subset-aware greedy optimization and consistently outperforms existing methods on six benchmarks spanning holistic video understanding, human-centric video understanding, and open-ended video understanding.
This work proposes a language-guided distillation framework for learning sensor-robust tactile representations and demonstrates that language-guided distillation enables scalable and hardware-agnostic tactile representation learning.
The results indicate that structured temporal representations can support both performance and inspectability by preserving symbolic structure, capturing temporal continuity, and providing human-readable diagnostics for video reasoning.
Reimplementation of the challenge evaluator shows that its BLEU-4 and METEOR are local variants whose F-mean weights recall nine to one, that two clinicians agree on 47 percent of findings for the same patient, and that a constant report consequently outscores a genuine second clinician report by 0.165 captioning.
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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