Search: “framework”

arXiv:2610.22108v1 Announce Type: new Abstract: Splatting-based radiance-field representations have recently gained popularity in robotic perception, enabling high-quality novel-view synthesis (NVS) t

hardwarearxiv-cs-ro

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CIM-Embed: Learning Instruction-Conditioned Multimodal Embeddings for Clustering

DGX agent

arXiv:2610.21805v1 Announce Type: new Abstract: Multimodal objects can require different partitions under different instructions, as when products in an e-commerce catalog are grouped by color, materi

model-releasesarxiv-cs-ai

16 Oct 2026

CoCopula: Conformal Calibration and Copula Aggregation for Reliable Renewable Energy Forecasting

arXiv:2602.02583v2 Announce Type: replace Abstract: The rapid growth of renewable energy penetration has intensified the need for reliable probabilistic forecasts to support grid operations at aggrega

applicationsarxiv-cs-lg

CoDA: Co-Evolution of Data Engines and Action Policies

arXiv:2610.22362v1 Announce Type: cross Abstract: Generative simulation can automate robot environment construction, but physically valid environments are not necessarily useful for training. The chal

safetyarxiv-cs-ai

Tutorials

Complete or Sparse: A Tale of Two Identifiabilities

arXiv:2610.20851v1 Announce Type: cross Abstract: Understanding when neural networks learn interpretable representations is central to mechanistic interpretability. We study this through identifiabili

tutorialsarxiv-cs-lg

ControlFlow3D: Distilling Multi-View Knowledge into Latent Flow Matching for Point Cloud Upsampling

arXiv:2610.21190v1 Announce Type: new Abstract: Point cloud upsampling is essential for 3D applications but remains challenging due to sparse, under-constrained observations. Multi-view images can res

CoSTA: Compressed Speech Token Adaptation for Efficient Spoken Dialogue Models

arXiv:2610.21143v1 Announce Type: cross Abstract: Spoken Dialogue Models (SDMs) typically share a speech-token space for generation and synthesis, leading to long autoregressive sequences and costly i

CoTS: Competitive Token Selection for Latent Reasoning in Large Language Models

arXiv:2610.20642v1 Announce Type: cross Abstract: Recent latent reasoning methods move beyond discrete Chain-of-Thought (CoT) by replacing sampled tokens with continuous soft embeddings or hidden stat

Counterfactual Neighborhood Risk Fields: Evidence-Grounded Selective Safety for Vision-Language Models

arXiv:2610.20679v1 Announce Type: new Abstract: Representation-based safety defenses for vision-language models (VLMs) often learn to separate harmful from benign inputs, but separation alone does not

safetyarxiv-cs-ai

CQDC-Warp: GPU-Accelerated Differentiable Quasi-Dynamic Simulation for Contact-Rich Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.21349v1 Announce Type: new Abstract: Efficient synthesis of contact-rich manipulation trajectories is essential for downstream robot learning. Gradient-based planning offers a promising app

Data-Efficient ConvNeXt Pretraining for High-Resolution Sentinel-1 GRD SAR Representation Learning

arXiv:2610.21993v1 Announce Type: new Abstract: Labeled Sentinel-1 Ground Range Detected (S1GRD) datasets remain scarce, limiting supervised deep learning for land-surface remote sensing, while self-s

De-Risking Robotic Welding for In-Space Metal Joining Through Physics-Grounded Digital Twins

model-releasesarxiv-cs-ro

arXiv:2610.21939v1 Announce Type: new Abstract: Growing interest in in-space servicing, manufacturing, and assembly has renewed attention on reliable metal joining for modular construction and on-orbi

Decision-FLIP: Budget-Free Structured Pruning for Gaussian Occupancy Models

arXiv:2610.20917v1 Announce Type: new Abstract: Occupancy predictors rely on large persistent banks of Gaussians or learned queries whose size is fixed by hand. Common pruning proxies, such as opacity

Deep Reinforcement Learning for HPC Job Scheduling: A Statistical Evaluation

arXiv:2610.21008v1 Announce Type: new Abstract: Deep Reinforcement Learning (DRL) offers learned job selection for High-Performance Computing (HPC), but performance against heuristics alone does not e

safetyarxiv-cs-ai

Defining and Generating Compositional Structure

arXiv:2610.20922v1 Announce Type: new Abstract: Compositional structure is pervasive in nature and across scales: atoms combine into molecules, molecules into cells, and cells into organisms, while fu

Differentially Private Distribution Release of Gaussian Mixture Models via KL-Divergence Minimization

model-releasesarxiv-cs-lg

arXiv:2506.03467v4 Announce Type: replace-cross Abstract: Gaussian Mixture Models (GMMs) are widely used statistical models for representing multi-modal data distributions, with numerous applications

Diffusion Language Models as Open Quantum Systems

arXiv:2610.21672v1 Announce Type: cross Abstract: Diffusion language models generate text by reversing a classical diffusion process over token sequences. We show that their continuous-time forward an

researcharxiv-cs-cl

DLOSAC: Joint Spatial-Geometric Image Estimation via Delaunay-Guided Local Optimization RANSAC

arXiv:2610.21215v1 Announce Type: new Abstract: Reliable image geometric estimation from noisy matching points is typically addressed using RANSAC, often combined with local optimization to refine inl

local-aiarxiv-cs-cv

DocPilot: Interactive Agent Orchestration and Training for Long Visual Document Understanding

arXiv:2610.21327v1 Announce Type: new Abstract: Multimodal long-document question answering requires models to seek sparse evidence across pages and modalities, understand heterogeneous document conte

agentsarxiv-cs-ai

DropKV: Decoupling Residual-Output Perturbation for Near-Optimal KV-Cache Eviction

arXiv:2610.22130v1 Announce Type: new Abstract: Key-value (KV) cache management has become a critical bottleneck for scaling Large Language Models (LLMs) to long-context scenarios due to linear memory

Efficient Pairwise Difference Learning: A Comparative Study of Encoding Strategies and Training Pair Selection

arXiv:2610.21644v1 Announce Type: cross Abstract: Pairwise Difference Learning for Classification (PDC) enhances supervised learning in low-data regimes by training a binary similarity classifier on p

EgoJEPA: Beyond Retargeting for Dexterous Manipulation from Egocentric Videos

arXiv:2610.20904v1 Announce Type: cross Abstract: Egocentric human videos offer a scalable alternative to costly robot demonstra- tions, yet transferring their manipulation priors to robot control rem

applicationsarxiv-cs-cv

Enhancing Knowledge Density via Hierarchical Context Pruning for Retrieval-Augmented Repository-Level Code Completion

model-releasesarxiv-cs-cl

arXiv:2508.10068v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has advanced repository-level code completion by retrieving external code snippets, API documentation, or

ETH: Data-Balanced Heterogeneous Pipeline Parallelism for Training Large Models

arXiv:2610.22035v1 Announce Type: cross Abstract: Current heterogeneity-aware training systems for large models balance workloads by assigning unequal numbers of layers across pipeline stages, a strat

researcharxiv-cs-lg

EVA-Cap: Optimizing Audiovisual Video Captioning via Event-Centric Alignment

arXiv:2610.22186v1 Announce Type: cross Abstract: Recent advances in Omni Language Models (OLMs) provide a unified solution for audiovisual video captioning. Nevertheless, existing approaches predomin

safetyarxiv-cs-cl

FastVLA: Task-Conditioned and Temporally Adaptive Visual Token Compression for Efficient Vision-Language-Action Models

arXiv:2610.22146v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models present a promising paradigm for general-purpose robot manipulation, but closed-loop deployment is often limited by

researcharxiv-cs-ro

Fault Detection and Bit-Error Rate Diagnostics in Optical Wireless Links Using Edge-AI

arXiv:2610.21402v1 Announce Type: new Abstract: Optical Wireless Communication (OWC) systems provide high-bandwidth, spatially secure, and RF-interference-free digital transmission. However, direct fr

local-aiarxiv-cs-lg

FedSkillGit: Federated Skill Evolution via Version Control

arXiv:2610.21348v1 Announce Type: new Abstract: Large language model agents can improve their capabilities by evolving reusable natural-language skills from execution experience. In real-world deploym

local-aiarxiv-cs-ai

FilterFusion: Prior-Guided Adaptive Filter Fusion for Efficient Video Denoising

arXiv:2610.21505v1 Announce Type: new Abstract: Real-world video denoising for communication systems must handle mixed degradations such as sensor noise, compression artifacts, and motion-induced inco

applicationsarxiv-cs-cv

FIRM: Fisher-Informed Retention Merging for Federated LLM Unlearning

arXiv:2610.21720v1 Announce Type: cross Abstract: Federated LLM unlearning addresses targeted knowledge removal when forget and retain data remain distributed across private clients and are inaccessib

Fractional Power-of-Two Quantization for Efficient and Effective Multiplier-Free LLM Inference

arXiv:2610.21257v1 Announce Type: cross Abstract: Large Language Models (LLMs) demand efficient inference, where the multiply-accumulate (MAC) operations in linear projections dominate compute and ene

From Long Context to Selective Memory:A Survey of Memory-Centric Compression for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.21165v1 Announce Type: new Abstract: Long-context capability has become essential for large language models (LLMs) to handle complex tasks, yet continuously expanding the context window doe

From Optical Flow to Safety: Visual Safety Certification via Scale-Free Relative Motion

arXiv:2610.21374v1 Announce Type: new Abstract: Safe autonomous navigation using monocular vision remains challenging because explicit obstacle states are not directly observable. This letter introduc

safetyarxiv-cs-ro

Functional Subnetwork Localization for Efficient Continual Learning in Large Language Models

arXiv:2610.21537v1 Announce Type: new Abstract: Biological intelligence continually adapts to new information while retaining prior skills through localized plasticity. In contrast, continual learning

FuseAdapt: Parameter-Efficient Multimodal Fusion for Semantic Segmentation with Missing Modalities

arXiv:2610.21779v1 Announce Type: new Abstract: Multi-modal semantic segmentation benefits from complementary sensors, but this benefit is fragile when some modalities are degraded or missing at test

FusionAudit: Pathway-Conditioned Robustness Auditing for Native Multimodal Models

arXiv:2610.21667v1 Announce Type: new Abstract: As vision-language models (VLMs) transition from frozen-encoder pipelines to native multimodal architectures, the visual channel increasingly serves as

researcharxiv-cs-cv

Tutorials

GeoPano: Towards Geometrically Accurate 3D Reconstruction from a Single Panorama

arXiv:2610.21297v1 Announce Type: new Abstract: Panoramic 3D reconstruction enables the holistic recovery of complete 360 ^irc scene geometry, offering significant benefits for robotics and AR/VR appl

tutorialsarxiv-cs-cv

GRADS: Graph-Regulated Agentic Data Synthesis with Controllable Difficulty

arXiv:2610.21167v1 Announce Type: new Abstract: Deep research agents are increasingly deployed to retrieve precise information from large corpora, yet multi-hop, long-horizon tasks remain challenging.

agentsarxiv-cs-ai

GraphACM: Graph-based Action Consistency Measurement for Uncertainty Quantification in LLM Agents

arXiv:2610.22031v1 Announce Type: new Abstract: Behavioral consistency across repeated executions provides an informative signal for assessing the reliability of large language model (LLM) agents. How

agentsarxiv-cs-ai

GraphBEAT: Graph-based Bucketized Event Aggregation Over Time for Early Risk Stratification of Gastrointestinal Cancers

arXiv:2610.22014v1 Announce Type: cross Abstract: Longitudinal electronic health records (EHRs) contain complementary diagnostic and laboratory information about patient health. However, irregularity,

GRASE: Geometry-native Real-to-sim Agentic Scene Modeling from Video

arXiv:2610.21498v1 Announce Type: new Abstract: Real-to-sim conversion aims to turn a captured video of a real environment into an editable 3D scene while preserving the geometry and layout of what wa

agentsarxiv-cs-cv

GRID-Planner: Graph-Structured Relational Reward Shaping for Diffusion Planning

arXiv:2610.21984v1 Announce Type: cross Abstract: Autonomous driving planning requires selecting trajectories that remain safe, rule-compliant, and comfortable under complex multi-agent interactions,

safetyarxiv-cs-cv

Grounded Human-Attributed Description and Activity Recognition in Videos

arXiv:2610.22295v1 Announce Type: new Abstract: Understanding characteristics and activities of individuals in complex multi-person environments is crucial for real-world applications. However, existi

applicationsarxiv-cs-cv

Harmful Partial Interventions and Benign Leakage in Concept-based Models

arXiv:2610.21750v1 Announce Type: cross Abstract: Artificial intelligence systems deployed in high-risk settings increasingly require models that support meaningful human oversight. Concept-based mode

local-aiarxiv-cs-ai

Hierarchical Interpretable Multitask Audio Representation Learning: An Analysis of Event-Scene Relationships through the Information Bottleneck

arXiv:2610.21520v1 Announce Type: cross Abstract: Joint Acoustic Scene Classification (ASC) and Audio Tagging (AT) models traditionally rely on unconstrained multihead architectures. However, this des

Honesty is the Best Policy ... or is it? Demand Management for Probabilistic Service Options

arXiv:2610.21351v1 Announce Type: new Abstract: To enable well-informed customer choices and redistribute demand across service options, providers can display probabilities regarding predicted service

safetyarxiv-cs-lg

Hardware

How to Train Your Little Dragon: Teaching a Small Language Model to Construct and Refine GPU Optimization Scripts

arXiv:2610.20980v1 Announce Type: cross Abstract: Compiler transformations interact, making GPU kernel optimization a search for combinations that preserve the computation while improving performance.

hardwarearxiv-cs-ai

IKMo: Image-Keyframed Motion Generation with Trajectory-Pose Conditioned Motion Diffusion Model

arXiv:2505.21146v2 Announce Type: replace-cross Abstract: While text-to-motion generation is mainstream, integrating explicit spatial constraints has become a standard solution for precise animation.

local-aiarxiv-cs-cv