Search: “synthesis”

arXiv:2607.13393v1 Announce Type: cross Abstract: A field can reformulate its computations freely exactly where its demand is stated independently of any incumbent implementation, and finds itself una

arXiv:2607.13539v1 Announce Type: new Abstract: While traditional graphics methods often synthesize 3D indoor scenes autoregressively or hierarchically, recent vision-language model (VLM)-based genera

arXiv:2607.13860v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in 2D medical image understanding, their extension to 3D volumetric

Retrieval-augmented generation (RAG) enhances large language models (LLMs) with external knowledge but still suffers from long contexts and disjoint retrieval–generation optimization. In this work, we

arXiv:2511.09483v3 Announce Type: replace Abstract: While multimodal large language models can describe visual content, their ability to generate executable procedures remains underexplored. CrochetBe

arXiv:2607.12934v1 Announce Type: new Abstract: Remote sensing change detection (RSCD) models are prone to catastrophic forgetting when incrementally adapted to new domains. Existing domain-incrementa

arXiv:2512.09925v2 Announce Type: replace Abstract: Recent advances in Gaussian Splatting-based inverse rendering extend Gaussian primitives with shading parameters and physically grounded light trans

arXiv:2603.13421v2 Announce Type: replace-cross Abstract: Generative models based on the Flow Matching objective, particularly Rectified Flow, have emerged as a dominant paradigm for efficient, high-f

arXiv:2607.12310v1 Announce Type: cross Abstract: While modern question answering (QA) systems excel on clean, schema-aligned corpora, real-world knowledge is rarely so neatly packaged. Answering ques

arXiv:2607.12858v1 Announce Type: new Abstract: Accurate open-world obstacle detection is critical for autonomous driving. Current anomaly segmentation methods suffer from a fundamental blind spot: th

arXiv:2607.11980v1 Announce Type: new Abstract: Like many optimization-driven domains, railway rescheduling relies on Mixed-Integer Linear Programming (MILP), yet the field's modeling knowledge is sca

arXiv:2607.11948v1 Announce Type: new Abstract: Regulated financial institutions operating under data-residency rules need tenant-owned language models that can run inside the institution's perimeter.

arXiv:2602.04029v2 Announce Type: replace-cross Abstract: Relational Foundation Models (RFMs) facilitate data-driven decision-making by learning from complex multi-table databases. However, the divers

arXiv:2607.12464v1 Announce Type: new Abstract: When labeled data are scarce, off-the-shelf diffusion models can augment training sets for few-shot medical image classification, but not all generated

Introduction RxBrain (Hy-Embodied-RxBrain-1.0) is a unified multimodal foundation model for embodied cognition — a single model that couples language reasoning with visual imagination to deliver three

arXiv:2607.08741v1 Announce Type: cross Abstract: Generating realistic 3D human motions in real-time within interactive applications is key for animation, simulation, and humanoid robotics. While rece

arXiv:2607.08073v1 Announce Type: new Abstract: Fetal electrocardiogram (fECG) and Doppler ultrasound provide complementary views of fetal cardiovascular function: fECG captures electrical activity wh

arXiv:2607.07779v1 Announce Type: cross Abstract: Recent developments in AI for Mathematics (AI4Math), especially Large Language Model (LLM)-driven theorem provers, has achieved remarkable success in

arXiv:2502.20805v3 Announce Type: replace-cross Abstract: Hand-object interaction(HOI) is the fundamental link between human and environment, yet its dexterous and complex pose significantly challenge

arXiv:2607.07891v1 Announce Type: cross Abstract: Roy Harris's Integrationist linguistics offers a compelling critique of the referentialist tradition embedded deep at the heart of computational appro

arXiv:2607.08705v1 Announce Type: new Abstract: Rapid advancements in video diffusion models and temporal editing tools have enabled the generation of highly realistic human-centric videos, posing unp

arXiv:2604.05182v2 Announce Type: replace-cross Abstract: We introduce the Large Sparse Reconstruction Model to study how scaling transformer context windows affects feed-forward 3D reconstruction. Al

arXiv:2607.08250v1 Announce Type: new Abstract: Dynamic scene reconstruction remains challenging due to the heterogeneous and spatially varying nature of real-world motion. Although recent 3D Gaussian

arXiv:2607.08003v1 Announce Type: cross Abstract: Catalysts are essential for sustainable chemical manufacturing, yet discovering novel architectures remains a bottleneck dominated by trial-and-error

arXiv:2607.07748v1 Announce Type: new Abstract: Large Language Models achieve strong code generation for high resource languages like Python and Java but suffer sharp performance drops on Low-Resource

arXiv:2606.17482v2 Announce Type: replace Abstract: Generating adversarial driving scenarios is critical for evaluating and improving autonomous vehicle decision-making systems in simulation. Recent a

arXiv:2607.08010v1 Announce Type: new Abstract: Production LLM agents often waste latency and reliability by regenerating code for the same procedural steps on every request. We replace this inference

arXiv:2607.07370v1 Announce Type: cross Abstract: In embodied intelligence systems, the motion controller serves as the critical bridge between semantic reasoning and physical execution. Humanoid cont

arXiv:2603.16551v2 Announce Type: replace-cross Abstract: Generative models are increasingly used to augment medical imaging datasets for fairer AI, yet a key assumption often goes unexamined: that ge

arXiv:2508.17298v3 Announce Type: replace-cross Abstract: Compositional visual reasoning has emerged as a key research frontier in multimodal AI, aiming to endow machines with the human-like ability t

arXiv:2607.07452v1 Announce Type: new Abstract: Dense visual SLAM is a fundamental problem in robotics. Recent advances in 3DGS have demonstrated its potential for dense SLAM. Existing 3DGS frameworks

arXiv:2607.07318v1 Announce Type: new Abstract: Rigorous content moderation is crucial for online advertising but leads to millions of daily rejections. This scale renders manual rectification infeasi

arXiv:2607.07320v1 Announce Type: new Abstract: The SoccerNet 2026 Challenges constitute the sixth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision rese

arXiv:2607.07468v1 Announce Type: cross Abstract: We study the recovery of sparse functions from finite, noisy, and indirect observations in the framework of statistical inverse learning. The unknown

arXiv:2501.18784v5 Announce Type: replace Abstract: Heuristics are a central component of deterministic planning, particularly in domain-independent settings where general applicability is prioritized

arXiv:2607.07436v1 Announce Type: new Abstract: A self-evolving agent retires its bad skills by watching them fail, so what happens when the judge cannot see the failures? Skill retirement is the stru

arXiv:2607.07117v1 Announce Type: cross Abstract: In text-to-image in-context learning (T2I-ICL), a model has to infer a latent compositional pattern from fewshot demonstrations for generating a query

arXiv:2607.05590v1 Announce Type: cross Abstract: Implantable brain-computer interfaces require on-node spike sorting to reduce telemetry bandwidth and power while maintaining reliable neural decoding

arXiv:2607.06233v1 Announce Type: new Abstract: LLM-powered data agents are playing an increasingly important role in data-driven decision making. However, existing data agents struggle to generalize

arXiv:2607.05787v1 Announce Type: new Abstract: Synthesizing physically plausible human-scene interactions (HSI) remains a critical challenge in computer vision and the development of human avatars. A

arXiv:2603.19216v2 Announce Type: replace-cross Abstract: Understanding and generating 3D objects as compositions of meaningful parts is fundamental to human perception and reasoning. However, most te

arXiv:2607.05638v1 Announce Type: cross Abstract: Teams deploying large language models in business contexts need evaluation systems, yet most treat evaluation as static model selection: run benchmark

arXiv:2607.05573v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) and Vision-Language Models (VLMs) enable the automatic generation of parametric 3D designs from natural-

arXiv:2607.06553v1 Announce Type: new Abstract: Large-scale text-to-image models are attractive backbones for dense prediction because RGB generation pretraining learns rich semantic, structural, and

arXiv:2607.06162v1 Announce Type: new Abstract: Image outpainting extends an image beyond its original borders, requiring seamless style integration and globally coherent scene completion. Building on

arXiv:2607.05765v1 Announce Type: new Abstract: Embodied navigation aims to build agents that interpret multimodal goals, reason in 3D space, and reach target destinations reliably in the real world.