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16,516 papers
Weak supervision sets a practical regime for audio-visual sound source localization as dense spatial annotations are costly to obtain at scale. The task, however, remains challenging, as models must locate sound sources from temporally aligned audio-visual data without pixel-level supervision. Recent large-scale audio-...
LOCKS stores a rank-$r$ spectral summary per page, reconstructs its within-page logits, and selects pages by log-sum-exp mass without reading candidate keys or values, and retains quality furthest under tight budgets on AIME26 and MATH-500.
Conversational AI can improve access to public health information, but public-facing healthcare applications require safeguards against inappropriate medical guidance and unsupported generation. We present a Safety-First Science Gateway for maternal and child health (MCH) resource navigation that combines large languag...
The results indicate that any immediate effects on opinions of AI are modest, although they leave open the possibility that anthropomorphic language could have an effect in naturalistic settings, or over gradual, continued exposure.
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Inspired by Kolmogorov-Arnold networks, trainable nonlinear functions are placed on the connections, making each physical connection a learnable computational element in physical neural networks.
It is found that agents are less effective at resolving tasks when building on agent code compared to human code, with task resolve rate drops of up to 13.1%.
Temporal Self-Imitation Learning (TSIL), a reinforcement learning framework that mines temporally efficient successful trajectories generated during learning and converts them into reusable supervision for future policy improvement, is introduced.
Skill-MAS is proposed, a novel third path that decouples experience retention from parametric updates by conceptualizing the high-level orchestration capability as an evolvable Meta-Skill and is revealed to be highly robust and exhibit strong transferability across unseen tasks and different LLMs.
Segment Anything Model 3 (SAM 3) provides a strong frozen backbone for concept-prompted segmentation, but applying it directly to open-vocabulary semantic segmentation (OVSS) is inefficient: full-resolution decoding is typically run over the entire dataset vocabulary, whereas each image contains only a small active sub...
This work proposes UPLOTS, a Unified, Prompt-guided Language model framework that leverages a single pre-trained transformer backbone guided by learned constraint prompts, enabling on-demand generation with precise pattern control in time-series generation.
Under a local Gaussian approximation, the divergence between the fine-tuned posterior and pretrained prior is bound by accumulated Fisher-weighted update costs, motivating curvature-aware selection in parameter groups based on temporal drift in their Fisher information.
Humanoid loco-manipulation benefits from one controller to coordinate locomotion, arm movements, and fall recovery. These behaviors are difficult to learn together from scratch because they require different skills and objectives. We present HANDOFF, a training architecture that distills motion-tracking, locomotion, an...
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.
Machine Intelligence
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