The paper introduces a Spatial Canvas Interface for poster generation, allowing users to directly compose visual elements in space using four binding types: semantic, identity, text, and pixel, along with Text Specifications for individual elements and global appearance. The Compo model, adapted from a pretrained image editing model, supports both direct inference and agentic mode, achieving stronger compositional controllability than existing systems while maintaining high visual quality.
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This work provides a new interface for creating posters by directly composing visual elements in space, improving control over the composition process compared to traditional text prompting methods.
The paper introduces Trace2Env, a learning-free framework that uses historical interaction traces to create a reusable environment worldbook for simulating realistic environments without rebuilding the original system. It improves next-observation fidelity and long-horizon interaction consistency compared to conventional prompt-based language world models.
4 days agoDaily PapersTetris3D is a generative framework for 3D scene reconstruction from a single image, ensuring objects are geometrically and physically coherent. It uses explicit conditioning on surrounding objects' geometry and physical relationships, along with a physics-based dataset called ComOb for training and evaluation.
2 days agoDaily PapersThe paper investigates on-policy distillation (OPD) in cross-tokenizer settings, focusing on alignment coverage and supervision reliability. It finds that strict 1:1 token alignment covers most student-generated tokens despite vocabulary mismatches, and that restricting reverse KL to a top-16 subset of shared vocabulary achieves comparable accuracy to full shared-vocabulary OPD, while adding span supervision reduces accuracy.
3 days agoDaily PapersThe paper introduces SGF+, a method for autoregressive video generation that decouples the roles of denoising and context writing by assigning separate parameters to each, improving visual quality and temporal consistency without additional training data or longer training periods.
2 days agoDaily PapersCheckerBench is a benchmark for evaluating coding agents' ability to synthesize static-analysis checkers from defect specifications, including tasks derived from 300 CVEs across multiple repositories and language ecosystems. CheckerLab, an evaluation framework, measures diagnostic contrast, patch localization, and tool use, with results showing that current agents struggle to develop reliable checkers, achieving a maximum Pass@1 of 45.33%.
3 days agoDaily PapersNAMVIS is a diffusion-free framework for multi-view image synthesis that uses geometry-conditioned next-scale autoregression, predicting discrete visual tokens through coarse-to-fine scale steps and parallel sampling across target views. It outperforms diffusion-based methods in PSNR, SSIM, and LPIPS while being over three times faster.
6 days ago