Search: “synthesis”

BrainTRACE: Tracing Longitudinal, Multimodal, and Volumetric Evidence in Brain MRI Clinical Reasoning

arXiv:2610.06571v1 Announce Type: new Abstract: Brain MRI interpretation is a longitudinal clinical reasoning problem: radiologists compare serial studies, integrate information across MRI sequences,

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

CodeForge-MA: Execution-Verified Multi-Agent Learning with Language-Conditioned LoRA for Multilingual Code Generation

DGX agent

arXiv:2610.05481v1 Announce Type: cross Abstract: Large language models for code generation often fail on execution, multilingual coverage, and contamination control, especially under frozen backbone

model-releasesarxiv-cs-lg

6 Oct 2026

Controllable and Photorealistic Pedestrian Risky Motion Generation for End-to-End Driving Safety Evaluation

model-releasesarxiv-cs-ro

arXiv:2610.06171v1 Announce Type: new Abstract: Evaluating end-to-end autonomous driving under rare, safety-critical vehicle-pedestrian interactions requires photorealistic, sensor-level scenarios. Ho

Controllable Road Marking Generation

arXiv:2610.05771v1 Announce Type: new Abstract: Lane and road markings provide critical guidance for vehicle navigation and multi-agent coordination, yet authoring them at scale remains a manual workf

EduAlign: Aligning Educational LLMs for Helpfulness, Personalization, and Creativity

arXiv:2507.20335v2 Announce Type: replace Abstract: Educational language models should pursue three complementary objectives: helpfulness through responsible guidance, personalization to learner needs

safetyarxiv-cs-lg

Empirical Variational Autoencoder

arXiv:2610.06545v1 Announce Type: new Abstract: We present Empirical Variational Autoencoder, a general generative framework for continuous-valued (i.e., non-vector-quantized) sequences. EVA is based

Event-based Continuous Color Video Decompression from Single Frames

arXiv:2312.00113v4 Announce Type: replace Abstract: We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional ca

FoleyGenEx: Unified Video-to-Audio Generation with Multi-Modal Control, Temporal Alignment, and Semantic Precision

arXiv:2606.14049v2 Announce Type: replace-cross Abstract: We present FoleyGenEx, a unified video-to-audio (VTA) framework integrating multi-modal control, frame-level temporal alignment, and fine-grai

Tutorials

From Pixels, Without Pre-training: Joint Generative and Self-Supervised Representation Learning in One Model

arXiv:2610.05711v1 Announce Type: cross Abstract: Strong image generation models are conditioned on class labels, aligned to frozen pretrained encoders, or built on separately trained autoencoders. Wh

tutorialsarxiv-cs-cv

GitSwarm: Decentralized Compounding Inference

model-releasesarxiv-cs-lg

arXiv:2610.04862v1 Announce Type: cross Abstract: Long-horizon problem solving and scientific research require computation to accumulate across successive attempts. Partial solutions, experimental fin

How Does Geometry Enter Generated Motion?

arXiv:2610.05135v1 Announce Type: new Abstract: Under a fixed physical law, the visible geometry of a scene determines how motion must change. We ask how video generators realize this relationship. We

Tutorials

Learning Subject-Specific Anatomical Representations via Manifold Expansion: Application to Accelerated Multi-Contrast MRI

arXiv:2610.04028v1 Announce Type: new Abstract: Clinical MRI routinely acquires multiple contrast-weighted images of the same anatomy for complementary tissue characterization. However, current accele

tutorialsarxiv-cs-cv

Paradee: Distilling Kokoro-82M into an 8M-Parameter Single-Voice Text-to-Speech Model

model-releasesarxiv-cs-lg

arXiv:2610.06817v1 Announce Type: cross Abstract: We distill Kokoro-82M, a widely used open text-to-speech model with 54 voices, into Paradee, an 8.07M-parameter model that speaks one of them. Paradee

RISED: Rubrics for Agentic Multi-Environment Selection and Self-Distillation

Training a single LLM agent jointly across diverse interactive environments has attracted increasing attention as a route to generalist agents. Existing curriculum and data-selection strategies often

agentsapple-ml-research

SPIN: Image Immunization Against Diffusion Editing via Single-Step Projection in Stochastic Neighborhoods

arXiv:2610.06334v1 Announce Type: new Abstract: Diffusion models have greatly advanced instruction-guided image editing, while also raising concerns about unauthorized image manipulation. Image immuni

SteadySplats: Resampling of Low-Variance Gaussians for High-Fidelity Stochastic Rendering

arXiv:2610.05576v1 Announce Type: new Abstract: Stochastic order-independent transparency enables efficient and elegant rendering of primitive-based radiance fields like 3D Gaussian Splatting models,

StepCAD: Mesh-to-CAD Code Generation via LLM Policy and Geometry-Guided Search

arXiv:2610.03799v1 Announce Type: new Abstract: Recovering executable CAD programs from 3D meshes is challenging due to the compositional nature of CAD construction and the interaction between discret

Universal Test-Time Training

arXiv:2610.05484v1 Announce Type: cross Abstract: Recent Test-Time Training (TTT) architectures compress context into fast weights that are updated online and queried as memory. Existing TTT designs k

VCURF: Virtual Camera-based Uncertainty of Radiance Fields

arXiv:2610.04076v1 Announce Type: new Abstract: Radiance fields, implemented with either implicit (NeRF) or explicit (Gaussian Splatting) representations, are advancing the state of the art in novel v

Visual Swarm Navigation via Deep Reinforcement Learning and Evolutionary Hybrid Design

arXiv:2610.06400v1 Announce Type: new Abstract: Swarm robotics presents a robust and cost-effective paradigm for advanced automation in complex, dynamic environments, such as those encountered in sear

safetyarxiv-cs-ro

Asterism: Exploring and Synthesizing Scattered Observations into Literature-Grounded Hypotheses and Theories

arXiv:2610.02673v1 Announce Type: cross Abstract: A theory draws many independent observations into one framework with novel hypotheses. A researcher building such a theory must synthesize observation

researcharxiv-cs-cl

Awomo-SimDataEngine: Agentic Simulation-ReadyWorld Generation

arXiv:2610.02274v1 Announce Type: new Abstract: Generating useful robot-training data requires more than visually plausiblescenes: objects must support interaction, placements must remain physicallyva

safetyarxiv-cs-ro

Can AI Understand the Language of Origami?

arXiv:2603.13856v3 Announce Type: replace-cross Abstract: Building AI systems that can plan, act, and create in the physical world requires more than pattern recognition. Such systems must reason abou

Closing the Train-Test Gap in World Models for Gradient-Based Planning

arXiv:2512.09929v2 Announce Type: replace Abstract: World models paired with model predictive control (MPC) can be trained offline on large-scale datasets of expert trajectories and enable generalizat

Contextual Flow Matching: Adaptive Step Selection in Flow Models for Efficient Visual Generation

arXiv:2610.03202v1 Announce Type: cross Abstract: Flow Matching enables high-quality visual generation via continuous-time dynamics, but inference remains costly due to multiple sequential function ev

Coupled reaction and diffusion governing interface evolution in solid-state batteries

arXiv:2506.10944v2 Announce Type: replace-cross Abstract: Understanding and controlling the atomistic-level reactions governing the formation of the solid-electrolyte interphase (SEI) is crucial for t

CriticHack: Evaluating Visual Rewards Under Robot Policy Optimization

model-releasesarxiv-cs-ai

arXiv:2610.02527v1 Announce Type: cross Abstract: Learned visual reward models are increasingly used to optimize robot policies, yet a reward model can score an execution that acts on the wrong object

DriftTTS: Few-Step Text-to-Speech Without Distillation via Distribution-Matching Drift

arXiv:2610.03390v1 Announce Type: cross Abstract: Few-step neural text-to-speech models often rely on short- ened diffusion or flow-matching schedules, or on distillation from pretrained multi-step te

safetyarxiv-cs-ai

Exact Memory-Time Optimization for Prefix-Cached Language Model Serving

model-releasesarxiv-cs-lg

arXiv:2610.02766v1 Announce Type: new Abstract: Retaining language-model prefix states trades recomputation against storage time. Optimizing each cached block independently can overcount savings: a re

Local Ai

On-Board Anomaly Detection for Efficient Marine Environmental Monitoring

arXiv:2610.03649v1 Announce Type: cross Abstract: Marine ecosystems are impacted by various threats such as oil spills, algal blooms, and sediment floods, which disrupt habitats, wildlife, and human a

local-aiarxiv-cs-ai

Refinement Buys Intelligibility, Search Buys Identity: What Test-Time Compute Buys in Masked-Diffusion TTS

arXiv:2610.03320v1 Announce Type: new Abstract: Diffusion language models for text-to-speech combine two forms of computation: model depth (parameters) and refinement steps (inference budget). We ask

Structural-Functional Brain Connectivity Generation via Multimodal Hypergraph-based Flow Matching

arXiv:2610.02722v1 Announce Type: new Abstract: Structural connectivity (SC) and functional connectivity (FC) provide complementary information on interactions between brain regions and are widely use

Where Quantum Fourier Sampling Stops Short: A Three-Gate Audit Protocol for Delay-PUF Security Models

arXiv:2610.02636v1 Announce Type: cross Abstract: Quantum Fourier sampling may help audit the spectral learnability of delay-based physical unclonable functions (PUFs). We ask whether that promise sur

safetyarxiv-cs-lg

A Comprehensive Review of One-Pixel Attack: Research Status, Taxonomy, Applications, Regulation Policy and Future Directions

arXiv:2610.00125v1 Announce Type: cross Abstract: One-Pixel Attacks (OPAs) represent one of the most extreme demonstrations of adversarial fragility in deep learning, where modifying a single pixel ca

Applications

Causal-Aware Tabular GANs with Reinforcement Learning

arXiv:2510.24046v2 Announce Type: replace-cross Abstract: Existing tabular data generation methods primarily focus on matching statistical distributions between real and synthetic data, often overlook

applicationsarxiv-cs-ai

Code That Works, Environments That Don't: Measuring Environment Reproducibility in AI-Generated Software

arXiv:2610.00425v1 Announce Type: cross Abstract: Code generation has emerged as a central capability of large language models, with coding agents now able to produce functionally correct software pro

agentsarxiv-cs-ai

DMAD: Distribution Matching as Adversarial Distillation for Fast Visual Generation

arXiv:2610.02188v1 Announce Type: cross Abstract: Distribution Matching Distillation (DMD) trains a few-step student from the difference between separately estimated target and student scores, so it m

DramaAgent: Agentic Storytelling Video Generation

arXiv:2610.00097v1 Announce Type: new Abstract: Recent diffusion and autoregressive models have substantially improved text-to-video generation, yet producing coherent long-form story videos with cons

agentsarxiv-cs-cv

EgoForge: Goal-Directed Egocentric World Simulator

arXiv:2603.20169v2 Announce Type: replace Abstract: Generative world models have shown promise for simulating dynamic environments, yet egocentric video remains challenging due to rapid viewpoint chan

End-to-End Learning vs. Modular Architectures: Comparative Insights into Autonomous Driving Systems

arXiv:2610.01746v1 Announce Type: cross Abstract: Autonomous driving systems have become a central focus of intelligent transportation research, with End-to-End Learning and Modular Architectures offe

Applications

Faithful Chart Generation for Multimodal Deep Research: Frame-Evidence Co-Adaptation

arXiv:2610.00374v1 Announce Type: cross Abstract: Analytical charts in multimodal deep research encode quantitative claims, requiring every visualized value to be faithfully grounded in supporting evi

applicationsarxiv-cs-ai

LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios

arXiv:2508.17692v2 Announce Type: replace Abstract: Recent advances in LLM-based agents highlight the importance of their reasoning frameworks, which guide the problem-solving process in diverse ways.

agentsarxiv-cs-ai

Memetic Trojans: Social Contagions as Carriers of Adversarial Payloads in Agent Networks

arXiv:2610.00430v1 Announce Type: cross Abstract: Autonomous large language model (LLM) agents increasingly interact in network environments where adversarial content can propagate between agents. Kno

agentsarxiv-cs-ai

Local Ai

OneStreamer: Unifying Perception, Memory, and Proactive Response in Streaming Video Interaction

arXiv:2610.01762v1 Announce Type: new Abstract: Streaming video LLMs must retain evidence before its relevance to future tasks is known and respond when sufficient evidence becomes available. The chal

local-aiarxiv-cs-cv

Real-time Appearance-based Gaze Estimation for Open Domains

arXiv:2603.26945v2 Announce Type: replace Abstract: Appearance-based gaze estimation (AGE) has achieved remarkable performance in constrained settings, yet we reveal a significant generalization gap w

Rethinking Data Augmentation under Covariate Shift: Invariant-Guided Diffusion and Prototype Reweighting

arXiv:2610.00873v1 Announce Type: cross Abstract: In many industrial applications, 1) tabular data is scarce and imbalanced and thus requires synthetic expansion; 2) input distributions drift between

SETA got accepted to NeurIPS 2026! 🎉 We released the full training scripts for DeepSeek-V4-Flash, GLM-5.2 (LoRA), Inkling-Small, and Qwen3.…

model-releasesclem-delangue--x

SETA got accepted to NeurIPS 2026! 🎉 We released the full training scripts for DeepSeek-V4-Flash, GLM-5.2 (LoRA), Inkling-Small, and Qwen3.8-27B, with both GRPO and PPO, alongside 4,500+ open-source,

Signal-Noise Factorization Isolates Nuisance Variation into Removable Subspaces

arXiv:2610.00751v1 Announce Type: cross Abstract: Recent theoretical work identified fundamental properties of representation geometry that shape inference ability of deep neural networks. These inclu