Tootfinder

Sources: WBD initiates a round of layoffs in its cable TV divisions, affecting well under 100 employees and largely impacting the Discovery side of the company (Peter White/Deadline)
https://deadline.com/2025/06/warner-bros-discovery-layoffs-tv-d…

Warner Bros. Discovery Initiates More Layoffs In Cable TV Divisions
Deadline understands that the company is set to layoff a number of people, particularly on the cable television side of its business.

Worst-to-first rankings: Which teams could skyrocket to the top of their divisions? https://www.espn.com/nfl/story/_/id/45391110/2025-nfl-season-worst-first-division-odds-predictions

Updating my CloudNativePG Clusters to postgresql:17.5 broke wal archiving to my Ceph S3 Object Store. Here's a new blog post describing the fix:
https://www.beyondwatts.com/posts/debugging-barman-xamzcontents…

beyondwatts | Debugging Barman XAmzContentSHA256Mismatch error after upgrading to postgresql:17.5
In an effort to keep my home cluster up to date, I upgraded CloudNativePG to v1.26 and the associated database clusters to cloudnative-pg/postgresql:17.5. All seemed ok with the upgrade until a couple of days later when the cluster primary instance PVCs started to run out of space. wal archiving had stopped working with the error message:

From One AFC West Club To Another: The Division Of RBs Stays Strong https://raiderramble.com/2025/06/04/from-one-afc-west-club-to-another-division-of-rbs/

IllumiCraft: Unified Geometry and Illumination Diffusion for Controllable Video Generation
Yuanze Lin, Yi-Wen Chen, Yi-Hsuan Tsai, Ronald Clark, Ming-Hsuan Yang
https://arxiv.org/abs/2506.03150

IllumiCraft: Unified Geometry and Illumination Diffusion for Controllable Video Generation
Although diffusion-based models can generate high-quality and high-resolution video sequences from textual or image inputs, they lack explicit integration of geometric cues when controlling scene lighting and visual appearance across frames. To address this limitation, we propose IllumiCraft, an end-to-end diffusion framework accepting three complementary inputs: (1) high-dynamic-range (HDR) video maps for detailed lighting control; (2) synthetically relit frames with randomized illumination ch…

This https://arxiv.org/abs/2505.16933 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning
In this work, we introduce LLaDA-V, a purely diffusion-based Multimodal Large Language Model (MLLM) that integrates visual instruction tuning with masked diffusion models, representing a departure from the autoregressive paradigms dominant in current multimodal approaches. Built upon LLaDA, a representative large language diffusion model, LLaDA-V incorporates a vision encoder and MLP connector that projects visual features into the language embedding space, enabling effective multimodal alignme…

🇺🇦 #NowPlaying on KEXP's #MorningShow
Joy Division:
🎵 Disorder
#JoyDivision
https://josephleeharris.bandcamp.com/track/joy-division-disorder
https://open.spotify.com/track/2WEw8oFZiANQzWdGElO3Mf

Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement
Mostafa Sadeghi (MULTISPEECH), Jean-Eudes Ayilo (MULTISPEECH), Romain Serizel (MULTISPEECH), Xavier Alameda-Pineda (ROBOTLEARN)
https://arxiv.org/abs/2507.02391

Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement
We explore unsupervised speech enhancement using diffusion models as expressive generative priors for clean speech. Existing approaches guide the reverse diffusion process using noisy speech through an approximate, noise-perturbed likelihood score, combined with the unconditional score via a trade-off hyperparameter. In this work, we propose two alternative algorithms that directly model the conditional reverse transition distribution of diffusion states. The first method integrates the diffusi…

This https://arxiv.org/abs/2412.03293 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Diffusion-VLA: Generalizable and Interpretable Robot Foundation Model via Self-Generated Reasoning
In this paper, we present DiffusionVLA, a novel framework that seamlessly combines the autoregression model with the diffusion model for learning visuomotor policy. Central to our approach is a next-token prediction objective, enabling the model to reason effectively over the user's query in the context of current observations. Subsequently, a diffusion model is attached to generate robust action outputs. To enhance policy learning through self-reasoning, we introduce a novel reasoning injectio…

Poster: libdebug, Build Your Own Debugger for a Better (Hello) World
Gabriele Digregorio, Roberto Alessandro Bertolini, Francesco Panebianco, Mario Polino
https://arxiv.org/abs/2506.02667

Poster: libdebug, Build Your Own Debugger for a Better (Hello) World
Automated debugging, long pursued in a variety of fields from software engineering to cybersecurity, requires a framework that offers the building blocks for a programmable debugging workflow. However, existing debuggers are primarily tailored for human interaction, and those designed for programmatic debugging focus on kernel space, resulting in limited functionality in userland. To fill this gap, we introduce libdebug, a Python library for programmatic debugging of userland binary executables…