Knowledge catalogue
arXiv:2605.15131v1 Announce Type: new Abstract: Reactive synthesis, the problem of automatically constructing a hardware circuit from a logical specification, is a long-standing challenge in formal ve
Anyone building with AI eventually hits the same tradeoff: how to get the most intelligence per dollar, the right model at the right cost for each task. That’s what DigitalOcean Inference Engine is bu
arXiv:2607.19765v1 Announce Type: new Abstract: Large view synthesis models synthesize novel views through cross-view attention without explicit 3D representations, and recent studies have shown that
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arXiv:2406.12632v3 Announce Type: replace-cross Abstract: Positron emission tomography (PET) provides molecular biomarkers for Alzheimer's disease and related dementias (ADRD) and is increasingly used
arXiv:2601.02424v2 Announce Type: replace-cross Abstract: The synthesis of nanocrystals has been highly dependent on trial-and-error, due to the complex correlation between synthesis parameters and ph
arXiv:2606.08421v1 Announce Type: new Abstract: Multi-contrast brain MRI provide complementary soft-tissue characteristics that aid in the screening and diagnosis of diseases. However, limited scannin
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Auto-generated synthesis of 194 entries about harrison-chase--x
arXiv:2510.07927v2 Announce Type: replace Abstract: Anomaly detection plays a pivotal role in manufacturing quality control, yet its application is constrained by limited abnormal samples and high man
arXiv:2604.07900v1 Announce Type: new Abstract: Industrial anomaly generation is a crucial method for alleviating the data scarcity problem in anomaly detection tasks. Most existing anomaly synthesis
arXiv:2503.02537v4 Announce Type: replace Abstract: Diffusion models have achieved remarkable progress across various visual generation tasks. However, their performance significantly declines when ge
// Multi-Agent Synthesis RAG // Nice paper on improving RAG systems with multiple agents. (bookmark it) The paper introduces MASS-RAG, a multi-agent synthesis framework for retrieval-augmented generat
arXiv:2604.16817v1 Announce Type: new Abstract: Imbalanced data is commonly present in real-world applications. While data synthesis can effectively mitigate the data scarcity problem of rare-classes,
arXiv:2605.11544v2 Announce Type: replace Abstract: Strategy synthesis typically follows an all-or-nothing paradigm, returning unrealisable whenever a specification cannot be guaranteed in an uncertai
arXiv:2607.23040v1 Announce Type: cross Abstract: This work proposes an actuator-aware spatiotemporal tube (STT) synthesis framework to accomplish temporal reach-avoid-stay (T-RAS) tasks for an unknow
arXiv:2507.22080v2 Announce Type: replace-cross Abstract: Acquiring high-quality instruction-code pairs is essential for training Large Language Models for code generation. While automated synthesis h
arXiv:2607.24729v1 Announce Type: new Abstract: We introduce MicroZoom, a generative framework for gigapixel image synthesis at the microscopic scale. Given a standard photograph and a sparse set of c
arXiv:2406.08311v3 Announce Type: replace-cross Abstract: Existing evaluations of tabular synthesis models rely primarily on low-order statistics and downstream task performance, leaving multivariate
arXiv:2606.29636v1 Announce Type: cross Abstract: An important task in quantum computing is unitary circuit synthesis compatible with physical hardware constraints. This problem has a natural hybrid s
arXiv:2606.29020v1 Announce Type: cross Abstract: Weather synthesis aims to add weather effects to input videos while preserving scene identity, structure, and motion. The key limitation of existing m
arXiv:2605.21213v1 Announce Type: cross Abstract: In this work, we present quantum reinforcement learning (RL) as a solution strategy for process synthesis problems. Building on our prior work, we dev
arXiv:2605.20920v1 Announce Type: new Abstract: Recent advances in machine learning and the availability of articulatory datasets allow vocal tract synthesis to be conditioned on phonetic sequences, a
arXiv:2604.23602v1 Announce Type: cross Abstract: Early, tool-free prediction of post-synthesis timing remains a key obstacle to rapid RTL iteration. We introduce TimingLLM, a two-stage retrieval-augm
arXiv:2505.11334v4 Announce Type: replace Abstract: This work aims at a challenging task: human action-reaction synthesis, i.e., generating human reactions conditioned on the action sequence of anothe
arXiv:2604.21414v1 Announce Type: new Abstract: Existing text-to-SQL synthesis pipelines still conflate executability with semantic validity: syntactic checks and execution-based validation can retain
arXiv:2602.11569v2 Announce Type: replace Abstract: Population synthesis is essential for individual-level simulation in transport planning and socio-economic analysis, yet remains challenging due to
arXiv:2604.21146v1 Announce Type: new Abstract: Diffusion models have achieved remarkable quality in multi-modal MRI synthesis, but their computational cost (hundreds of sampling steps and separate mo
arXiv:2607.27379v1 Announce Type: new Abstract: High-quality, diverse data are vital for large language models (LLMs) but remain scarce and costly. Data synthesis is a viable alternative and succeeds
arXiv:2603.11325v2 Announce Type: replace Abstract: Low-field to high-field MRI synthesis has emerged as a promising strategy to improve image quality when access to high-field scanners is limited. Ho
arXiv:2607.27167v1 Announce Type: cross Abstract: LLM-based agents excel at software engineering tasks where an existing codebase provides context, but constructing a program from scratch remains fund
arXiv:2607.04554v1 Announce Type: new Abstract: Dexterous grasping across diverse object scales requires contact modes ranging from two-finger pinches to bimanual grasps. Existing dexterous grasp synt
arXiv:2511.17918v2 Announce Type: replace Abstract: Despite the success of recent novel view synthesis methods, they tend to struggle in sparse-view settings. This poor generalization to unseen viewpo
arXiv:2606.00315v1 Announce Type: new Abstract: Modern generative machine learning (ML) models can propose novel inorganic crystalline materials with targeted properties; however, synthesis planning o
arXiv:2606.01315v1 Announce Type: new Abstract: Novel view synthesis (NVS) is a fundamental problem in computer vision and graphics. Recent advances in neural radiance fields (NeRF), 3D Gaussian Splat
arXiv:2606.02068v1 Announce Type: cross Abstract: Recently, novel view synthesis has witnessed remarkable progress, with mainstream methods such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatt
arXiv:2605.13536v1 Announce Type: cross Abstract: High-Level Synthesis (HLS) compiles algorithmic C/C++ descriptions into hardware, with Quality of Results (QoR) -- latency and resource utilization --
arXiv:2605.11867v1 Announce Type: new Abstract: Structural MRI-to-amyloid PET synthesis has been proposed as a non-invasive alternative for amyloid assessment in Alzheimer's disease (AD). However, rep
arXiv:2605.12169v1 Announce Type: new Abstract: With the recent surge of generative models, diffusion-based approaches have become mainstream for view synthesis tasks, either in an explicit depth-warp
arXiv:2506.00433v4 Announce Type: replace Abstract: High-resolution image synthesis remains a core challenge in generative modeling, particularly in balancing computational efficiency with the preserv
arXiv:2604.12169v1 Announce Type: new Abstract: We present a screw geometry-based manipulation planning framework for the robotic automation of solution-based synthesis, exemplified through the prepar
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arXiv:2607.01962v1 Announce Type: cross Abstract: We study the challenging problem of novel view video synthesis from single images or monocular videos. Existing methods, which operate under the assum
arXiv:2607.00569v1 Announce Type: new Abstract: In this article, we present dynamic modeling, gait synthesis, and feedback control design for a modular novel subsurface robot, designed for human-free
arXiv:2606.31229v1 Announce Type: new Abstract: Ideation plays a pivotal role in scientific discovery. Recent LLM, especially AI Scientist systems, show promising potential for automated ideation. How
arXiv:2605.30469v1 Announce Type: cross Abstract: 3D audio and novel-view acoustic synthesis models are usually evaluated with global metrics.However, global metrics often hide where and why binaural
arXiv:2605.29891v1 Announce Type: new Abstract: Recent Large View Synthesis Models (LVSMs) advocate an encoder-decoder architecture that separates reconstruction and rendering into distinct networks.
arXiv:2605.25763v2 Announce Type: replace Abstract: Text-to-image synthesis has made significant progress, benefiting from the strong generative capabilities of diffusion models. However, these models
arXiv:2605.16142v1 Announce Type: new Abstract: LLMs have shown impressive success in program synthesis, discovering programs that surpass prior solutions. However, these approaches rely on simple num
arXiv:2605.07521v1 Announce Type: new Abstract: Current computer-aided synthesis planning (CASP) methods often treat retrosynthesis as solved once a single feasible route is identified, focusing prima
arXiv:2605.00074v1 Announce Type: cross Abstract: DNA-synthesis providers screen incoming orders by searching the requested sequence against curated hazard lists. We show that this baseline collapses
arXiv:2511.07743v3 Announce Type: replace Abstract: Ultrasound imaging is a cornerstone of non-invasive clinical diagnostics, yet its limited field of view poses challenges for novel view synthesis. W
arXiv:2411.16719v4 Announce Type: replace Abstract: Domain randomization through synthesis is a powerful strategy to train networks that are unbiased with respect to the domain of the input images. Ra
arXiv:2602.17909v2 Announce Type: replace Abstract: Diffusion-based approaches have recently demonstrated strong performance for single-image novel view synthesis by conditioning generative models on
arXiv:2604.15675v1 Announce Type: new Abstract: Achieving cultural alignment in Large Language Models (LLMs) increasingly depends on synthetic data generation. For such synthesis, the most vital initi