Tootfinder

Here are the email addresses to make your voice heard at Disney/ABC:
👉General Issues: DisneyABCtv_Support@disney.com
👉Publicity / Corporate Comms: Ashley.r.kline@disney.com
👉Audience Information: cheryl.pratesa@abc.com
👉Investor Relations: alexia.quadrani@disney.com
👉Disney Advertising: Disney.Advertising@disney.com
If anyone needs sample language, here’s a starting point you can copy and paste:
Dear Disney/ABC Leadership,
Your decision to silence a comedian for a harmless joke while protecting and platforming voices that openly promote cruelty is indefensible. It reeks of hypocrisy, cowardice, and corporate complicity.
Suppressing humor while elevating propaganda is how fascism gains ground. You are helping it along.
This is a warning: every dollar I once spent on Disney subscriptions, merchandise, films, and parks will now be withheld. I will also be encouraging others to cancel, divest, and pressure your advertisers and shareholders until Disney/ABC adopts clear, viewpoint-neutral standards that respect all voices equally.
History will not remember kindly the corporations that bent to fear and power, silencing dissent while protecting division. Right now, Disney/ABC is on the wrong side of that history. Shame on you. We will remember!
Sincerely,
- From Rob Brezsny on a different Social Media platform
#BoycottDisney #JimmyKImmel #FreedomOfSpeech

RRRA: Resampling and Reranking through a Retriever Adapter
Bongsu Kim
https://arxiv.org/abs/2508.11670 https://arxiv.org/pdf/2508.11670

RRRA: Resampling and Reranking through a Retriever Adapter
In dense retrieval, effective training hinges on selecting high quality hard negatives while avoiding false negatives. Recent methods apply heuristics based on positive document scores to identify hard negatives, improving both performance and interpretability. However, these global, example agnostic strategies often miss instance specific false negatives. To address this, we propose a learnable adapter module that monitors Bi-Encoder representations to estimate the likelihood that a hard negat…

Matrix-Game 2.0: An Open-Source, Real-Time, and Streaming Interactive World Model
Xianglong He, Chunli Peng, Zexiang Liu, Boyang Wang, Yifan Zhang, Qi Cui, Fei Kang, Biao Jiang, Mengyin An, Yangyang Ren, Baixin Xu, Hao-Xiang Guo, Kaixiong Gong, Cyrus Wu, Wei Li, Xuchen Song, Yang Liu, Eric Li, Yahui Zhou
https://arxiv.org/abs/2508.13009

Matrix-Game 2.0: An Open-Source, Real-Time, and Streaming Interactive World Model
Recent advances in interactive video generations have demonstrated diffusion model's potential as world models by capturing complex physical dynamics and interactive behaviors. However, existing interactive world models depend on bidirectional attention and lengthy inference steps, severely limiting real-time performance. Consequently, they are hard to simulate real-world dynamics, where outcomes must update instantaneously based on historical context and current actions. To address this, we pr…

e-boost: Boosted E-Graph Extraction with Adaptive Heuristics and Exact Solving
Jiaqi Yin, Zhan Song, Chen Chen, Yaohui Cai, Zhiru Zhang, Cunxi Yu
https://arxiv.org/abs/2508.13020

e-boost: Boosted E-Graph Extraction with Adaptive Heuristics and Exact Solving
E-graphs have attracted growing interest in many fields, particularly in logic synthesis and formal verification. E-graph extraction is a challenging NP-hard combinatorial optimization problem. It requires identifying optimal terms from exponentially many equivalent expressions, serving as the primary performance bottleneck in e-graph based optimization tasks. However, traditional extraction methods face a critical trade-off: heuristic approaches offer speed but sacrifice optimality, while exac…

Estimates for Schr\"{o}dinger Groups and Imaginary Power Operators on Weak Hardy Spaces Associated with Non-negative Self-adjoint Operators and Ball Quasi-Banach Function Spaces
Xiong Liu, Wenhua Wang
https://arxiv.org/abs/2508.13913

Estimates for Schrödinger Groups and Imaginary Power Operators on Weak Hardy Spaces Associated with Non-negative Self-adjoint Operators and Ball Quasi-Banach Function Spaces
Let $(\mathbb{X},d,μ)$ be a doubling metric measure space, $L$ a non-negative self-adjoint operator on $L^2(\mathbb{X})$ satisfying the Davies-Gaffney estimate, and $X(\mathbb{X})$ a ball quasi-Banach function space on $\mathbb{X}$ satisfying some mild assumptions with $p\in(0,\infty)$ and $s_0\in(0,\min\{p,1\}]$. In this article, the authors first study the weak Hardy space $WH_{X,L}(\mathbb{X})$ associated with $L$ and $X(\mathbb{X})$, and then establish the atomic and molecular decompositio…

Hierarchical Planning and Scheduling for Reconfigurable Multi-Robot Disassembly Systems under Structural Constraints
Takuya Kiyokawa, Tomoki Ishikura, Shingo Hamada, Genichiro Matsuda, Kensuke Harada
https://arxiv.org/abs/2509.14564

Hierarchical Planning and Scheduling for Reconfigurable Multi-Robot Disassembly Systems under Structural Constraints
This study presents a system integration approach for planning schedules, sequences, tasks, and motions for reconfigurable robots to automatically disassemble constrained structures in a non-destructive manner. Such systems must adapt their configuration and coordination to the target structure, but the large and complex search space makes them prone to local optima. To address this, we integrate multiple robot arms equipped with different types of tools, together with a rotary stage, into a re…

#Spearhead's #MichaelFranti played a concert last night at #SDSU as online rumblings grew about allegations from a female artist casting some unusually dark shadows over the positive vibes associated with ex-

Estimates for pseudo-differential operators on the torus revisited. III
Duv\'an Cardona, Manuel Mart\'inez
https://arxiv.org/abs/2508.13338 https://

Estimates for pseudo-differential operators on the torus revisited. III
This paper finishes the goal of the authors started in two previous manuscripts dedicated to revisiting the continuity properties of toroidal pseudo-differential operators with symbols in the Hörmander classes. Here we prove pointwise estimates in terms of the Fefferman-Stein sharp maximal function and of the Hardy-Littlewood maximal function. Combining these estimates with the properties of Muckenhoupt's weight class $A_p$ we obtain boundedness theorems for pseudo-differential operators betwe…

QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation
Jiazheng Li, Hong Lu, Kaiyue Wen, Zaiwen Yang, Jiaxuan Gao, Hongzhou Lin, Yi Wu, Jingzhao Zhang
https://arxiv.org/abs/2507.13266

QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation
Reinforcement learning (RL) has become a key component in training large language reasoning models (LLMs). However, recent studies questions its effectiveness in improving multi-step reasoning-particularly on hard problems. To address this challenge, we propose a simple yet effective strategy via Question Augmentation: introduce partial solutions during training to reduce problem difficulty and provide more informative learning signals. Our method, QuestA, when applied during RL training on mat…

Scalable Multi-Objective Robot Reinforcement Learning through Gradient Conflict Resolution
Humphrey Munn, Brendan Tidd, Peter B\"ohm, Marcus Gallagher, David Howard
https://arxiv.org/abs/2509.14816

Scalable Multi-Objective Robot Reinforcement Learning through Gradient Conflict Resolution
Reinforcement Learning (RL) robot controllers usually aggregate many task objectives into one scalar reward. While large-scale proximal policy optimisation (PPO) has enabled impressive results such as robust robot locomotion in the real world, many tasks still require careful reward tuning and are brittle to local optima. Tuning cost and sub-optimality grow with the number of objectives, limiting scalability. Modelling reward vectors and their trade-offs can address these issues; however, multi…