Search: “synthesis”

arXiv:2604.13604v1 Announce Type: cross Abstract: Binary stellar evolution simulations are computationally expensive. Stellar population synthesis relies on these detailed evolution models at a fundam

arXiv:2604.13062v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated strong capabilities in code generation and text synthesis, yet their potential for sym

arXiv:2604.13340v1 Announce Type: new Abstract: We present a multispectral extension to 3D Gaussian Splatting (3DGS) for wavelength-aware view synthesis. Each Gaussian is augmented with spectral radia

arXiv:2604.13036v1 Announce Type: new Abstract: Recent advances in video generation enable a new paradigm for 3D scene creation: generating camera-controlled videos that simulate scene walkthroughs, t

arXiv:2305.16347v2 Announce Type: replace-cross Abstract: Synthesis of digital artifacts conditioned on user prompts has become an important paradigm facilitating an explosion of use cases with genera

arXiv:2604.12446v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models have achieved remarkable success in image synthesis, but their reliance on large-scale data and open ecosystems i

arXiv:2604.12322v1 Announce Type: new Abstract: The push for efficient text to image synthesis has moved the field toward one step sampling, yet existing methods still face a three way tradeoff among

arXiv:2604.10512v1 Announce Type: new Abstract: The development of generalizable Novel View Synthesis (NVS) models is critically limited by the scarcity of large-scale training data featuring diverse

arXiv:2604.09688v1 Announce Type: new Abstract: Recent large-scale generative models enable high-quality 3D synthesis. However, the public accessibility of pre-trained weights introduces a critical vu

arXiv:2507.14800v2 Announce Type: replace-cross Abstract: With the advanced reasoning, contextual understanding, and information synthesis capabilities of large language models (LLMs), a novel paradig

arXiv:2604.11365v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) has been widely used for automated reasoning data exploration, but current supervision extraction methods remain ineffici

arXiv:2604.09903v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has recently unlocked real-time, high-fidelity novel view synthesis by representing scenes using explicit 3D primitives. Ho

arXiv:2604.11229v1 Announce Type: cross Abstract: Retrieving procedure-oriented evidence from materials science papers is difficult because key synthesis details are often scattered across long, conte

arXiv:2505.13777v2 Announce Type: replace-cross Abstract: We present Sat2Sound, a unified multimodal framework for geospatial soundscape understanding, designed to predict and map the distribution of

arXiv:2604.11797v1 Announce Type: new Abstract: We present SyncFix, a framework that enforces cross-view consistency during the diffusion-based refinement of reconstructed scenes. SyncFix formulates r

arXiv:2604.09850v1 Announce Type: new Abstract: Existing text-to-image diffusion models, while excelling at subject synthesis, exhibit a persistent foreground bias that treats the background as a pass

arXiv:2604.11685v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has become a state-of-the-art framework for real-time, high-fidelity novel view synthesis. However, its substantial storage

arXiv:2510.20512v2 Announce Type: replace Abstract: Recent progress in accelerating text-to-image diffusion models enables high-fidelity synthesis within a single denoising step. However, customizing

arXiv:2604.09023v1 Announce Type: new Abstract: Multi-task visual anomaly detection is critical for car-related manufacturing quality assessment. However, existing methods remain task-specific, hinder

arXiv:2604.09246v1 Announce Type: cross Abstract: Differentiable Digital Signal Processing (DDSP) pipelines for voice conversion rely on subtractive synthesis, where a periodic excitation signal is sh

arXiv:2604.05072v2 Announce Type: replace Abstract: Recent large language models have shifted SVG generation from differentiable rendering optimization to autoregressive program synthesis. However, ex

arXiv:2511.20068v2 Announce Type: replace Abstract: Autoregressive (AR) image generation has recently emerged as a powerful paradigm for image synthesis. Leveraging the generation principle of large l

arXiv:2604.07786v1 Announce Type: new Abstract: Talking face generation has gained significant attention as a core application of generative models. To enhance the expressiveness and realism of synthe

arXiv:2604.06285v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have become essential for tasks such as image synthesis, captioning, and retrieval by aligning textual and visual inform

arXiv:2604.08370v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has demonstrated impressive performance in 3D scene reconstruction. Beyond novel view synthesis, it shows great potential f

arXiv:2604.08546v1 Announce Type: new Abstract: Text-to-video diffusion models have enabled open-ended video synthesis, but often struggle with generating the correct number of objects specified in a

arXiv:2610.22298v1 Announce Type: cross Abstract: Large language models (LLMs) can generate differential diagnoses for complex cases, but a useful second opinion must also be factually grounded, clini

arXiv:2610.21505v1 Announce Type: new Abstract: Real-world video denoising for communication systems must handle mixed degradations such as sensor noise, compression artifacts, and motion-induced inco

arXiv:2610.20939v1 Announce Type: new Abstract: Online reinforcement learning (RL) with verifiable rewards has driven rapid progress in mathematics, coding, and tool use, but scaling this success to G

arXiv:2610.16251v1 Announce Type: cross Abstract: Deep-search agents are commonly trained by distilling tool-use trajectories from stronger teacher models. However, structurally complex questions may

arXiv:2610.19080v1 Announce Type: new Abstract: Reinforcement learning (RL) has substantially improved the reasoning of autoregressive and discrete-diffusion language models. Language models that gene

arXiv:2610.17358v1 Announce Type: cross Abstract: Formal verification proves that a program satisfies its specification, but says nothing about whether the specification captures what the author meant

arXiv:2610.14118v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has driven their deployment toward general-purpose harness environments, where LLM-based agents op

arXiv:2610.18010v2 Announce Type: replace-cross Abstract: We introduce Fish Audio Drama 3, an open-source speech generation model that turns text into directed performances, built on a 35B-parameter m

arXiv:2606.17648v3 Announce Type: replace Abstract: Standard accuracy metrics cannot explain why LLMs handle variable tracking but fail on semantically equivalent loops. We study an internal lifecycle

arXiv:2610.15082v1 Announce Type: cross Abstract: As text-to-speech (TTS) systems continue to advance, provenance tracking and security verification of synthesized speech have become increasingly impo

arXiv:2610.20341v1 Announce Type: new Abstract: Feed-forward Gaussian reconstruction builds 3D scenes directly from input images for novel view rendering, but learning Gaussian attributes from predict

arXiv:2610.19131v1 Announce Type: cross Abstract: Maintenance work orders are the largest written record of how industrial equipment fails, yet in most plants they are close to unusable for analysis.

arXiv:2610.16397v1 Announce Type: new Abstract: We study environment scaling as a way to increase agent-benchmark difficulty while holding core task objectives fixed. Our framework, Recursive Environm

arXiv:2610.15481v1 Announce Type: new Abstract: Independently authored skills can impose incompatible requirements, competing preferences, and redundant instructions when jointly loaded by an LLM agen

arXiv:2512.23044v3 Announce Type: replace Abstract: Autonomous agents are shifting information seeking from passive retrieval toward proactive, open-ended research, yet this progress has largely bypas

arXiv:2610.19847v1 Announce Type: new Abstract: We address inverse rendering with 3D Gaussian Splatting (3DGS) by introducing explicit visibility modeling for relighting as well as material and light

arXiv:2610.16692v1 Announce Type: new Abstract: We address the Cross-View Object Re-Identification (ReID) task, aiming to match identities across drastically different viewpoints. We focus on Single-V

arXiv:2610.14261v1 Announce Type: new Abstract: Whole-slide images (WSIs) are gigapixel-scale digital scans of histopathology tissue and serve as the primary basis for cancer diagnosis. Existing histo

arXiv:2610.15077v1 Announce Type: new Abstract: A brain tumor is an unusual growth of cells in the brain that can be cancerous or not, affecting normal brain function and causing serious risk to healt

arXiv:2610.18871v1 Announce Type: new Abstract: Sparse-to-dense motion completion recovers dense mesh motion from sparse vertex displacements. Residual priors trained on one geometry family frequently