Search: “framework”

Sample-efficient Transfer Reinforcement Learning via Adaptive Reward Shaping and Policy-Ratio Reweighting Strategy

arXiv:2606.26527v1 Announce Type: new Abstract: Transfer learning improves policy learning efficiency by reusing knowledge from source tasks, providing a feasible paradigm for safe and efficient auton

safetyarxiv-cs-lg

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Research

Sampling sea state using a diffusion model

DGX agent

arXiv:2606.26389v1 Announce Type: cross Abstract: Sea state prediction is essential for operational maritime applications and coupled earth system modeling, yet current spectral wave models remain com

researcharxiv-cs-ai

26 Jun 2026

Scaling Multi-Reference Image Generation with Dynamic Reward Optimization

arXiv:2606.26947v1 Announce Type: cross Abstract: While personalized image generation has achieved remarkable progress, multi-reference image generation (MRIG) remains a challenging task. Most existin

Local Ai

Scaling Nonlinear Optimization: Many Problems One GPU

arXiv:2606.26341v1 Announce Type: new Abstract: Many robotics problems, including trajectory optimization, inverse kinematics, and contact-rich motion planning, reduce to nonlinear programs (NLPs). Ma

local-aiarxiv-cs-ro

SciFig: Towards Automating Editable Figure Generation for Scientific Papers

arXiv:2601.04390v2 Announce Type: replace Abstract: High-quality methodology figures are central to scientific communication, yet they remain difficult and time-consuming to create. Such figures must

See & Sniff: Learning Visuo-Olfactory Representations

arXiv:2606.27307v1 Announce Type: new Abstract: While modern multimodal models integrate vision with language, audio, or touch, olfaction remains largely unexplored due to the lack of paired visuo-olf

ShareLock: A Stealthy Multi-Tool Threshold Poisoning Attack Against MCP

arXiv:2606.27027v1 Announce Type: cross Abstract: With the rapid evolution of LLM-driven agents, Model Context Protocol (MCP), an open protocol bridging LLMs with external tools, has quickly become fo

Simulation-based inference for rapid Bayesian parameter estimation in epidemiological models: a comparison with MCMC

arXiv:2606.27286v1 Announce Type: new Abstract: Mechanistic epidemiological models are widely used to support infectious disease forecasting and public-health decision making. Bayesian calibration of

SKILL-DISCO: Distilling and Compiling Agent Traces into Reusable Procedural Skills

arXiv:2606.26669v1 Announce Type: new Abstract: Agents often repeatedly solve similar task instances from scratch, leading to unnecessary reasoning cost and long execution traces. Prior work has explo

agentsarxiv-cs-ai

SOLAR: AI-Powered Speed-of-Light Performance Analysis

arXiv:2606.26383v1 Announce Type: cross Abstract: How fast could a deep-learning model run on target hardware, and how far is today's implementation from that limit? These questions are central to sof

SpaceRipple: Lightweight Semantic Delivery for Mission-Oriented LEO Earth Observation Satellite Networks

arXiv:2606.26559v1 Announce Type: cross Abstract: Earth observation satellite networks generate massive volumes of high-resolution imagery, whereas inter-satellite and downlink resources remain limite

SSI-Policy: Learning Structured Scene Interfaces for Vision-Language Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.26800v1 Announce Type: new Abstract: Real-world robotic manipulation demands spatial grounding, task-aware reasoning, and precise control. Learning such capabilities becomes particularly ch

Staying VIGILant: Mitigating Visual Laziness via Counterfactual Visual Alignment in MLLMs

arXiv:2606.26387v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) extend large language models (LLMs) with visual perception, enabling joint reasoning over images and text. De

safetyarxiv-cs-cl

Stochastic Gradient Optimization with Model-Assisted Sampling

model-releasesarxiv-cs-lg

arXiv:2606.27171v1 Announce Type: new Abstract: This work addresses the problem of variance in stochastic gradient estimation for machine learning optimization. Deep learning relies on mini-batch meth

SubdivAR: Autoregressive Next-Scale Prediction for Neural Mesh Subdivision

arXiv:2606.27088v1 Announce Type: new Abstract: Mesh subdivision is a fundamental operation for converting coarse, editable meshes into high-resolution surfaces, with broad applications in digital ass

Applications

Target-Aware Bandit Allocation for Scalable Surrogate Optimization in Chemical Space

arXiv:2606.26657v1 Announce Type: new Abstract: Identifying high-utility candidates from massive discrete spaces under expensive evaluations is a recurring challenge across the sciences, with structur

applicationsarxiv-cs-lg

TaskTok: Delving into Task Tokens for Task-driven Image Restoration

arXiv:2606.26615v1 Announce Type: new Abstract: While traditional image restoration focuses on perceptual quality, Task-Driven Image Restoration (TDIR) aims to maximize the performance of downstream h

TAVR-VLM: Risk-Conditioned Causal Grounding for Hallucination-Resistant Report Generation

arXiv:2606.26874v1 Announce Type: new Abstract: Transcatheter Aortic Valve Replacement (TAVR) planning requires meticulous multimodal reasoning. However, adapting Multimodal Large Language Models (MLL

TEMPO-Diffusion: Temporally Exposed Malicious Poisoning of Diffusion Models

arXiv:2606.26285v1 Announce Type: cross Abstract: Noise-based backdoor attacks on diffusion models typically rely on input-time trigger injection, untargeted activation, and out-of-distribution target

Term-Centric Hierarchy Induction from Heterogeneous Corpora

model-releasesarxiv-cs-cl

arXiv:2606.26963v1 Announce Type: new Abstract: Organizing knowledge from diverse text sources into interpretable hierarchies is crucial for tasks such as policy analysis, innovation monitoring, and e

Local Ai

TGHE: Template-based Graph Homomorphic Encryption for Privacy-Preserving GNN Inference in Edge-Cloud Systems

arXiv:2606.26664v1 Announce Type: cross Abstract: Existing homomorphic encryption (HE)-based GNN systems adopt a graph-centric paradigm that couples per-query cost to global graph size, limiting evalu

local-aiarxiv-cs-ai

The Red Queen Godel Machine: Co-Evolving Agents and Their Evaluators

arXiv:2606.26294v1 Announce Type: cross Abstract: Self-improving agents are state-of-the-art (SOTA) on agentic coding benchmarks and have recently been extended to general domains. However, their sear

The Role of Input Dimensionality in the Emergence and Targeted Control of Adversarial Examples

arXiv:2606.26207v1 Announce Type: cross Abstract: Several theoretical works have tried to explain the adversarial vulnerability of deep neural networks through properties of high-dimensional geometry.

researcharxiv-cs-lg

Topology-Informed Neural Networks for Flood Detection in Optical and Synthetic Aperture Radar Imagery

arXiv:2606.26204v1 Announce Type: new Abstract: Floods frequently impact regions around the world. Rapid and accurate flood detection is crucial for emergency response and timely mitigation of human a

safetyarxiv-cs-lg

Towards Consistent and Efficient Dataset Distillation via Diffusion-Driven Selection

arXiv:2412.09959v5 Announce Type: replace Abstract: Dataset distillation provides an effective approach to reduce memory and computational costs by optimizing a compact dataset that achieves performan

Towards Video Anomaly Detection from Event Streams: A Baseline and Benchmark Datasets

arXiv:2603.24991v2 Announce Type: replace Abstract: Event-based vision, characterized by low redundancy, focus on dynamic motion, and inherent privacy-preserving properties, naturally fits the demands

Tractography-Driven Synthetic Data Generation for Fiber Bundle Segmentation in Tracer Histology

arXiv:2606.26898v1 Announce Type: new Abstract: Diffusion MRI (dMRI) tractography enables non-invasive reconstruction of white-matter pathways, but its accuracy is fundamentally limited by indirect, l

Transformer-Based Classification of Bacterial Raman Spectra with LOOCV

arXiv:2606.27096v1 Announce Type: new Abstract: Transformer-based models have recently attracted increasing attention for Raman spectral classification. In this study, a transformer-based approach was

researcharxiv-cs-lg

Tuning Language Models by Mixture-of-Depths Ensemble

arXiv:2410.13077v2 Announce Type: replace-cross Abstract: Transformer-based Large Language Models (LLMs) traditionally rely on final-layer loss for finetuning and final-layer representations for predi

Understanding Domain-Aware Distribution Alignment in Budgeted Entity Matching

arXiv:2606.27342v1 Announce Type: cross Abstract: Entity Matching (EM) is a core operation in the data integration pipeline, where records from different sources are compared to determine whether they

safetyarxiv-cs-ai

VibeAct: Vibration to Actions for Contact-Rich Reactive Robot Dexterity

arXiv:2606.27344v1 Announce Type: new Abstract: Dexterous manipulation depends on contact events that are fast, local, and often visually occluded. Piezoelectric microphones offer a compact and high-b

safetyarxiv-cs-ro

ViQ: Text-Aligned Visual Quantized Representations at Any Resolution

arXiv:2606.27313v1 Announce Type: new Abstract: A unified representation for text and vision is a natural pursuit, as it enables simpler multimodal modeling and more efficient training. However, repre

VisNec: Measuring and Leveraging Visual Necessity for Multimodal Instruction Tuning

arXiv:2603.01195v2 Announce Type: replace-cross Abstract: The effectiveness of multimodal instruction tuning depends not only on dataset scale, but critically on whether training samples genuinely req

Where Larger Models Excel: The Primacy of Constraint-Guided Reasoning

arXiv:2606.26108v1 Announce Type: new Abstract: Larger language models consistently outperform smaller ones on reasoning benchmarks, yet the reasoning differences underlying this gap remain underexplo

researcharxiv-cs-cl

World Action Models Enable Continual Imitation Learning with Recurrent Generative Replays

arXiv:2606.27374v1 Announce Type: cross Abstract: Going beyond predicting robot actions, World Action Models (WAMs) can also generate future visual observations. We build on this generative capability

safetyarxiv-cs-cv

2K Retrofit: Entropy-Guided Efficient Sparse Refinement for High-Resolution 3D Geometry Prediction

arXiv:2603.19964v3 Announce Type: replace Abstract: High-resolution geometric prediction is essential for robust perception in autonomous driving, robotics, and AR/MR, but current foundation models ar

A Benchmark for Heterogeneous Stereo Deblurring with Physically- and Epipolar-constrained Cross Attention

arXiv:2606.25962v1 Announce Type: new Abstract: Modern stereo-capable smartphones enable immersive XR content capture. However, hardware heterogeneity across camera modules often causes severe asymmet

A cross-process welding penetration status prediction algorithm based on unsupervised domain adaptation in laser and TIG welding

arXiv:2606.26078v1 Announce Type: new Abstract: Supervised deep learning has been widely used for weld penetration state classification; however, its performance often degrades significantly under dom

A welding penetration prediction model for laser welding process based on self-supervised learning using physics-informed neural networks

arXiv:2606.26059v1 Announce Type: new Abstract: The laser welding full-penetration is of critical importance, as it constitutes one of the fundamental factors in achieving defect-free welded joints. A

Tutorials

Adapt Only When It Pays: Budgeted Decision-Loss Priority for Delayed Online Time-Series Adaptation

arXiv:2606.25068v1 Announce Type: new Abstract: Online time-series forecasters receive labels only after horizon-dependent delays, while every adaptation step spends limited compute. We study when an

tutorialsarxiv-cs-lg

Adaptive Joint Compression and Synchronisation in Federated Split Learning for IoT Rainfall Prediction

arXiv:2606.25003v1 Announce Type: new Abstract: Federated split learning (FSL) enables collaborative training across bandwidth-constrained IoT devices, but repeated activation and gradient exchange cr

safetyarxiv-cs-lg

Applications

ADM-Fusion: Adaptive Deep Multi-Sensor Fusion for Robust Ego-Motion Estimation in Diverse Conditions

arXiv:2606.25111v1 Announce Type: cross Abstract: Robust multi-sensor fusion is essential for reliable autonomy in diverse and degraded environments, where sensor reliability can fluctuate rapidly. Be

applicationsarxiv-cs-cv

AeroCast: Probabilistic 3D Trajectory Prediction for Non-Cooperative Aerial Obstacles via Transformer-MDN Architecture

arXiv:2606.25122v1 Announce Type: cross Abstract: Autonomous aerial vehicles operating in shared airspace must predict the future positions of non-cooperative obstacles to plan evasive maneuvers befor

agentsarxiv-cs-lg

Agentic evolution of physically constrained foundation models

model-releasesarxiv-cs-lg

arXiv:2606.25532v1 Announce Type: cross Abstract: Artificial intelligence increasingly drives automated scientific discovery, yet contemporary generalist agents lack physical grounding, frequently hal

Agentic Knowledge Tracing: A Multi-Agent LLM Architecture for Stealth Assessment of Financial Literacy in Serious Games

arXiv:2606.25358v1 Announce Type: new Abstract: Assessing financial literacy during gameplay without disrupting the learning experience remains a key challenge in serious games for education. We prese

agentsarxiv-cs-ai

AgentOdyssey: Open-Ended Long-Horizon Text Game Generation for Test-Time Continual Learning Agents

arXiv:2606.24893v1 Announce Type: new Abstract: For agents to learn continuously from interaction with the world at test time, they must be able to explore effectively, acquire new world knowledge and

agentsarxiv-cs-cl

Applications

Agents are easy to demo locally. The hard part is shipping them inside a real app. We published a deployment cookbook for @LangChain agents:…

applicationsharrison-chase--x

Agents are easy to demo locally. The hard part is shipping them inside a real app. We published a deployment cookbook for @LangChain agents: full-stack examples with streaming UI, subagents, thread hi

AI Coaching for Accelerating Human Skill Development with Reinforcement Learning

arXiv:2606.25337v1 Announce Type: new Abstract: AI copilots can substantially boost human performance through shared control, but excessive assistance can induce over-reliance and skill atrophy. This

agentsarxiv-cs-ro