Search: “framework”

Delta Forcing: Trust Region Steering for Interactive Autoregressive Video Generation

arXiv:2605.14382v1 Announce Type: new Abstract: Interactive real-time autoregressive video generation is essential for applications such as content creation and world modeling, where visual content mu

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Denoising-GS: Gaussian Splatting with Spatial-aware Denoising

DGX agent

arXiv:2605.14880v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have achieved remarkable success in high-fidelity Novel View Synthesis (NVS), yet the optimization proce

model-releasesarxiv-cs-cv

15 May 2026

Derivation Prompting: A Logic-Based Method for Improving Retrieval-Augmented Generation

arXiv:2605.14053v1 Announce Type: cross Abstract: The application of Large Language Models to Question Answering has shown great promise, but important challenges such as hallucinations and erroneous

Agents

DermAgent: A Self-Reflective Agentic System for Dermatological Image Analysis with Multi-Tool Reasoning and Traceable Decision-Making

arXiv:2605.14403v1 Announce Type: new Abstract: Dermatological diagnosis requires integrating fine-grained visual perception with expert clinical knowledge. Although Multimodal Large Language Models (

agentsarxiv-cs-cv

Hardware

DiffPhD: A Unified Differentiable Solver for Projective Heterogeneous Materials in Elastodynamics with Contact-Rich GPU-Acceleration

arXiv:2605.14526v1 Announce Type: cross Abstract: Differentiable simulation of soft bodies is a foundation for system identification, trajectory optimization, and Real2Sim transfer. Yet, existing meth

hardwarearxiv-cs-ro

DiffusionOPD: A Unified Perspective of On-Policy Distillation in Diffusion Models

arXiv:2605.15055v1 Announce Type: cross Abstract: Reinforcement learning has emerged as a powerful tool for improving diffusion-based text-to-image models, but existing methods are largely limited to

Distribution-Aware Algorithm Design with LLM Agents

arXiv:2605.14141v1 Announce Type: new Abstract: We study learning when the learned object is executable solver code rather than a predictor. In this setting, correctness is not enough: two solvers may

Distribution Corrected Offline Data Distillation for Large Language Models

arXiv:2605.14071v1 Announce Type: new Abstract: Distilling reasoning traces from strong large language models into smaller ones is a promising route to improve intelligence in resource-constrained set

safetyarxiv-cs-cl

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving

arXiv:2507.04049v4 Announce Type: replace Abstract: Most end-to-end autonomous driving methods rely on imitation learning from single expert demonstrations, often leading to conservative and homogeneo

Do Language Models Align with Brains? Prediction Scores Are Not Enough

arXiv:2605.14025v1 Announce Type: cross Abstract: Brain-language model comparisons often interpret neural prediction scores as evidence that model representations capture brain-relevant language compu

Do We Really Need External Tools to Mitigate Hallucinations? SIRA: Shared-Prefix Internal Reconstruction of Attribution

arXiv:2605.14621v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) often hallucinate when language priors dominate weak or ambiguous visual evidence. Existing contrastive decoding

Does Synthetic Layered Design Data Benefit Layered Design Decomposition?

arXiv:2605.15167v1 Announce Type: new Abstract: Recent advances in image generation have made it easy to produce high-quality images. However, these outputs are inherently flattened, entangling foregr

applicationsarxiv-cs-cv

Agents

DriveCtrl: Conditioned Sim-to-Real Driving Video Generation

arXiv:2605.15116v1 Announce Type: new Abstract: Large-scale labelled driving video data is essential for training autonomous driving systems. Although simulation offers scalable and fully annotated da

agentsarxiv-cs-cv

Dual-Dimensional Consistency: Balancing Budget and Quality in Adaptive Inference-Time Scaling

arXiv:2605.15100v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable abilities in reasoning. However, maximizing their potential through inference-time scaling fac

Dual Hierarchical Dialogue Policy Learning for Legal Inquisitive Conversational Agents

arXiv:2605.14057v1 Announce Type: new Abstract: Most existing dialogue systems are user-driven, primarily designed to fulfill user requests. However, in many critical real-world scenarios, a conversat

safetyarxiv-cs-cl

DUET: Dual-Paradigm Adaptive Expert Triage with Single-cell Inductive Prior for Spatial Transcriptomics Prediction

arXiv:2605.14104v1 Announce Type: new Abstract: Inferring spatially resolved gene expression from histology images offers a cost-effective complement to spatial transcriptomics (ST). However, existing

researcharxiv-cs-cv

Dynamic Mixed-Precision Routing for Efficient Multi-step LLM Interaction

arXiv:2602.02711v2 Announce Type: replace Abstract: Large language models (LLMs) achieve strong performance in long-horizon decision-making tasks through multi-step interaction and reasoning at test t

Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signal

arXiv:2605.14014v1 Announce Type: cross Abstract: Internet of Things (IoT) systems continuously collect heterogeneous sensing signals from ubiquitous sensors to support intelligent applications such a

applicationsarxiv-cs-ai

Efficient Generative Retrieval for E-commerce Search with Semantic Cluster IDs and Expert-Guided RL

arXiv:2605.14434v1 Announce Type: cross Abstract: Generative retrieval offers a promising alternative by unifying the fragmented multi-stage retrieval process into a single end-to-end model. However,

Efficient Online Conformal Selection with Limited Feedback

model-releasesarxiv-cs-lg

arXiv:2605.14953v1 Announce Type: new Abstract: We address the problem of conformal selection, where an agent must select a minimal subset of options to ensure that at least one ``success'' is identif

Enhancing Few-Shot Classification of Benchmark and Disaster Imagery with ABHFA-Net

model-releasesarxiv-cs-cv

arXiv:2510.18326v3 Announce Type: replace Abstract: The rising incidence of natural and human-induced disasters necessitates robust visual recognition systems capable of operating under limited labele

Enjoy Your Layer Normalization with the Computational Efficiency of RMSNorm

arXiv:2605.14521v1 Announce Type: new Abstract: Layer normalization (LN) is a fundamental component in modern deep learning, but its per-sample centering and scaling introduce non-negligible inference

researcharxiv-cs-lg

Ergodic Imitation for Adaptive Exploration around Demonstrations

arXiv:2605.13996v1 Announce Type: new Abstract: In robotics, a common challenge in imitation learning is the mismatch between training and deployment conditions, caused, for example, by environmental

Local Ai

EVA: Editing for Versatile Alignment against Jailbreaks

arXiv:2605.14750v1 Announce Type: cross Abstract: Large Language Models (LLMs) and Vision Language Models (VLMs) have demonstrated impressive capabilities but remain vulnerable to jailbreaking attacks

local-aiarxiv-cs-ai

Evidential Reasoning Advances Interpretable Real-World Disease Screening

arXiv:2605.15171v1 Announce Type: cross Abstract: Disease screening is critical for early detection and timely intervention in clinical practice. However, most current screening models for medical ima

applicationsarxiv-cs-ai

Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model

arXiv:2605.14950v1 Announce Type: new Abstract: Vision-Language-Action models have emerged as a promising paradigm for robotic manipulation by unifying perception, language grounding, and action gener

Evolving Layer-Specific Scalar Functions for Hardware-Aware Transformer Adaptation

arXiv:2605.14047v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve state-of-the-art performance on challenging vision tasks, but their deployment on edge devices is severely hindered b

Exploring Bottlenecks in VLM-LLM Navigation: How 3D Scene Understanding Capability Impacts Zero-Shot VLN

arXiv:2605.14801v1 Announce Type: new Abstract: Zero-shot vision-and-language navigation (VLN) has gained significant attention due to its minimal data collection costs and inherent generalization. Th

FaceParts: Segmentation and Editing of Gaussian Splatting

arXiv:2605.13853v1 Announce Type: cross Abstract: Facial editing is an important task with applications in entertainment, virtual reality, and digital avatars. Most existing approaches rely on generat

Fair and Calibrated Toxicity Detection with Robust Training and Abstention

arXiv:2605.14074v1 Announce Type: new Abstract: Fairness in toxicity classification involves three integrated axes: ranking, calibration, and abstention. Training-time interventions and post-hoc safet

safetyarxiv-cs-lg

Hardware

Falkor-IRAC: Graph-Constrained Generation for Verified Legal Reasoning in Indian Judicial AI

arXiv:2605.14665v1 Announce Type: new Abstract: Legal reasoning is not semantic similarity search. A court judgment encodes constrained symbolic reasoning: precedent propagation, procedural state tran

hardwarearxiv-cs-ai

FedStain: Modeling Higher-Order Stain Statistics for Federated Domain Generalization in Computational Pathology

model-releasesarxiv-cs-cv

arXiv:2605.14590v1 Announce Type: new Abstract: Robust whole-slide image (WSI) analysis under strict data-governance remains challenging due to substantial cross-institutional stain heterogeneity. Dom

FlowInOne:Unifying Multimodal Generation as Image-in, Image-out Flow Matching

model-releasesarxiv-cs-cv

arXiv:2604.06757v2 Announce Type: replace Abstract: Multimodal generation has long been dominated by text-driven pipelines where language dictates vision but cannot reason or create within it. We chal

FlowSteer: Towards Agents Designing Agentic Workflows via Reinforced Progressive Canvas Editing

arXiv:2602.01664v4 Announce Type: replace Abstract: In recent years, agentic workflows have been widely applied to solve complex human tasks. However, existing workflow construction still faces key ch

ForcingDAS: Unified and Robust Data Assimilation via Diffusion Forcing

arXiv:2605.14285v1 Announce Type: cross Abstract: Data assimilation (DA) estimates the state of an evolving dynamical system from noisy, partial observations, and is widely used in scientific simulati

applicationsarxiv-cs-lg

From Descriptive to Prescriptive: Uncover the Social Value Alignment of LLM-based Agents

arXiv:2605.14034v1 Announce Type: new Abstract: Wide applications of LLM-based agents require strong alignment with human social values. However, current works still exhibit deficiencies in self-cogni

Local Ai

From Local Matches to Global Masks: Template-Guided Instance Detection and Segmentation in Open-World Scenes

arXiv:2603.03577v2 Announce Type: replace Abstract: Detecting and segmenting novel object instances in open-world environments is a fundamental problem in robotic perception. Given only a small set of

local-aiarxiv-cs-cv

Agents

From Plans to Pixels: Learning to Plan and Orchestrate for Open-Ended Image Editing

arXiv:2605.15181v1 Announce Type: new Abstract: Modern image editing models produce realistic results but struggle with abstract, multi step instructions (e.g., ``make this advertisement more vegetari

agentsarxiv-cs-cv

From Ranking to Reasoning: Explainable Web API Recommendation via Semantic Reasoning

arXiv:2511.05820v2 Announce Type: replace-cross Abstract: The rapid growth of Web APIs has made automated Web API recommendation essential for efficient mashup development. However, existing approache

From Scenes to Elements: Multi-Granularity Evidence Retrieval for Verifiable Multimodal RAG

model-releasesarxiv-cs-cl

arXiv:2605.15019v1 Announce Type: new Abstract: Multimodal Retrieval-Augmented Generation (RAG) systems retrieve evidence at coarse granularities (entire images or scenes), creating a mismatch with fi

From Table to Cell: Attention for Better Reasoning with TABALIGN

arXiv:2605.14465v1 Announce Type: new Abstract: Multi-step LLM reasoning over structured tables fails because planning and execution share no explicit cell-grounding contract. Existing methods constra

FU-MPC: Frontier- and Uncertainty-Aware Model Predictive Control for Efficient and Accurate UAV Exploration with Motorized LiDAR

arXiv:2605.14920v1 Announce Type: new Abstract: Efficient UAV exploration in unknown environments requires rapid coverage expansion while maintaining accurate and reliable localization, since safe nav

Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs

arXiv:2410.06431v5 Announce Type: replace Abstract: Accurate uncertainty quantification in large language models (LLMs) is essential for reliable confidence estimation, yet fine-tuned LLMs often becom

researcharxiv-cs-lg

GenCircuit-RL: Reinforcement Learning from Hierarchical Verification for Genetic Circuit Design

arXiv:2605.14215v1 Announce Type: new Abstract: Genetic circuit design remains a laborious, expert-driven process despite decades of progress in synthetic biology. We study this problem through code g

Generating HDR Video from SDR Video

arXiv:2605.14703v1 Announce Type: new Abstract: The high dynamic range (HDR) video ecosystem is approaching maturity, but the problem of upconverting legacy standard dynamic range (SDR) videos persist

researcharxiv-cs-cv

Geometry-Aware Sampling-Based Motion Planning on Riemannian Manifolds

arXiv:2602.00992v2 Announce Type: replace Abstract: In many robot motion planning problems, task objectives and physical constraints induce non-Euclidean geometry on the configuration space, yet many

Local Ai

GeoVista: Visually Grounded Active Perception for Ultra-High-Resolution Remote Sensing Understanding

arXiv:2605.14475v1 Announce Type: new Abstract: Interpreting ultra-high-resolution (UHR) remote sensing images requires models to search for sparse and tiny visual evidence across large-scale scenes.

local-aiarxiv-cs-cv

GhostCite: A Large-Scale Analysis of Citation Validity in the Age of Large Language Models

arXiv:2602.06718v2 Announce Type: replace-cross Abstract: Citations provide the basis for trusting scientific claims; when they are invalid or fabricated, this trust collapses. With the advent of Larg