Tootfinder

Very, very useful:
https://abyssdomain.expert/@filippo/114496179105976467

"Donald Trump says Elon Musk has ‘lost his mind’ and dismisses peace offering
Trump says he is ‘not particularly’ interested in reconciling with Musk, who reportedly wanted to speak to president"
cue the SNL skit

Didn't we just have a war celebration last year, and now we're having another one? Cue gammon-Brenda...

Weekend #Plankton Factoid 🦠🦐
Light is an extremely important factor in the oceans. It governs not only photosynthesis, but is also an important cue for vertically migrating zooplankton and needed for visual predation. The finding that 20% of the #oceans, especially at vital polar regions, are incre…

Cue Stock Bat Footage
#Monsterdon

🇺🇦 #NowPlaying on #KEXP's #Early
Yellow Magic Orchestra:
🎵 Cue
#YellowMagicOrchestra
https://perpetualdoom.bandcamp.com/track/cue-yellow-magic-orchestra
https://open.spotify.com/track/15beQw4bH4fePS8oAE2Yef
🎶 show playlist 👇
https://open.spotify.com/playlist/5F6PDmIbE0oCzbwTklfrLZ
🎶 KEXP playlist 👇
https://open.spotify.com/playlist/6VNALrOa3gWbk794YuIrwg

Discounting and Drug Seeking in Biological Hierarchical Reinforcement Learning
Vardhan Palod, Pranav Mahajan, Veeky Baths, Boris S. Gutkin
https://arxiv.org/abs/2506.04549

Discounting and Drug Seeking in Biological Hierarchical Reinforcement Learning
Despite a strong desire to quit, individuals with long-term substance use disorder (SUD) often struggle to resist drug use, even when aware of its harmful consequences. This disconnect between knowledge and compulsive behavior reflects a fundamental cognitive-behavioral conflict in addiction. Neurobiologically, differential cue-induced activity within striatal subregions, along with dopamine-mediated connectivity from the ventral to the dorsal striatum, contributes to compulsive drug-seeking. H…

This https://arxiv.org/abs/2505.13688 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Gaze-Enhanced Multimodal Turn-Taking Prediction in Triadic Conversations
Turn-taking prediction is crucial for seamless interactions. This study introduces a novel, lightweight framework for accurate turn-taking prediction in triadic conversations without relying on computationally intensive methods. Unlike prior approaches that either disregard gaze or treat it as a passive signal, our model integrates gaze with speaker localization, structuring it within a spatial constraint to transform it into a reliable predictive cue. Leveraging egocentric behavioral cues, our…

This https://arxiv.org/abs/2505.19314 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

SoloSpeech: Enhancing Intelligibility and Quality in Target Speech Extraction through a Cascaded Generative Pipeline
Target Speech Extraction (TSE) aims to isolate a target speaker's voice from a mixture of multiple speakers by leveraging speaker-specific cues, typically provided as auxiliary audio (a.k.a. cue audio). Although recent advancements in TSE have primarily employed discriminative models that offer high perceptual quality, these models often introduce unwanted artifacts, reduce naturalness, and are sensitive to discrepancies between training and testing environments. On the other hand, generative m…

Online Audio-Visual Autoregressive Speaker Extraction
Zexu Pan, Wupeng Wang, Shengkui Zhao, Chong Zhang, Kun Zhou, Yukun Ma, Bin Ma
https://arxiv.org/abs/2506.01270

Online Audio-Visual Autoregressive Speaker Extraction
This paper proposes a novel online audio-visual speaker extraction model. In the streaming regime, most studies optimize the audio network only, leaving the visual frontend less explored. We first propose a lightweight visual frontend based on depth-wise separable convolution. Then, we propose a lightweight autoregressive acoustic encoder to serve as the second cue, to actively explore the information in the separated speech signal from past steps. Scenario-wise, for the first time, we study ho…