Search: “framework”

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

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Model Releases

Functional Subnetwork Localization for Efficient Continual Learning in Large Language Models

DGX agent

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

model-releasesarxiv-cs-ai

16 Oct 2026

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

model-releasesarxiv-cs-cv

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

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.

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

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,

researcharxiv-cs-ai

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

Applications

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

Illumination-Aware Active Perception for Spacecraft Inspection

arXiv:2610.22335v1 Announce Type: new Abstract: Harsh and rapidly varying orbital illumination introduces failure modes during spacecraft inspection. Existing planners rely on line-of-sight inspection

tutorialsarxiv-cs-ro

Improving Environment-Agnostic Coding Agents: The Role of Scaffolding

arXiv:2610.22289v1 Announce Type: new Abstract: Stronger language models may increasingly construct useful procedures for themselves, reducing the advantage of developer-supplied scaffolding. We inves

Applications

In-Context Preference-Conditioned Pareto Set Learning from Limited Offline Data

arXiv:2610.21736v1 Announce Type: new Abstract: Multi-objective optimization involves diverse preferences over conflicting objectives. Rather than returning a finite set of trade-off solutions, prefer

applicationsarxiv-cs-ai

In the Guise of Correction: How Framing and Cultural Adaptation Erode LLM Safety on Real-World Criminal Cases

arXiv:2610.21789v1 Announce Type: cross Abstract: Existing safety benchmarks rely largely on synthetic prompts with loosely grounded taxonomies and offer little focused analysis of severe crime catego

Incentivizing Tool-Use Reinforcement Learning for Post-Arrival Emergency Care Prediction

arXiv:2610.21449v1 Announce Type: new Abstract: Large language models (LLMs) can reason over both structured measurements and free-text records, which makes them attractive for emergency department (E

Inertially Significant Humanoid Teleoperation via Whole Body Model Predictive Control and Online Parameter Estimation

model-releasesarxiv-cs-ro

arXiv:2610.22176v1 Announce Type: new Abstract: The effective deployment of humanoid robots in practical tasks of interest will require a capability of sensing and adapting to variations in inertial p

Interpreting Language Model Parameters

arXiv:2610.20748v1 Announce Type: cross Abstract: Mechanistic interpretability aims to uncover how neural networks use their parameters to implement their impressive neural algorithms. Although previo

Iterative Neural Variational Solver of Committor Function in Under-damped Langevin Dynamics

model-releasesarxiv-cs-lg

arXiv:2610.20617v1 Announce Type: cross Abstract: The committor function describes the probability that a stochastic dynamical system, while transitioning between two metastable states, will first rea

KnowGPO: Knowledge-Grouped Policy Optimization for Search Agents

arXiv:2610.22331v1 Announce Type: new Abstract: Deep search agents solve knowledge-intensive tasks through long-horizon, multi-turn interactions, where assigning credit to individual search decisions

safetyarxiv-cs-ai

KULTURE Bench: A Benchmark for Assessing Language Model in Korean Cultural Context

arXiv:2412.07251v1 Announce Type: cross Abstract: Large language models have exhibited significant enhancements in performance across various tasks. However, the complexity of their evaluation increas

L2G-SR: Learning to Guide LLM-based Symbolic Regression

arXiv:2610.20685v1 Announce Type: new Abstract: Symbolic regression searches for an equation that explains observed data. Numerical error is commonly used to guide the search, but it alone can favor a

tutorialsarxiv-cs-ai

L2GSSL: Label-Efficient Local-to-Global Self-Supervised Learning for Volumetric Healthcare Data

arXiv:2610.21356v1 Announce Type: new Abstract: Healthcare institutions routinely accumulate high-dimensional computed tomography (CT) volumes, but only a fraction can be annotated by experts. We pres

local-aiarxiv-cs-cv

LAMP: Layerwise Adaptive Mixing of Predictors for Training-Free Few-Shot Vision-Language Adaptation

arXiv:2610.22182v1 Announce Type: new Abstract: Few-shot adaptation often relies on an encoder's final global representation, leaving complementary information in intermediate layers underused. Combin

researcharxiv-cs-cv

LCT: Losslessly Compressed Tensors with GPU friendly execution for Training

model-releasesarxiv-cs-lg

arXiv:2610.22179v1 Announce Type: new Abstract: Lossless tensor compression could reduce memory usage during training, but training requires tensors to be repeatedly re-encoded. We introduce Losslessl

Learning at the Right Pace: Adaptive Data Scheduling Improves LLM Reinforcement Learning

arXiv:2606.22305v2 Announce Type: replace Abstract: Large Language Models (LLMs) achieve remarkable reasoning capabilities through reinforcement learning (RL) post-training. However, existing RL post-

safetyarxiv-cs-cl

Learning Not To Interfere: Adapting Experts For Model Merging

arXiv:2603.13467v2 Announce Type: replace-cross Abstract: Model merging has shown that multitask models can be created by directly combining the parameters of different models that are each specialize

researcharxiv-cs-ai

Learning Rewards in Strategic Games

arXiv:2610.21912v1 Announce Type: cross Abstract: Understanding the objectives that drive agents' behavior is crucial in strategic environments, where multiple agents interact and adapt to one another

safetyarxiv-cs-ai

Learning Self-Orchestration in Decentralized Agent Swarms

arXiv:2610.22322v1 Announce Type: cross Abstract: The capabilities of an agent swarm depend on both its individual members and how they coordinate. Yet existing multi-agent systems often train agents

local-aiarxiv-cs-ai

Learning Speech Attribute Representations via Multi-Teacher Distillation

arXiv:2610.21941v1 Announce Type: new Abstract: Recent post-training approaches have shown that self-supervised speech encoders can be adapted to learn a single utterance-level speech attribute throug

tutorialsarxiv-cs-cl

Learning to Search for Executable Patternmaking from Certified Programs

arXiv:2610.21579v1 Announce Type: cross Abstract: Recent models generate sewing patterns from images or text, and program-based representations make these patterns executable. These systems produce a

researcharxiv-cs-ai

Learning Topology-Aware Representations for Mechanics-Relevant TPMS Metamaterials

arXiv:2610.20684v1 Announce Type: cross Abstract: Learning informative representations of mechanical Triply Periodic Minimal Surface (TPMS) metamaterials is important for mechanics analysis and struct

safetyarxiv-cs-cv

Learning When to Think: Utility-Guided Adaptive Reasoning for Efficient Text Retrieval

model-releasesarxiv-cs-cl

arXiv:2610.21030v1 Announce Type: cross Abstract: Reasoning-conditioned embeddings can improve retrieval by progressively refining semantic constraints. However, additional reasoning may introduce ove

LEASH: Uncertainty-Aware Weak-to-Strong Escalation and Oversight for Computer-Use Agents

arXiv:2610.22280v1 Announce Type: new Abstract: Computer-use agents increasingly tackle long-horizon tasks, where running a frontier model at every step is expensive and a small open-weight model alon

Let's Ask Gauss: Improved One-Run Privacy Auditing

arXiv:2606.12733v3 Announce Type: replace Abstract: Privacy auditing provides an important safeguard by estimating the actual information leaked by a model, thus ensuring that theoretical privacy guar

researcharxiv-cs-lg

Librarian Agents: Training LLMs to Curate Long-Context Workspaces that Anticipate Future Queries

arXiv:2610.22273v1 Announce Type: cross Abstract: Reasoning over long document contexts remains a challenge for large language models (LLMs). Standard retrieval methods are inherently reactive, bottle

LOOP-MAC: Learning-Based Multi-Agent Coordination with Guaranteed Local Feasibility in a Virtual Power Plant

arXiv:2310.17882v3 Announce Type: replace Abstract: By aggregating distributed energy resources (DERs) into a single dispatchable resource, virtual power plants (VPPs) enable the grid to use the flexi

agentsarxiv-cs-lg

LoopAhead: Speculating Ahead for Faster Decoding in Looped Language Models

arXiv:2610.21594v1 Announce Type: new Abstract: Looped Transformers improve parameter efficiency by repeatedly applying the same Transformer layers. However, generating each token still involves seque

MAGMA: Multiplier-Augmented Geometric Motion Algorithm

arXiv:2610.21852v1 Announce Type: new Abstract: Solving optimal control problems for high-dimensional mechanical systems subject to constraints remains challenging due to nonlinear dynamics and non-co

researcharxiv-cs-ro

MAI-Gym: An Open All-in-One Platform for GUI Agent Evaluation and RL Training across Mobile and Computer Environments

arXiv:2610.20939v1 Announce Type: new Abstract: Online reinforcement learning (RL) with verifiable rewards has driven rapid progress in mathematics, coding, and tool use, but scaling this success to G

MAIA: Anticipating Interaction Anomalies in Contact-Rich Manipulation via Multimodal World Models

arXiv:2610.21686v1 Announce Type: new Abstract: Reliable contact-rich manipulation requires detecting execution deviations early enough for corrective action. Yet most monitoring methods are reactive,

safetyarxiv-cs-ro

Manifold Generative Annealing for Contact Constraint-aware Impedance Control with Reinforcement Learning Prior

arXiv:2610.21140v1 Announce Type: new Abstract: Contact-rich robotic tasks require coordinated motion and impedance under uncertain interaction dynamics and physical constraints. While recent methods

safetyarxiv-cs-ro

ManiFusion: Unlocking the High-Throughput Generation via Superposition in Manifold Space

arXiv:2610.21433v1 Announce Type: new Abstract: Diffusion models achieve high-quality image generation but remain computationally expensive due to iterative denoising across many timesteps. Existing a

tutorialsarxiv-cs-cv