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Thinking in Blender: Staged Executable Inverse Graphics with Vision-Language Models
arXiv:2606.02580v1 Announce Type: new Abstract: Inverse graphics is a longstanding and highly underconstrained problem that seeks to reconstruct images as editable 3D scenes which can be rendered, relit, and manipulated. In this work, we investigate whether pretrained vision-language models (VLMs) can perform executable inverse graphics directly from a single image by reconstructing a scene as an editable Blender program, without relying on specialized 2D or 3D foundation models,...
Marjane Satrapi, Iranian-French author of graphic novel Persepolis, dies aged 56
Marjane Satrapi, Iranian-French author of graphic novel Persepolis, dies aged 56 Satrapi created Persepolis based on her life during Iran’s revolution. The work achieved global success and film recognition. Marjane Satrapi, the Iranian-French artist, filmmaker and author of the autobiographical graphic novel Persepolis, has died aged 56, French President Emmanuel Macron's office said on Thursday (Jun 4) "Her passing is that of a figure of French culture and of an artist enamored of freedom,...
AMD's Radeon RX 9070 GRE graphics card is now available to purchase
AMD's Radeon RX 9070 GRE graphics card is now available to purchase It'll set you back $549. AMD just released the Radeon RX 9070 GRE graphics card globally after it came out in China last year. The GRE stands for "Golden Rabbit Edition," though sometimes it's referred to as the "Great Radeon Edition."
In-Context Graphical Inference
arXiv:2606.05042v1 Announce Type: new Abstract: Marginal inference in discrete graphical models forces a choice between exactness and scalability: exact algorithms are intractable for high-treewidth graphs, while iterative approximations (Belief Propagation, variational methods) sacrifice convergence guarantees on frustrated topologies. We argue that this dichotomy stems from a mismatched inductive bias: iterative methods abandon the sequential elimination structure that makes exact...
Graphical einops: bridging tensor networks and computation graphs
Announce Type: new Abstract: Architecture diagrams are ubiquitous in deep learning, but they are usually only representational: the tensor-program identities they suggest are still proved by prose and tensor-axis manipulation. We introduce a formal graphical calculus for the structural fragment of tensor programming underlying einops, making such diagrams proof-enabling. Our calculus represents tensor axes as nested graded tubes around a base type.
TASTE: A Designer-Annotated Multi-Dimensional Preference Dataset for AI-Generated Graphic Design
Announce Type: replace Abstract: Text-to-image models now generate graphic design at production scale, yet their supervision still comes primarily from photo-style preference datasets with a single overall verdict per comparison. Designers evaluate designs along several distinct axes (e.g., typography, layout, color harmony) that a single preference label collapses. We release \emph{TASTE} \textit{(Typography, Aesthetics, Spatial, Tone, Etc.)}, a multi-dimensional preference dataset in which...
‘I want to bury it under a roundabout!’ Kim Noble on his unusual approach to promoting his graphic novel
Performance artist Kim Noble is promoting his graphic novel, *In Pursuit of a Wonderful Nothing*, with unconventional methods. He has proposed burying copies of the book under a roundabout, a suggestion his publishers reportedly rejected. Noble also recounted past attempts to promote his work by leaving drawings in public toilets for publishers to find.
Making Graphics Like it's 1993
Personal website and blog. Catlantean 3D is a side-project I've been slowly building in my spare time for over a year, and I intend to release it on Steam next year. My goal was to build a complete, shippable first-person shooter using techniques that were common in the early 90s, while allowing myself the luxury of using a modern compiler and a platform abstraction layer.
TurtleAI: Benchmarking Multimodal Models for Visual Programming in Turtle Graphics
arXiv:2606.03626v1 Announce Type: new Abstract: Vision-language models (VLMs) have been explored for visual programming, where they generate code to solve visual tasks. However, most prior work focuses on visual programming for productivity; it remains unclear how well current VLMs perform on education-oriented visual programming and what factors limit their performance. To bridge this gap, we introduce TurtleAI, a benchmark containing 823 tasks curated based on real-world visual programming...
Mitigating False Credit Propagation: Probabilistic Graphical Reward Aggregation for Rubric-Based Reinforcement Learning
arXiv:2606.03361v1 Announce Type: new Abstract: Rubric-based rewards are increasingly used for open-ended language model post-training, but criterion-level scores are often aggregated as independent utilities. This flat scalarization ignores rubric-specified prerequisite and activation relations among criteria, allowing reward or penalty to be counted even when the condition that licenses it is absent. We call this structural reward-aggregation failure \textbf{False Credit Propagation} (FCP).