Tootfinder

Mistral adds new features to its Le Chat chatbot, including a new "deep research" mode, native multilingual reasoning, and advanced image editing (Rebecca Bellan/TechCrunch)
https://techcrunch.com/2025/07/17/mistrals-…

Mistral's Le Chat chatbot gets a productivity push with new ‘deep research' mode | TechCrunch
French AI lab Mistral introduced a range of new features to its Le Chat chatbot on Thursday that bring it closer to the capabilities of rivals like OpenAI and Google. The new update includes a new “deep research” mode, native multilingual reasoning, and advanced image editing. 

EditGen: Harnessing Cross-Attention Control for Instruction-Based Auto-Regressive Audio Editing
Vassilis Sioros, Alexandros Potamianos, Giorgos Paraskevopoulos
https://arxiv.org/abs/2507.11096

EditGen: Harnessing Cross-Attention Control for Instruction-Based Auto-Regressive Audio Editing
In this study, we investigate leveraging cross-attention control for efficient audio editing within auto-regressive models. Inspired by image editing methodologies, we develop a Prompt-to-Prompt-like approach that guides edits through cross and self-attention mechanisms. Integrating a diffusion-based strategy, influenced by Auffusion, we extend the model's functionality to support refinement edits, establishing a baseline for prompt-guided audio editing. Additionally, we introduce an alternativ…

Some non-citizen journalists working in the US are self-censoring, wiping their social media accounts, canceling travel plans, and more, fearing deportation (Angela Fu/Poynter)
https://www.poynter.org/reporting-editing/…

Foreign journalists in the U.S. are self-censoring to protect themselves from the Trump administration - Poynter
Non-citizen journalists working in the U.S. report wiping their social media accounts, canceling travel plans and pulling bylines.

HPR3D: Hierarchical Proxy Representation for High-Fidelity 3D Reconstruction and Controllable Editing
Tielong Wang, Yuxuan Xiong, Jinfan Liu, Zhifan Zhang, Ye Chen, Yue Shi, Bingbing Ni
https://arxiv.org/abs/2507.11971

HPR3D: Hierarchical Proxy Representation for High-Fidelity 3D Reconstruction and Controllable Editing
Current 3D representations like meshes, voxels, point clouds, and NeRF-based neural implicit fields exhibit significant limitations: they are often task-specific, lacking universal applicability across reconstruction, generation, editing, and driving. While meshes offer high precision, their dense vertex data complicates editing; NeRFs deliver excellent rendering but suffer from structural ambiguity, hindering animation and manipulation; all representations inherently struggle with the trade-of…

HUG-VAS: A Hierarchical NURBS-Based Generative Model for Aortic Geometry Synthesis and Controllable Editing
Pan Du, Mingqi Xu, Xiaozhi Zhu, Jian-xun Wang
https://arxiv.org/abs/2507.11474

HUG-VAS: A Hierarchical NURBS-Based Generative Model for Aortic Geometry Synthesis and Controllable Editing
Accurate characterization of vascular geometry is essential for cardiovascular diagnosis and treatment planning. Traditional statistical shape modeling (SSM) methods rely on linear assumptions, limiting their expressivity and scalability to complex topologies such as multi-branch vascular structures. We introduce HUG-VAS, a Hierarchical NURBS Generative model for Vascular geometry Synthesis, which integrates NURBS surface parameterization with diffusion-based generative modeling to synthesize r…

Instance-Specific Test-Time Training for Speech Editing in the Wild
Taewoo Kim, Uijong Lee, Hayoung Park, Choongsang Cho, Nam In Park, Young Han Lee
https://arxiv.org/abs/2506.13295

Instance-Specific Test-Time Training for Speech Editing in the Wild
Speech editing systems aim to naturally modify speech content while preserving acoustic consistency and speaker identity. However, previous studies often struggle to adapt to unseen and diverse acoustic conditions, resulting in degraded editing performance in real-world scenarios. To address this, we propose an instance-specific test-time training method for speech editing in the wild. Our approach employs direct supervision from ground-truth acoustic features in unedited regions, and indirect …

I don’t know you guys. Trump might be on to something here.

Ok, #Obsidian bases just caught me: bulk editing frontmatter across files in a table. So blazing fast...

To add a single example here (feel free to chime in with your own):
Problem: editing code is sometimes tedious because external APIs require boilerplate.
Solutions:
- Use LLM-generated code. Downsides: energy use, code theft, potential for legal liability, makes mistakes, etc. Upsides: popular among some peers, seems easy to use.
- Pick a better library (not always possible).
- Build internal functions to centralize boilerplate code, then use those (benefits: you get a better understanding of the external API, and a more-unit-testable internal code surface; probably less amortized effort).
- Develop a non-LLM system that actually reasons about code at something like the formal semantics level and suggests boilerplate fill-ins based on rules, while foregrounding which rules it's applying so you can see the logic behind the suggestions (needs research).
Obviously LLM use in coding goes beyond this single issue, but there are similar analyses for each potential use of LLMs in coding. I'm all cases there are:
1. Existing practical solutions that require more effort (or in many cases just seem to but are less-effort when amortized).
2. Near-term researchable solutions that directly address the problem and which would be much more desirable in the long term.
Thus in addition to disastrous LLM effects on the climate, on data laborers, and on the digital commons, they tend to suck us into cheap-seeming but ultimately costly design practices while also crowding out better long-term solutions. Next time someone suggests how useful LLMs are for some task, try asking yourself (or them) what an ideal solution for that task would look like, and whether LLM use moves us closer to or father from a world in which that solution exists.

Foreign journalists in the U.S. are self-censoring to protect themselves from the Trump administration (Angela Fu/Poynter)
https://www.poynter.org/reporting-editing/2025/foreign-journalists-in-the-u-s-are-self-censoring-to-protect-themselves-from-the-trump-administration/
http://www.memeorandum.com/250714/p144#a250714p144

ChainEdit: Propagating Ripple Effects in LLM Knowledge Editing through Logical Rule-Guided Chains
Zilu Dong, Xiangqing Shen, Zinong Yang, Rui Xia
https://arxiv.org/abs/2507.08427 …

ChainEdit: Propagating Ripple Effects in LLM Knowledge Editing through Logical Rule-Guided Chains
Current knowledge editing methods for large language models (LLMs) struggle to maintain logical consistency when propagating ripple effects to associated facts. We propose ChainEdit, a framework that synergizes knowledge graph-derived logical rules with LLM logical reasoning capabilities to enable systematic chain updates. By automatically extracting logical patterns from structured knowledge bases and aligning them with LLMs' internal logics, ChainEdit dynamically generates and edits logically…

Meta adds AI video editing tools to the Edits app and Meta AI, letting users edit up to 10 seconds of a video with 50 preset prompts, free for a "limited time" (Emma Roth/The Verge)
https://www.theverge.com/news/685581/meta-video-editing-ai-pre…

Meta’s new AI video tool can put you in a desert (or at least try to)
Meta is rolling out new AI video editing tools that lets you change the theme of your video, change the background, or even transform what you’re wearing.

For me I use both type of laptops. The windows machine (soon going to #linux) and my #linux laptop (retiring after I convert the windows laptop) I use for serious photo editing, condo newsletters, some work related programming, personal items (like medical).
The Chromebook I use for light…

Here's an attempt at making a somewhat artistic photo of a mundane object by making it black and white and upping the contrast and only using the phone's built-in editing tools. #photography #BlackAndWhite

Private Memorization Editing: Turning Memorization into a Defense to Strengthen Data Privacy in Large Language Models
Elena Sofia Ruzzetti, Giancarlo A. Xompero, Davide Venditti, Fabio Massimo Zanzotto
https://arxiv.org/abs/2506.10024

Private Memorization Editing: Turning Memorization into a Defense to Strengthen Data Privacy in Large Language Models
Large Language Models (LLMs) memorize, and thus, among huge amounts of uncontrolled data, may memorize Personally Identifiable Information (PII), which should not be stored and, consequently, not leaked. In this paper, we introduce Private Memorization Editing (PME), an approach for preventing private data leakage that turns an apparent limitation, that is, the LLMs' memorization ability, into a powerful privacy defense strategy. While attacks against LLMs have been performed exploiting previou…

For my next trick, I will make this bunny disappear. 🪄⁠🐰

There is lots of talk that using correct punctuation like “curly quotes”—or em-dashes—in – as it looks for me – US book style is a hint for AI-generated text. As LLMs basically are statistical parrots with some syntax engine that are based on vector similarity on their training data I suppose this means AI were predominantly trained on books (and maybe newspaper articles) with proper copy-editing.
This also means all the biases and the racism etc comes from this properly edited books t…

Adobe releases iOS and Android apps for Firefly, letting users generate images and videos using text prompts and experiment with popular AI photo editing tools (Jess Weatherbed/The Verge)
https://www.theverge.com/news/688080/adobe-firefly-…

Adobe made a mobile app for its Firefly generative AI tools
The all-in-one platform for Adobe’s Firefly generative AI models is now available on iPhone and Android devices.

Masquerade: Learning from In-the-wild Human Videos using Data-Editing
Marion Lepert, Jiaying Fang, Jeannette Bohg
https://arxiv.org/abs/2508.09976 https://…

Masquerade: Learning from In-the-wild Human Videos using Data-Editing
Robot manipulation research still suffers from significant data scarcity: even the largest robot datasets are orders of magnitude smaller and less diverse than those that fueled recent breakthroughs in language and vision. We introduce Masquerade, a method that edits in-the-wild egocentric human videos to bridge the visual embodiment gap between humans and robots and then learns a robot policy with these edited videos. Our pipeline turns each human video into robotized demonstrations by (i) est…

Integrating Large Language Models into Text Animation: An Intelligent Editing System with Inline and Chat Interaction
Bao Zhang, Zihan Li, Zhenglei Liu, Huanchen Wang, Yuxin Ma
https://arxiv.org/abs/2506.10762

Integrating Large Language Models into Text Animation: An Intelligent Editing System with Inline and Chat Interaction
Text animation, a foundational element in video creation, enables efficient and cost-effective communication, thriving in advertisements, journalism, and social media. However, traditional animation workflows present significant usability barriers for non-professionals, with intricate operational procedures severely hindering creative productivity. To address this, we propose a Large Language Model (LLM)-aided text animation editing system that enables real-time intent tracking and flexible edi…

Building a Code-Editing #Agent in 400 Lines of #Go Code 🤖
➰
🔧 Complete agent implementation requires only #LLM integration, loop structure & sufficient token allocation
🧵 👇

Another exciting thing I discovered: https://jsoncrack.com/

JSON Crack | Transform your data into interactive graphs
JSON Crack Editor is a tool for visualizing into graphs, analyzing, editing, formatting, querying, transforming and validating JSON, CSV, YAML, XML, and more.

@… well, there are two separate problems here right? One is a scenario in which the textarea is readonly-esque and you want to report the value with line numbers outside of editing. The other is reporting line numbers while a user is editing? I’m not even sure what the latter might look like? e.g. “Your cursor is on line 4, which has the following code:”?

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[3/4]:
- GIE-Bench: Towards Grounded Evaluation for Text-Guided Image Editing
Yusu Qian, Jiasen Lu, Tsu-Jui Fu, Xinze Wang, Chen Chen, Yinfei Yang, Wenze Hu, Zhe Gan

Claude Code, Gemini CLI, and CLI Codex, terminal-based AI tools launched since February, have surprisingly gained ground on AI code editors with traditional UIs (Russell Brandom/TechCrunch)
https://techcrunch.com/2025/07/15/ai-coding-tools-a…

AI coding tools are shifting to a surprising place: the terminal | TechCrunch
For years, code-editing tools like Cursor, Windsurf, and GitHub’s Copilot have been the standard for AI-powered software development. But as agentic AI grows more powerful and vibe-coding takes off, a subtle shift has changed how AI systems are interacting with software. Instead of working on code, they’re increasingly interacting directly with the shell of whatever system they’re installed in. It’s a significant change in how AI-powered software development happens – and despite the …

Next Edit Prediction: Learning to Predict Code Edits from Context and Interaction History
Ruofan Lu, Yintong Huo, Meng Zhang, Yichen Li, Michael R. Lyu
https://arxiv.org/abs/2508.10074

Next Edit Prediction: Learning to Predict Code Edits from Context and Interaction History
The rapid advancement of large language models (LLMs) has led to the widespread adoption of AI-powered coding assistants integrated into a development environment. On one hand, low-latency code completion offers completion suggestions but is fundamentally constrained to the cursor's current position. On the other hand, chat-based editing can perform complex modifications, yet forces developers to stop their work, describe the intent in natural language, which causes a context-switch away from t…

Sorry for messing up your scrolling style, done editing all of my pinned posts!

Multimodal Modeling of CRISPR-Cas12 Activity Using Foundation Models and Chromatin Accessibility Data
Azim Dehghani Amirabad, Yanfei Zhang, Artem Moskalev, Sowmya Rajesh, Tommaso Mansi, Shuwei Li, Mangal Prakash, Rui Liao
https://arxiv.org/abs/2506.11182

Multimodal Modeling of CRISPR-Cas12 Activity Using Foundation Models and Chromatin Accessibility Data
Predicting guide RNA (gRNA) activity is critical for effective CRISPR-Cas12 genome editing but remains challenging due to limited data, variation across protospacer adjacent motifs (PAMs-short sequence requirements for Cas binding), and reliance on large-scale training. We investigate whether pre-trained biological foundation model originally trained on transcriptomic data can improve gRNA activity estimation even without domain-specific pre-training. Using embeddings from existing RNA foundati…

Sure, sex is great, but have you ever tried editing a really great piece of someone else's writing?

Periodical chinafake demo videos should be picking up soon once I get my iPad (main filming editing device) fully repaired! Look forward to that, and keep an eye on my channel! @…

#WritersCoffeeClub
June 13
Do you restrict what you read or watch while working on a WIP? Why or why not?
June 14
Do you take notes for your WIP? How closely do you follow them?
June 15
Have you ever challenged yourself to write without editing? What were the results?
---
No, but I may limit whether I read or watch anything at all at the time. Flow…

FlowDrag: 3D-aware Drag-based Image Editing with Mesh-guided Deformation Vector Flow Fields
Gwanhyeong Koo, Sunjae Yoon, Younghwan Lee, Ji Woo Hong, Chang D. Yoo
https://arxiv.org/abs/2507.08285

FlowDrag: 3D-aware Drag-based Image Editing with Mesh-guided Deformation Vector Flow Fields
Drag-based editing allows precise object manipulation through point-based control, offering user convenience. However, current methods often suffer from a geometric inconsistency problem by focusing exclusively on matching user-defined points, neglecting the broader geometry and leading to artifacts or unstable edits. We propose FlowDrag, which leverages geometric information for more accurate and coherent transformations. Our approach constructs a 3D mesh from the image, using an energy functi…

A look at The Examination, a nonprofit investigative news outlet with ~20 staffers launched in 2023 that focuses on Big Food, tobacco, pollution, and drugs (Sophie Endrud/Poynter)
https://www.poynter.org/reporting-editing/2025/t…

Meet The Examination, a nonprofit watchdog for global health - Poynter
Ben Hallman and his team of almost 20 are taking on four of the biggest global industries, one health investigation at a time

🔄 Agent loop architecture: user input − model inference − tool execution − result feedback − continuous conversation flow
💻 String replacement editing approach works effectively with current #AI models for precise code modifications

InterGSEdit: Interactive 3D Gaussian Splatting Editing with 3D Geometry-Consistent Attention Prior
Minghao Wen, Shengjie Wu, Kangkan Wang, Dong Liang
https://arxiv.org/abs/2507.04961

InterGSEdit: Interactive 3D Gaussian Splatting Editing with 3D Geometry-Consistent Attention Prior
3D Gaussian Splatting based 3D editing has demonstrated impressive performance in recent years. However, the multi-view editing often exhibits significant local inconsistency, especially in areas of non-rigid deformation, which lead to local artifacts, texture blurring, or semantic variations in edited 3D scenes. We also found that the existing editing methods, which rely entirely on text prompts make the editing process a "one-shot deal", making it difficult for users to control the editing de…

The AI editing stuff on this phone is cool but definitely has its limits

A busy morning here. Editing podcast episodes, prepping videos for a new client programme, and getting ready for an afternoon of coaching sessions.
And it's already 25C... 🥵

I'm doing a Wikiversity edit right now over at
en.wikiversity.org/wiki/Editing_Internet_Texts/Persuasive_Language_in_Advertising
just a small spelling mistake...
Will post my edit into this post once it is published!
Edit summary(still not publilshed):
small spelling edit: "of our lives" instead of "of out lives"
This is a minor edit ==> CHECK BOX ✅

Editing Internet Texts/Persuasive Language in Advertising - Wikiversity

Musician Shura on finding something to say
https://thecreativeindependent.com/people/musician-shura-on-finding-something-to-say/?utm_source=flipboard&…

Musician Shura on finding something to say – The Creative Independent
Musician Shura discusses overcoming writer’s block, creating things without simultaneously editing them, and never doing the same thing twice.

SoK: Machine Unlearning for Large Language Models
Jie Ren, Yue Xing, Yingqian Cui, Charu C. Aggarwal, Hui Liu
https://arxiv.org/abs/2506.09227 https://

SoK: Machine Unlearning for Large Language Models
Large language model (LLM) unlearning has become a critical topic in machine learning, aiming to eliminate the influence of specific training data or knowledge without retraining the model from scratch. A variety of techniques have been proposed, including Gradient Ascent, model editing, and re-steering hidden representations. While existing surveys often organize these methods by their technical characteristics, such classifications tend to overlook a more fundamental dimension: the underlying…

Editing Cotton Mather's Biblia Americana (1693-1728): America’s First Bible Commentary and Storehouse of Early Modern Learning https://networks.h-net.org/group/announcements/20121478/editing-cotton-mathers-biblia-am…

This https://arxiv.org/abs/2411.04846 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDS_…

On the Complexity of 2-club Cluster Editing with Vertex Splitting
Editing a graph to obtain a disjoint union of s-clubs is one of the models for correlation clustering, which seeks a partition of the vertex set of a graph so that elements of each resulting set are close enough according to some given criterion. For example, in the case of editing into s-clubs, the criterion is proximity since any pair of vertices (in an s-club) are within a distance of s from each other. In this work we consider the vertex splitting operation, which allows a vertex to belong …

Training-Free Text-Guided Color Editing with Multi-Modal Diffusion Transformer
Zixin Yin, Xili Dai, Ling-Hao Chen, Deyu Zhou, Jianan Wang, Duomin Wang, Gang Yu, Lionel M. Ni, Heung-Yeung Shum
https://arxiv.org/abs/2508.09131

Training-Free Text-Guided Color Editing with Multi-Modal Diffusion Transformer
Text-guided color editing in images and videos is a fundamental yet unsolved problem, requiring fine-grained manipulation of color attributes, including albedo, light source color, and ambient lighting, while preserving physical consistency in geometry, material properties, and light-matter interactions. Existing training-free methods offer broad applicability across editing tasks but struggle with precise color control and often introduce visual inconsistency in both edited and non-edited regi…

A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation
Shuting He, Peilin Ji, Yitong Yang, Changshuo Wang, Jiayi Ji, Yinglin Wang, Henghui Ding
https://arxiv.org/abs/2508.09977

A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation
3D Gaussian Splatting (3DGS) has recently emerged as a powerful alternative to Neural Radiance Fields (NeRF) for 3D scene representation, offering high-fidelity photorealistic rendering with real-time performance. Beyond novel view synthesis, the explicit and compact nature of 3DGS enables a wide range of downstream applications that require geometric and semantic understanding. This survey provides a comprehensive overview of recent progress in 3DGS applications. It first introduces 2D foundat…

Advanced microwave photonic waveform editing: enabling the evolution of radar systems into joint radar and spectrum sensing systems
Chi Jiang, Taixia Shi, Dingding Liang, Lei Gao, Chulun Lin, Yang Chen
https://arxiv.org/abs/2506.02583

Advanced microwave photonic waveform editing: enabling the evolution of radar systems into joint radar and spectrum sensing systems
In response to the urgent demand for the development of future radar application platforms from single radar functionality towards integrated multi-functional systems, we show an advanced microwave photonic waveform editing method that enables the editing of arbitrary radar waveforms, equipping them with the capability to perform spectrum sensing. This, in turn, expands single-function radar systems into joint radar and spectrum sensing systems. We theoretically define and calculate the accumul…

with the power of editing, we can pretend like this didn’t happen

• 🔧 Extensible architecture via #PHP and #JavaScript plugins with lazy loading capabilities for performance
• 🎨 Visual #CMS functionality enabling live website content editing and drag & dr…

Today I made an account on Liberapay to throw some bucks at all the #Openstreetmap editing apps I use on my phone almost daily. Given how good this makes me feel, it's money well spent!

QGIS User Conf 2025 videos have landed!
The #QGISUC2025 team has done an awesome job recording and editing the conference presentations ...
http://anitagraser.com/2025/06/25/qgi

QGIS User Conf 2025 videos have landed!
The QGISUC2025 team has done an awesome job recording and editing the conference presentations. All “presentation” type talks where the presenter has accepted to be published are now av…

I keep using “lol” too often in work messages. Finding myself editing it out to replace with the more professional “haha”

Very iiiiiinteresting...👀 https://mastodon.social/@BenRiceM/114772697889686953

Interested in helping out with one of the most innovative, grassroots, publishing efforts around? The Journal of Open Source Software (@…) is looking for editors. We conduct collaborative checklist-based peer review of research software using GitHub issues. It's the most positive, rewarding, community-based reviewing/editing work I've ever been a part of.
https://blog.joss.theoj.org/2025/08/call-for-editors
Happy to answer questions if anyone is interested

Which #project should I prioritize or #focus on?
Please boost, that would really help, thanks!
To those who don't know one or more of those projects:
https://

Docmost: Open-source collaborative wiki and documentation software
https://docmost.com
Das klingt ernsthaft gut und würde einige Usability-Probleme des Mediawikis lösen. Unter anderem durch Markdown als Standard und Drag & Drop-Seitenhierarchie.
Realtime-Collaborative-Editing, schicke Ko…

How Robust is Model Editing after Fine-Tuning? An Empirical Study on Text-to-Image Diffusion Models
Feng He, Zhenyang Liu, Marco Valentino, Zhixue Zhao
https://arxiv.org/abs/2506.18428

How Robust is Model Editing after Fine-Tuning? An Empirical Study on Text-to-Image Diffusion Models
Model editing offers a low-cost technique to inject or correct a particular behavior in a pre-trained model without extensive retraining, supporting applications such as factual correction and bias mitigation. Despite this common practice, it remains unknown whether edits persist after fine-tuning or whether they are inadvertently reversed. This question has fundamental practical implications. For example, if fine-tuning removes prior edits, it could serve as a defence mechanism against hidden …

LoRAShield: Data-Free Editing Alignment for Secure Personalized LoRA Sharing
Jiahao Chen, junhao li, Yiming Wang, Zhe Ma, Yi Jiang, Chunyi Zhou, Qingming Li, Tianyu Du, Shouling Ji
https://arxiv.org/abs/2507.07056

LoRAShield: Data-Free Editing Alignment for Secure Personalized LoRA Sharing
The proliferation of Low-Rank Adaptation (LoRA) models has democratized personalized text-to-image generation, enabling users to share lightweight models (e.g., personal portraits) on platforms like Civitai and Liblib. However, this "share-and-play" ecosystem introduces critical risks: benign LoRAs can be weaponized by adversaries to generate harmful content (e.g., political, defamatory imagery), undermining creator rights and platform safety. Existing defenses like concept-erasure methods focu…

Reuse or Generate? Accelerating Code Editing via Edit-Oriented Speculative Decoding
Peiding Wang, Li Zhang, Fang Liu, Yinghao Zhu, Wang Xu, Lin Shi, Xiaoli Lian, Minxiao Li, Bo Shen, An Fu
https://arxiv.org/abs/2506.02780

Reuse or Generate? Accelerating Code Editing via Edit-Oriented Speculative Decoding
Large Language Models (LLMs) have demonstrated remarkable capabilities in code editing, substantially enhancing software development productivity. However, the inherent complexity of code editing tasks forces existing approaches to rely on LLMs' autoregressive end-to-end generation, where decoding speed plays a critical role in efficiency. While inference acceleration techniques like speculative decoding are applied to improve the decoding efficiency, these methods fail to account for the uniqu…

Paramount said late Tuesday that it had agreed to pay Trump $16 million to settle his lawsuit over the editing of an interview on the CBS News program “60 Minutes,” an extraordinary bribe to a sitting president by a major media organization.
Paramount said its payment included Trump’s legal fees and costs and that the money, minus the legal fees, would be paid to Mr. Trump’s future presidential library. (wink, wink)
The deal is the clearest sign yet that Trump’s ability to intimi…

Paramount to Pay Trump $16 Million to Settle ‘60 Minutes’ Lawsuit
President Trump had sued over an interview with former Vice President Kamala Harris. The company needs federal approval for a multibillion-dollar sale.

Since migrating away from big tech platforms (including Google Drive) I have been using Libreoffice for my writing and presentations.
I often get asked why I do not use OnlyOffice since it looks so much better (especially the web client). Two answers:
- The presentation tools of OnlyOffice are too barebones
But more importantly:
OnlyOffice is a company that seems to be controlled by a Russian guy who invests a lot of time to hide the fact that OnlyOffice is Russian (see…

Comparing Collabora with OnlyOffice
Collabora Online provides excellent interoperabilty, efficient backend for scalability, best privacy, and a rich interface for cooperation and editing docx, xlsx, pptx and odf

Edit360: 2D Image Edits to 3D Assets from Any Angle
Junchao Huang, Xinting Hu, Zhuotao Tian, Shaoshuai Shi, Li Jiang
https://arxiv.org/abs/2506.10507 https…

Edit360: 2D Image Edits to 3D Assets from Any Angle
Recent advances in diffusion models have significantly improved image generation and editing, but extending these capabilities to 3D assets remains challenging, especially for fine-grained edits that require multi-view consistency. Existing methods typically restrict editing to predetermined viewing angles, severely limiting their flexibility and practical applications. We introduce Edit360, a tuning-free framework that extends 2D modifications to multi-view consistent 3D editing. Built upon vi…

StyliTruth : Unlocking Stylized yet Truthful LLM Generation via Disentangled Steering
Chenglei Shen, Zhongxiang Sun, Teng Shi, Xiao Zhang, Jun Xu
https://arxiv.org/abs/2508.04530

StyliTruth : Unlocking Stylized yet Truthful LLM Generation via Disentangled Steering
Generating stylized large language model (LLM) responses via representation editing is a promising way for fine-grained output control. However, there exists an inherent trade-off: imposing a distinctive style often degrades truthfulness. Existing representation editing methods, by naively injecting style signals, overlook this collateral impact and frequently contaminate the model's core truthfulness representations, resulting in reduced answer correctness. We term this phenomenon stylization-…

Beyond Simple Edits: X-Planner for Complex Instruction-Based Image Editing
Chun-Hsiao Yeh, Yilin Wang, Nanxuan Zhao, Richard Zhang, Yuheng Li, Yi Ma, Krishna Kumar Singh
https://arxiv.org/abs/2507.05259

Beyond Simple Edits: X-Planner for Complex Instruction-Based Image Editing
Recent diffusion-based image editing methods have significantly advanced text-guided tasks but often struggle to interpret complex, indirect instructions. Moreover, current models frequently suffer from poor identity preservation, unintended edits, or rely heavily on manual masks. To address these challenges, we introduce X-Planner, a Multimodal Large Language Model (MLLM)-based planning system that effectively bridges user intent with editing model capabilities. X-Planner employs chain-of-thou…

Surgical Knowledge Rewrite in Compact LLMs: An 'Unlearn-then-Learn' Strategy with ($IA^3$) for Localized Factual Modulation and Catastrophic Forgetting Mitigation
Stanley Ngugi
https://arxiv.org/abs/2508.07075

Surgical Knowledge Rewrite in Compact LLMs: An 'Unlearn-then-Learn' Strategy with ($IA^3$) for Localized Factual Modulation and Catastrophic Forgetting Mitigation
Large Language Models (LLMs) struggle with dynamic knowledge updates, especially when new information conflicts with deeply embedded facts. Such conflicting factual edits often lead to two critical issues: resistance to adopting the new fact and severe catastrophic forgetting of unrelated knowledge. This paper introduces and evaluates a novel "unlearn-then-learn" strategy for precise knowledge editing in LLMs, leveraging the parameter-efficient fine-tuning (PEFT) technique, Infused Adapter by I…

Today's job: editing a former student's brilliant paper on a topic near and dear to my heart for publication in the journal. #Academia has its days.

Eigenvoice Synthesis based on Model Editing for Speaker Generation
Masato Murata, Koichi Miyazaki, Tomoki Koriyama, Tomoki Toda
https://arxiv.org/abs/2507.03377

Eigenvoice Synthesis based on Model Editing for Speaker Generation
Speaker generation task aims to create unseen speaker voice without reference speech. The key to the task is defining a speaker space that represents diverse speakers to determine the generated speaker trait. However, the effective way to define this speaker space remains unclear. Eigenvoice synthesis is one of the promising approaches in the traditional parametric synthesis framework, such as HMM-based methods, which define a low-dimensional speaker space using pre-stored speaker features. Thi…

From Long Videos to Engaging Clips: A Human-Inspired Video Editing Framework with Multimodal Narrative Understanding
Xiangfeng Wang, Xiao Li, Yadong Wei, Xueyu Song, Yang Song, Xiaoqiang Xia, Fangrui Zeng, Zaiyi Chen, Liu Liu, Gu Xu, Tong Xu
https://arxiv.org/abs/2507.02790

From Long Videos to Engaging Clips: A Human-Inspired Video Editing Framework with Multimodal Narrative Understanding
The rapid growth of online video content, especially on short video platforms, has created a growing demand for efficient video editing techniques that can condense long-form videos into concise and engaging clips. Existing automatic editing methods predominantly rely on textual cues from ASR transcripts and end-to-end segment selection, often neglecting the rich visual context and leading to incoherent outputs. In this paper, we propose a human-inspired automatic video editing framework (HIVE)…

If I get any of the grants I applied for, I will do #live streams again for the #development. ✨👩‍💻✨
Thus far, I asked:
- NLnet to fund #LinuxBoot integration with U-Boot XPL
- OSFF to…

SecureT2I: No More Unauthorized Manipulation on AI Generated Images from Prompts
Xiaodong Wu, Xiangman Li, Qi Li, Jianbing Ni, Rongxing Lu
https://arxiv.org/abs/2507.03636

SecureT2I: No More Unauthorized Manipulation on AI Generated Images from Prompts
Text-guided image manipulation with diffusion models enables flexible and precise editing based on prompts, but raises ethical and copyright concerns due to potential unauthorized modifications. To address this, we propose SecureT2I, a secure framework designed to prevent unauthorized editing in diffusion-based generative models. SecureT2I is compatible with both general-purpose and domain-specific models and can be integrated via lightweight fine-tuning without architectural changes. We catego…

Model Editing as a Double-Edged Sword: Steering Agent Ethical Behavior Toward Beneficence or Harm
Baixiang Huang, Zhen Tan, Haoran Wang, Zijie Liu, Dawei Li, Ali Payani, Huan Liu, Tianlong Chen, Kai Shu
https://arxiv.org/abs/2506.20606

Model Editing as a Double-Edged Sword: Steering Agent Ethical Behavior Toward Beneficence or Harm
Agents based on Large Language Models (LLMs) have demonstrated strong capabilities across a wide range of tasks. However, deploying LLM-based agents in high-stakes domains comes with significant safety and ethical risks. Unethical behavior by these agents can directly result in serious real-world consequences, including physical harm and financial loss. To efficiently steer the ethical behavior of agents, we frame agent behavior steering as a model editing task, which we term Behavior Editing. …

PartialEdit: Identifying Partial Deepfakes in the Era of Neural Speech Editing
You Zhang, Baotong Tian, Lin Zhang, Zhiyao Duan
https://arxiv.org/abs/2506.02958

PartialEdit: Identifying Partial Deepfakes in the Era of Neural Speech Editing
Neural speech editing enables seamless partial edits to speech utterances, allowing modifications to selected content while preserving the rest of the audio unchanged. This useful technique, however, also poses new risks of deepfakes. To encourage research on detecting such partially edited deepfake speech, we introduce PartialEdit, a deepfake speech dataset curated using advanced neural editing techniques. We explore both detection and localization tasks on PartialEdit. Our experiments reveal …

Microsoft launches Copilot 3D, a free AI-powered tool allowing users to transform 2D images into 3D models without a text prompt, available in Copilot Labs (Tom Warren/The Verge)
https://www.theverge.com/hands-on/756587/microsoft-copilot-3d-feature-hands-on

Microsoft’s new Copilot 3D feature is great for Ikea, bad for my dog
Microsoft has created a new Copilot 3D feature. It converts 2D images into 3D models that can be used for 3D printing or in 3D editing software.

∩️ Undo/redo functionality using git reflog for commits and branches. Custom patches for advanced rebase operations and commit editing. Bisect support for finding problematic commits efficiently.
📦 Available via #Homebrew, package managers, or binary releases.

Does Editing Improve Answer Quality on Stack Overflow? A Data-Driven Investigation
Saikat Mondal, Chanchal K. Roy
https://arxiv.org/abs/2507.21329 https://…

Does Editing Improve Answer Quality on Stack Overflow? A Data-Driven Investigation
High-quality answers in technical Q&A platforms like Stack Overflow (SO) are crucial as they directly influence software development practices. Poor-quality answers can introduce inefficiencies, bugs, and security vulnerabilities, and thus increase maintenance costs and technical debt in production software. To improve content quality, SO allows collaborative editing, where users revise answers to enhance clarity, correctness, and formatting. Several studies have examined rejected edits and ide…

B-repLer: Semantic B-rep Latent Editor using Large Language Models
Yilin Liu, Niladri Shekhar Dutt, Changjian Li, Niloy J. Mitra
https://arxiv.org/abs/2508.10201 https://…

B-repLer: Semantic B-rep Latent Editor using Large Language Models
Multimodal large language models (mLLMs), trained in a mixed modal setting as a universal model, have been shown to compete with or even outperform many specialized algorithms for imaging and graphics tasks. As demonstrated across many applications, mLLMs' ability to jointly process image and text data makes them suitable for zero-shot applications or efficient fine-tuning towards specialized tasks. However, they have had limited success in 3D analysis and editing tasks. This is due to both the…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[2/3]:
- InsViE-1M: Effective Instruction-based Video Editing with Elaborate Dataset Construction
Yuhui Wu, Liyi Chen, Ruibin Li, Shihao Wang, Chenxi Xie, Lei Zhang

This https://arxiv.org/abs/2411.14681 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

TrojanEdit: Multimodal Backdoor Attack Against Image Editing Model
Multimodal diffusion models for image editing generate outputs conditioned on both textual instructions and visual inputs, aiming to modify target regions while preserving the rest of the image. Although diffusion models have been shown to be vulnerable to backdoor attacks, existing efforts mainly focus on unimodal generative models and fail to address the unique challenges in multimodal image editing. In this paper, we present the first study of backdoor attacks on multimodal diffusion-based i…

Pronunciation Editing for Finnish Speech using Phonetic Posteriorgrams
Zirui Li, Lauri Juvela, Mikko Kurimo
https://arxiv.org/abs/2507.02115 https://

Pronunciation Editing for Finnish Speech using Phonetic Posteriorgrams
Synthesizing second-language (L2) speech is potentially highly valued for L2 language learning experience and feedback. However, due to the lack of L2 speech synthesis datasets, it is difficult to synthesize L2 speech for low-resourced languages. In this paper, we provide a practical solution for editing native speech to approximate L2 speech and present PPG2Speech, a diffusion-based multispeaker Phonetic-Posteriorgrams-to-Speech model that is capable of editing a single phoneme without text al…

FRED: Financial Retrieval-Enhanced Detection and Editing of Hallucinations in Language Models
Likun Tan, Kuan-Wei Huang, Kevin Wu
https://arxiv.org/abs/2507.20930 https://

FRED: Financial Retrieval-Enhanced Detection and Editing of Hallucinations in Language Models
Hallucinations in large language models pose a critical challenge for applications requiring factual reliability, particularly in high-stakes domains such as finance. This work presents an effective approach for detecting and editing factually incorrect content in model-generated responses based on the provided context. Given a user-defined domain-specific error taxonomy, we construct a synthetic dataset by inserting tagged errors into financial question-answering corpora and then fine-tune fou…

This https://arxiv.org/abs/2506.01921 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

MedEBench: Revisiting Text-instructed Image Editing
Text-guided image editing has seen rapid progress in natural image domains, but its adaptation to medical imaging remains limited and lacks standardized evaluation. Clinically, such editing holds promise for simulating surgical outcomes, creating personalized teaching materials, and enhancing patient communication. To bridge this gap, we introduce \textbf{MedEBench}, a comprehensive benchmark for evaluating text-guided medical image editing. It consists of 1,182 clinically sourced image-prompt …

Adobe rolls out new generative AI features for Photoshop to let users more easily add or remove people and objects, including "Harmonize" compositing, in beta (Jess Weatherbed/The Verge)
https://www.theverge.com/news/715073/adobe-photosho…

Photoshop just made it shockingly easy to edit objects and people into photos
Adobe is launching some new generative AI features for Photoshop that make it easier than ever to convincingly add or remove people and objects in photographs.

Reasoning to Edit: Hypothetical Instruction-Based Image Editing with Visual Reasoning
Qingdong He, Xueqin Chen, Chaoyi Wang, Yanjie Pan, Xiaobin Hu, Zhenye Gan, Yabiao Wang, Chengjie Wang, Xiangtai Li, Jiangning Zhang
https://arxiv.org/abs/2507.01908

Reasoning to Edit: Hypothetical Instruction-Based Image Editing with Visual Reasoning
Instruction-based image editing (IIE) has advanced rapidly with the success of diffusion models. However, existing efforts primarily focus on simple and explicit instructions to execute editing operations such as adding, deleting, moving, or swapping objects. They struggle to handle more complex implicit hypothetical instructions that require deeper reasoning to infer plausible visual changes and user intent. Additionally, current datasets provide limited support for training and evaluating rea…

FPEdit: Robust LLM Fingerprinting through Localized Knowledge Editing
Shida Wang, Chaohu Liu, Yubo Wang, Linli Xu
https://arxiv.org/abs/2508.02092 https://…

FPEdit: Robust LLM Fingerprinting through Localized Knowledge Editing
Large language models represent significant investments in computation, data, and engineering expertise, making them extraordinarily valuable intellectual assets. Nevertheless, these AI assets remain vulnerable to unauthorized redistribution and commercial exploitation through fine-tuning or black-box deployment. Current fingerprinting approaches face a fundamental trade-off: intrinsic methods require full parameter access, while backdoor-based techniques employ statistically anomalous triggers…

Pro3D-Editor : A Progressive-Views Perspective for Consistent and Precise 3D Editing
Yang Zheng, Mengqi Huang, Nan Chen, Zhendong Mao
https://arxiv.org/abs/2506.00512

Pro3D-Editor : A Progressive-Views Perspective for Consistent and Precise 3D Editing
Text-guided 3D editing aims to precisely edit semantically relevant local 3D regions, which has significant potential for various practical applications ranging from 3D games to film production. Existing methods typically follow a view-indiscriminate paradigm: editing 2D views indiscriminately and projecting them back into 3D space. However, they overlook the different cross-view interdependencies, resulting in inconsistent multi-view editing. In this study, we argue that ideal consistent 3D ed…

Setting The Table with Intent: Intent-aware Schema Generation and Editing for Literature Review Tables
Vishakh Padmakumar, Joseph Chee Chang, Kyle Lo, Doug Downey, Aakanksha Naik
https://arxiv.org/abs/2507.19521

Setting The Table with Intent: Intent-aware Schema Generation and Editing for Literature Review Tables
The increasing volume of academic literature makes it essential for researchers to organize, compare, and contrast collections of documents. Large language models (LLMs) can support this process by generating schemas defining shared aspects along which to compare papers. However, progress on schema generation has been slow due to: (i) ambiguity in reference-based evaluations, and (ii) lack of editing/refinement methods. Our work is the first to address both issues. First, we present an approach…

VideoGuard: Protecting Video Content from Unauthorized Editing
Junjie Cao, Kaizhou Li, Xinchun Yu, Hongxiang Li, Xiaoping Zhang
https://arxiv.org/abs/2508.03480 https://

VideoGuard: Protecting Video Content from Unauthorized Editing
With the rapid development of generative technology, current generative models can generate high-fidelity digital content and edit it in a controlled manner. However, there is a risk that malicious individuals might misuse these capabilities for misleading activities. Although existing research has attempted to shield photographic images from being manipulated by generative models, there remains a significant disparity in the protection offered to video content editing. To bridge the gap, we pr…

TokenSmith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability
Mohammad Aflah Khan, Ameya Godbole, Johnny Tian-Zheng Wei, Ryan Wang, James Flemings, Krishna Gummadi, Willie Neiswanger, Robin Jia
https://arxiv.org/abs/2507.19419

TokenSmith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability
Understanding the relationship between training data and model behavior during pretraining is crucial, but existing workflows make this process cumbersome, fragmented, and often inaccessible to researchers. We present TokenSmith, an open-source library for interactive editing, inspection, and analysis of datasets used in Megatron-style pretraining frameworks such as GPT-NeoX, Megatron, and NVIDIA NeMo. TokenSmith supports a wide range of operations including searching, viewing, ingesting, expor…

Fine-Grained Spatially Varying Material Selection in Images
Julia Guerrero-Viu, Michael Fischer, Iliyan Georgiev, Elena Garces, Diego Gutierrez, Belen Masia, Valentin Deschaintre
https://arxiv.org/abs/2506.09023

Fine-Grained Spatially Varying Material Selection in Images
Selection is the first step in many image editing processes, enabling faster and simpler modifications of all pixels sharing a common modality. In this work, we present a method for material selection in images, robust to lighting and reflectance variations, which can be used for downstream editing tasks. We rely on vision transformer (ViT) models and leverage their features for selection, proposing a multi-resolution processing strategy that yields finer and more stable selection results than …

Activation-Guided Local Editing for Jailbreaking Attacks
Jiecong Wang, Haoran Li, Hao Peng, Ziqian Zeng, Zihao Wang, Haohua Du, Zhengtao Yu
https://arxiv.org/abs/2508.00555 http…

Activation-Guided Local Editing for Jailbreaking Attacks
Jailbreaking is an essential adversarial technique for red-teaming these models to uncover and patch security flaws. However, existing jailbreak methods face significant drawbacks. Token-level jailbreak attacks often produce incoherent or unreadable inputs and exhibit poor transferability, while prompt-level attacks lack scalability and rely heavily on manual effort and human ingenuity. We propose a concise and effective two-stage framework that combines the advantages of these approaches. The …

InstaInpaint: Instant 3D-Scene Inpainting with Masked Large Reconstruction Model
Junqi You, Chieh Hubert Lin, Weijie Lyu, Zhengbo Zhang, Ming-Hsuan Yang
https://arxiv.org/abs/2506.10980

InstaInpaint: Instant 3D-Scene Inpainting with Masked Large Reconstruction Model
Recent advances in 3D scene reconstruction enable real-time viewing in virtual and augmented reality. To support interactive operations for better immersiveness, such as moving or editing objects, 3D scene inpainting methods are proposed to repair or complete the altered geometry. However, current approaches rely on lengthy and computationally intensive optimization, making them impractical for real-time or online applications. We propose InstaInpaint, a reference-based feed-forward framework t…

This https://arxiv.org/abs/2506.00512 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGR_…

Pro3D-Editor : A Progressive-Views Perspective for Consistent and Precise 3D Editing
Text-guided 3D editing aims to precisely edit semantically relevant local 3D regions, which has significant potential for various practical applications ranging from 3D games to film production. Existing methods typically follow a view-indiscriminate paradigm: editing 2D views indiscriminately and projecting them back into 3D space. However, they overlook the different cross-view interdependencies, resulting in inconsistent multi-view editing. In this study, we argue that ideal consistent 3D ed…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[2/9]:
- Prompt-Softbox-Prompt: A Free-Text Embedding Control for Image Editing
Yitong Yang, Yinglin Wang, Tian Zhang, Jing Wang, Shuting He

Adobe launches a Photoshop app for Android in beta for devices running Android 11 or later with 6GB of RAM, including core desktop features like layering (Aisha Malik/TechCrunch)
https://techcrunch.com/2025/06/03/adobe-launches-beta-…

Adobe launches beta version of its Photoshop app on Android | TechCrunch
The app offers a similar set of editing tools as the desktop version, including layering and masking, but is optimized for mobile screens.

EditInspector: A Benchmark for Evaluation of Text-Guided Image Edits
Ron Yosef, Moran Yanuka, Yonatan Bitton, Dani Lischinski
https://arxiv.org/abs/2506.09988

EditInspector: A Benchmark for Evaluation of Text-Guided Image Edits
Text-guided image editing, fueled by recent advancements in generative AI, is becoming increasingly widespread. This trend highlights the need for a comprehensive framework to verify text-guided edits and assess their quality. To address this need, we introduce EditInspector, a novel benchmark for evaluation of text-guided image edits, based on human annotations collected using an extensive template for edit verification. We leverage EditInspector to evaluate the performance of state-of-the-art…

Cut2Next: Generating Next Shot via In-Context Tuning
Jingwen He, Hongbo Liu, Jiajun Li, Ziqi Huang, Yu Qiao, Wanli Ouyang, Ziwei Liu
https://arxiv.org/abs/2508.08244 https://

Cut2Next: Generating Next Shot via In-Context Tuning
Effective multi-shot generation demands purposeful, film-like transitions and strict cinematic continuity. Current methods, however, often prioritize basic visual consistency, neglecting crucial editing patterns (e.g., shot/reverse shot, cutaways) that drive narrative flow for compelling storytelling. This yields outputs that may be visually coherent but lack narrative sophistication and true cinematic integrity. To bridge this, we introduce Next Shot Generation (NSG): synthesizing a subsequent…

Shape-for-Motion: Precise and Consistent Video Editing with 3D Proxy
Yuhao Liu, Tengfei Wang, Fang Liu, Zhenwei Wang, Rynson W. H. Lau
https://arxiv.org/abs/2506.22432

Shape-for-Motion: Precise and Consistent Video Editing with 3D Proxy
Recent advances in deep generative modeling have unlocked unprecedented opportunities for video synthesis. In real-world applications, however, users often seek tools to faithfully realize their creative editing intentions with precise and consistent control. Despite the progress achieved by existing methods, ensuring fine-grained alignment with user intentions remains an open and challenging problem. In this work, we present Shape-for-Motion, a novel framework that incorporates a 3D proxy for …

Moodifier: MLLM-Enhanced Emotion-Driven Image Editing
Jiarong Ye, Sharon X. Huang
https://arxiv.org/abs/2507.14024 https://arxiv.org/…

Moodifier: MLLM-Enhanced Emotion-Driven Image Editing
Bridging emotions and visual content for emotion-driven image editing holds great potential in creative industries, yet precise manipulation remains challenging due to the abstract nature of emotions and their varied manifestations across different contexts. We tackle this challenge with an integrated approach consisting of three complementary components. First, we introduce MoodArchive, an 8M+ image dataset with detailed hierarchical emotional annotations generated by LLaVA and partially valid…

NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining
Maksim Kuprashevich, Grigorii Alekseenko, Irina Tolstykh, Georgii Fedorov, Bulat Suleimanov, Vladimir Dokholyan, Aleksandr Gordeev
https://arxiv.org/abs/2507.14119

NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining
Recent advances in generative modeling enable image editing assistants that follow natural language instructions without additional user input. Their supervised training requires millions of triplets: original image, instruction, edited image. Yet mining pixel-accurate examples is hard. Each edit must affect only prompt-specified regions, preserve stylistic coherence, respect physical plausibility, and retain visual appeal. The lack of robust automated edit-quality metrics hinders reliable auto…