Search: “framework”

HiReFF: High-Resolution Feedforward Human Reconstruction from Uncalibrated Sparse-View Video

arXiv:2606.29333v1 Announce Type: new Abstract: Uncalibrated volumetric video streaming for human reconstruction is essential for holographic communication and AR/VR, yet remains challenging due to th

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HorizonRelight: Relighting Long-horizon Videos Consistently via Diffusion Transformers

DGX agent

arXiv:2606.29095v1 Announce Type: new Abstract: Diffusion-based video relighting enables controllable relighting from a single input video, but modern video diffusion backbones are trained on short cl

researcharxiv-cs-cv

30 Jun 2026

How Schrödinger sped up molecular discovery by 4x with Alphaevolve

model-releasesgoogle-cloud-ai

Computational chemistry researchers have traditionally faced a frustrating trade-off when simulating molecular interactions: use fast classical force fields that sacrifice precision or rely on accurat

How Should World Models Be Evaluated for Embodied Decision-Making? A Decision-Making-Centric Position

arXiv:2606.15032v2 Announce Type: replace Abstract: World models have become a central abstraction in modern AI. The term now refers to several different objects: action-conditioned environment models

safetyarxiv-cs-lg

HSD: Training-Free Acceleration for Document Parsing Vision-Language Models with Hierarchical Speculative Decoding

arXiv:2602.12957v3 Announce Type: replace Abstract: Document parsing is a fundamental task in multimodal understanding, supporting a wide range of downstream applications such as information extractio

HTC-SGA Former: A Hybrid Transformer-CNN Network with Self-Guided Attention and a New Boundary-Weighted Adaptive Loss for Coronary DSA Vessel Segmentation

arXiv:2606.29744v1 Announce Type: new Abstract: Accurate coronary Digital Subtraction Angiography (DSA) vessel segmentation is essential for computer-aided diagnosis and treatment planning of coronary

Human2Any: Human-to-Robot Transfer via Constraint-Aware Compositional Planning

arXiv:2606.28813v1 Announce Type: cross Abstract: Human videos are a scalable source of supervision for robot manipulation, as they are abundant and naturally capture rich object interactions. However

HyBIRD: Hyperbolic Bridge Retrieval and Diagnosis for Methodology Inspiration Retrieval

model-releasesarxiv-cs-ai

arXiv:2606.28336v1 Announce Type: cross Abstract: Methodology Inspiration Retrieval (MIR) asks a system to retrieve prior papers whose methods can inspire a new research proposal. Unlike general scien

Agents

Hybrid Retriever Evolution for Multimodal Document Reasoning Agents

arXiv:2606.29648v1 Announce Type: cross Abstract: Different retrievers, including lexical, semantic, and multimodal approaches, provide highly complementary strengths for multimodal document understan

agentsarxiv-cs-ai

Hyper-Network Neural Functional Maps for Unsupervised Robust 3D Shape Matching

arXiv:2606.30131v1 Announce Type: cross Abstract: Functional maps are the cornerstone of recent non-rigid 3D shape matching methods due to their efficiency and performance. However, existing methods s

IHDec: Divergence-Steered Contrastive Decoding for Securing Multi-Turn Instruction Hierarchies

arXiv:2606.29960v1 Announce Type: new Abstract: Large Language Models (LLMs) often fail to maintain instruction hierarchies (IH) when processing multi-source inputs with varying role-level priorities,

safetyarxiv-cs-cl

IMCBench: A benchmark for multimodal LLMs in Image-grounded Medical Conversations

model-releasesarxiv-cs-ai

arXiv:2606.28556v1 Announce Type: new Abstract: Recent advances in large language models and vision-language models have enabled reasoning over multimodal data, offering opportunities for clinical app

Insidious by Design: Implications of Large Language Model algorithmic bias for the Global South

model-releasesarxiv-cs-ai

arXiv:2606.28333v1 Announce Type: cross Abstract: egin{quote} The biases in Large Language Models' (LLMs) outputs remain inadequately theorised, particularly from the perspective of the Global South.

Interventional Flow Matching: Prospective Dose-Response Forecasting with Velocity-Field Jacobian Regularization

arXiv:2606.29386v1 Announce Type: new Abstract: Predicting a patient's physiological trajectory under a planned treatment sequence is a prospective interventional problem, not standard time-series ext

safetyarxiv-cs-lg

Invariant Reasoning Directions in Latent Trajectories of Language Models

arXiv:2606.29164v1 Announce Type: cross Abstract: Latent reasoning models perform multi-step inference directly in hidden-state space, yet the structure of these latent reasoning trajectories remains

JASPR: Joint Spatial Representation learning of histology and spatial genomics for improved virtual genomic screening and clinical prognostication

arXiv:2606.28395v1 Announce Type: new Abstract: Recent studies have shown that spatial properties of tumors are critical for understanding disease biology and predicting patient outcomes. These spatia

tutorialsarxiv-cs-cv

Joint 3D Gravity and Magnetic Inversion via Rectified Flow and Ginzburg-Landau Guidance

arXiv:2603.06829v2 Announce Type: replace Abstract: Subsurface ore detection is of paramount importance given the rising depletion of shallow mineral resources in recent years. It is crucial to explor

researcharxiv-cs-lg

JOPP-3D: Joint Open Vocabulary Semantic Segmentation on Point Clouds and Panoramas

arXiv:2603.06168v3 Announce Type: replace Abstract: Semantic segmentation across visual modalities such as 3D point clouds and panoramic images remains a challenging task, primarily due to the scarcit

Agents

KbSD: Knowledge Boundary aware Self-Distillation for Behavioral Calibration in Agentic Search

arXiv:2606.29863v1 Announce Type: new Abstract: Agentic search equips large language models with dynamic retrieval abilities, but existing reinforcement learning methods remain limited by reward spars

agentsarxiv-cs-cl

Knowing Bias, Doing Better: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement

arXiv:2601.21864v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit social biases that reinforce harmful stereotypes, limiting their safe deployment. Most existing debiasing metho

Kriging and neural network models for pressure losses across perforated plates

arXiv:2606.29628v1 Announce Type: cross Abstract: In this paper, two novel data-driven models based on kriging and neural networks (NN) are proposed to predict pressure losses across perforated plates

researcharxiv-cs-lg

KYON: Semi-Modular Wheel-Legged Quadruped With Agile Bimanual Capability

arXiv:2606.30243v1 Announce Type: new Abstract: This paper presents KYON, a hybrid wheel-legged quadruped robot equipped with a bimanual upper body for loco-manipulation tasks. The platform features a

safetyarxiv-cs-ro

L2D2-GS: Learning to Densify for Feedforward Dynamic Gaussian Scene Reconstruction

arXiv:2606.29374v1 Announce Type: new Abstract: High-fidelity reconstruction of dynamic urban environments is a cornerstone of autonomous driving simulation and large-scale world modeling. While 3D Ga

safetyarxiv-cs-cv

LaGen: Towards Autoregressive LiDAR Scene Generation

arXiv:2511.21256v2 Announce Type: replace Abstract: Generative world models for autonomous driving (AD) are of great value in applications such as data augmentation, closed-loop simulation, and safety

safetyarxiv-cs-cv

LAMP: Long-Horizon Adaptive Manipulation Planning for Multi-Robot Collaboration in Cluttered Space

arXiv:2606.29358v1 Announce Type: new Abstract: Multi-robot manipulation requires jointly reasoning about contact formations, robot motions under coupled dynamics, and collision avoidance. Systematica

tutorialsarxiv-cs-ro

Latent Actions from Factorized Transition Effects under Agent Ambiguity

arXiv:2606.30544v1 Announce Type: new Abstract: Latent Action Models (LAMs) learn action-like proxies from observation transitions. However, in multi-object or distractor-rich scenes, these visual eff

Latent Noise Mask for Reducing Visual Redundancy in Multimodal Large Language Models

arXiv:2606.30168v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) often fail in fine-grained visual reasoning, as question-relevant visual cues are diluted by dense and redundan

Learned Coordination Conventions in Cooperative MARL: Measuring the Translation Gap Between Theory-Informed Roles and Learned Routing

arXiv:2606.29541v1 Announce Type: new Abstract: Role-semantic assignments provide priors over how heterogeneous agents may coordinate, but cooperative MARL systems instead settle on conventions throug

Learned iterative networks: An operator learning perspective

arXiv:2512.08444v2 Announce Type: replace-cross Abstract: Learned image reconstruction has become a pillar in computational imaging and inverse problems. Among the most successful approaches are learn

tutorialsarxiv-cs-lg

Learning from Acquisition: Metadata-driven Multimodal Pre-training for Cardiac MRI

arXiv:2606.28991v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging (CMR) routinely records structured acquisition metadata, yet most CMR foundation models rely primarily on image-only

Learning from Mistakes: Rollout-Retrieval Lifelong Policy Learning for Autonomous Driving

arXiv:2606.30537v1 Announce Type: cross Abstract: Autonomous driving policies should be able to improve continually as deployment exposes them to increasingly diverse and long-tail traffic situations.

Learning How to Use Tools, Not Just When: Pattern-Aware Tool-Integrated Reasoning

arXiv:2509.23292v4 Announce Type: replace Abstract: Tool-integrated reasoning (TIR) has become a key approach for improving large reasoning models (LRMs) on complex problems. Prior work has mainly stu

tutorialsarxiv-cs-ai

Learning to Route and Schedule LLMs from User Retrials via Contextual Queueing Bandits

model-releasesarxiv-cs-lg

arXiv:2602.02061v2 Announce Type: replace Abstract: Explosive demands for LLMs often cause user queries to accumulate in server queues, requiring efficient routing (query-LLM matching) and scheduling

Learning Where and When: Patch-Based Spatiotemporal Localization in Weakly Supervised Video Anomaly Detection

arXiv:2606.29498v1 Announce Type: new Abstract: Weakly supervised video anomaly detection (WSVAD) has predominantly focused on temporal localization, identifying when anomalies occur while largely neg

local-aiarxiv-cs-cv

Lie Group Diffusion Models for Hardware-Aware Quantum Circuit Synthesis

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

local-aiarxiv-cs-lg

LLM-Ideoplasticity: Measuring Ideological Plasticity in the Political Behavior of LLMs as a Context-Conditioned Distribution

arXiv:2606.28335v1 Announce Type: cross Abstract: We argue, with systematic empirical evidence, that a large language model's political ideology is not a fixed point, but a conditional distribution P(

local-aiarxiv-cs-ai

LLMography: Transforming Human-AI Conversations into Traceability, Oversight, and Auditability Indicators

arXiv:2606.29437v1 Announce Type: cross Abstract: The growing use of Large Language Models (LLMs) in education, software engineering, academic writing, and technical documentation raises a key questio

LoGSAM: Parameter-Efficient Cross-Modal Grounding for MRI Segmentation

model-releasesarxiv-cs-cv

arXiv:2603.17576v3 Announce Type: replace Abstract: Precise localization and delineation of brain tumors using magnetic resonance imaging (MRI) are essential for planning therapy and guiding surgical

LoRAShield: Data-Free Editing Alignment for Secure Personalized LoRA Sharing

arXiv:2507.07056v2 Announce Type: replace-cross Abstract: The proliferation of Low-Rank Adaptation (LoRA) models has democratized personalized text-to-image generation, enabling users to share lightwe

safetyarxiv-cs-lg

Low-cost concept-based localized explanations: How far can we get with training-free approaches?

arXiv:2606.29069v1 Announce Type: new Abstract: Concept-based Explainable AI (C-XAI) seeks human-understandable explanations grounded in semantic concepts, yet validation is limited by the scarcity of

local-aiarxiv-cs-ai

M^3 QuestionIng: Multi-modal Multi-span Medical Question Answering

arXiv:2606.28329v1 Announce Type: cross Abstract: The growing adoption of AI in healthcare, particularly in preventive care, highlights the critical need for accessibility and precision in Medical Que

MALOQ: Massively Accelerated Learning of Operators for Quantum Transport

arXiv:2606.28911v1 Announce Type: new Abstract: Machine-learned (ML) operator models can be trained to predict density functional theory (DFT) Hamiltonian/density matrices at significantly reduced com

researcharxiv-cs-lg

Masked Diffusion Decoding as x-Prediction Flow

arXiv:2606.29066v1 Announce Type: new Abstract: Masked diffusion language models (MDLMs) generate text by iteratively unmasking tokens, but their standard decoder reduces each step to a binary action:

safetyarxiv-cs-cl

MATCH: Modulating Attention via In-Context Retrieval for Long-Context Transformers

arXiv:2606.29844v1 Announce Type: cross Abstract: The quadratic computational cost of traditional attention mechanisms poses a major bottleneck to the scalability and practical deployment of large lan

Agents

MAVIN: Multi-Shot Audio-Visual Generation with Narrative Control

arXiv:2606.29473v1 Announce Type: new Abstract: While recent generative models produce high-fidelity videos, they struggle with the complex narrative control required for coherent multi-shot audio-vis

agentsarxiv-cs-cv

McMg: A Learned Phase-Space Multi-channel Multigrid Preconditioner for Helmholtz Equation

arXiv:2606.30495v1 Announce Type: cross Abstract: Solving heterogeneous Helmholtz equations at high wavenumbers remains challenging because the discretized operator is indefinite, pollution degrades p

researcharxiv-cs-ai

MedEvoEval: Evaluating Continual Evolution of Doctor Agents through Simulated Clinical Episodes

arXiv:2606.28900v1 Announce Type: new Abstract: Doctor agents are moving beyond single-turn answer generation toward evolving clinical decision systems. Within an outpatient episode, they acquire evid

researcharxiv-cs-ai

MeEvo: Metacognitive Evolution Combined with Natural Evolution for Automatic Heuristic Design

arXiv:2606.14202v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have advanced Automatic Heuristic Design (AHD) by enabling heuristic generation through reasoning and code synthe

researcharxiv-cs-ai