Search: “framework”

LOGIC: An LLM Benchmark for Intent-Grounded Change Impact in Aerospace Electrical Systems

arXiv:2610.07580v1 Announce Type: new Abstract: Aerospace electrical-design revisions can contain multiple genuine changes, although an engineering request may authorize only a subset. Propagating eve

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Model Releases

M3SunAgent: Monocular 3D Spatial Understanding Agent for Metric Depth Estimation and 3D Visual Grounding

DGX agent

arXiv:2610.07982v1 Announce Type: new Abstract: Monocular metric depth estimation and 3D visual grounding represent the two complementary cornerstones of monocular 3D spatial understanding (M3Sun), fr

model-releasesarxiv-cs-cv

7 Oct 2026

MedCORE: Criteria-Grounded Clinical Reasoning for Interpretable Medical Image Diagnosis

arXiv:2610.08528v1 Announce Type: cross Abstract: Clinical diagnosis is inherently a structured reasoning process, yet existing deep learning models often bypass this structure by mapping image featur

researcharxiv-cs-ai

MedZERO: Self-Evolving Agents for Open-Ended Medical Reasoning Through Controlled Knowledge Accumulation

arXiv:2610.08327v1 Announce Type: new Abstract: Large language models (LLMs) have shown promise in medical question answering and clinical reasoning, yet their improvement remains constrained by stati

researcharxiv-cs-ai

MemCo: Memory-Centric Collaboration for Generalizing LLM Agents to Unseen Environments

arXiv:2610.07376v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate in interactive environments, where they need to make sequential decisions through observation, ac

Memory Prediction Excess: A Probabilistic Quantity for Predictive Gain and Memory Length in Stochastic Processes

arXiv:2610.06894v1 Announce Type: cross Abstract: A central question in the prediction of stochastic processes is the extent to which past information can improve the probability of correctly predicti

Tutorials

MetaLearnNCA: Few-Shot Offline Meta-Learning via Interacting Neural Cellular Automata

arXiv:2610.08479v1 Announce Type: cross Abstract: Few-shot meta-learning traditionally formulates task adaptation either as analytical gradient descent through unrolled computational graphs or as metr

tutorialsarxiv-cs-ai

Mitigating Concept Drift in QoS Prediction for Teleoperation of Autonomous Vehicles Using Historic Data

arXiv:2610.08297v1 Announce Type: cross Abstract: Teleoperation serves as the fallback solution to autonomous driving but reliable functions of the teleoperation require a certain amount of mobile net

MobileVISTA: Generative Data Augmentation for Pose Generalization in Mobile Manipulation

arXiv:2610.07511v1 Announce Type: cross Abstract: Mobile manipulators such as humanoid robots are increasingly deployed in dynamic, unstructured environments to perform dexterous manipulation tasks. H

researcharxiv-cs-cv

MoF: Preference-Aware Mixture Modeling for Black-Box LLM Personalization

arXiv:2610.08330v1 Announce Type: new Abstract: Proprietary Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks, yet aligning their outputs with diverse

Multimodal Knowledge Distillation for Gastric Adenocarcinoma Classification from Whole-Slide Images

arXiv:2610.07913v1 Announce Type: cross Abstract: Gastric adenocarcinoma (GA) is a leading cause of cancer-related mortality worldwide, and accurate histopathological subtype classification from whole

Applications

Navigating Route Latent Space for Synthesizable Molecular Design

arXiv:2610.07560v1 Announce Type: new Abstract: Goal-directed molecular design has advanced rapidly, yet a substantial proportion of designed molecules remain difficult to synthesize in practice, limi

applicationsarxiv-cs-ai

Navigation with RF Cues: Embodied Perception Action under Multipath Uncertainty

model-releasesarxiv-cs-ro

arXiv:2610.08105v1 Announce Type: new Abstract: Smart factory inspection requires robots to reach connected equipment without a prior map or known target coordinates. Radio frequency (RF) signals from

Neural Algorithmic Reasoning for Graph Saddle Point Problems

arXiv:2610.07255v1 Announce Type: new Abstract: Neural algorithmic reasoning, or aligning a neural network with an algorithmic paradigm, has emerged as an approach to solving polynomial-time-solvable

safetyarxiv-cs-lg

Nonlocal Hamiltonian Dynamics on Sparse Levy Graphs: Spectral Analysis and Multimodal Sampling

arXiv:2610.06904v1 Announce Type: cross Abstract: We develop a sparse graph method for transporting probability mass toward multimodal target distributions through damped nonlocal Hamiltonian dynamics

Nord-Parl-TTS: Finnish and Swedish TTS Dataset from Parliament Speech

arXiv:2509.17988v2 Announce Type: cross Abstract: Text-to-speech (TTS) development is limited by scarcity of high-quality, publicly available speech data for most languages outside a few high-resource

researcharxiv-cs-cl

One for All, All for One: Coordinated Multi-Agent Diffusion Steering via Stochastic Optimal Control

arXiv:2610.08595v1 Announce Type: cross Abstract: Deep generative models often produce structured outputs composed of interacting components. Modelling these outputs with a single model requires learn

OOPMAS: Object-Oriented Multi-Agent Systems for Query-Level Workflow Generation

arXiv:2610.07787v1 Announce Type: new Abstract: Multi-agent systems (MAS) powered by large language models have shown strong performance across code generation, mathematical reasoning, and question an

Optimization Encoders: Rethinking Second-Order Meta-Learning for Neural Fields

arXiv:2610.08075v1 Announce Type: cross Abstract: Conditional neural fields represent signals continuously, but their effectiveness depends on how the conditional latent representations are inferred f

Pareto-Optimal Entropy-Regularized Trajectory Optimization

arXiv:2610.08532v1 Announce Type: new Abstract: Trajectory optimization (TO) under nonlinear dynamics, actuation limits and collision avoidance constraints is a fundamental problem in robotics, albeit

researcharxiv-cs-ro

Partially Observable Zero-shot coordination by Predicting Intention of Partner

arXiv:2610.08142v1 Announce Type: new Abstract: Zero-shot coordination in embodied settings requires acting while the partner is intermittently out of view, leaving existing methods with ambiguous par

PEARS: Physical-Prior-Guided Efficient Adaptation via Failure Reasoning and Diffusion Steering for Tactile Manipulation

arXiv:2610.08784v1 Announce Type: new Abstract: Pretrained robotic policies can suffer substantial performance degradation under out-of-distribution (OOD) conditions encountered during deployment, mot

safetyarxiv-cs-ro

Performative Prediction with Selective Labels

arXiv:2610.08272v1 Announce Type: new Abstract: Many social applications of machine learning exhibit performative effects: population behavior changes in response to deployed models. Performative pred

safetyarxiv-cs-lg

Applications

PhoneBot: A Low-Cost Open Humanoid Robot Platform Reusing Smartphones

arXiv:2610.08737v1 Announce Type: new Abstract: The adoption of humanoid robots in education and research remains limited by high hardware costs, complex sensing systems, and substantial computational

applicationsarxiv-cs-ro

PhysTacGen: Physics-Aware Visual-Tactile Sensor Image Generation

arXiv:2610.08068v1 Announce Type: new Abstract: Realistic physical interaction is a cornerstone of embodied intelligence, yet collecting paired visual--tactile data remains costly. Visual-to-tactile s

PIE-PS: Photometric Stereo from Physical Irradiance Event Streams

arXiv:2610.08188v1 Announce Type: new Abstract: Event cameras record asynchronous log-image-irradiance changes with microsecond latency and high dynamic range. These properties are useful for photomet

researcharxiv-cs-cv

PlaySuite: A Large-Scale Benchmark for Interactive Visual Intelligence

arXiv:2610.07127v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models yield strong performance on static perception and reasoning benchmarks, yet such evaluations largely o

POLAR: Ontology-Guided Risk Prevention for Tool-Calling LLM Agents

arXiv:2610.08082v1 Announce Type: new Abstract: LLM tool-use agents operate in dynamic environments where many actions carry operational risk. However, most safety mechanisms react only after errors m

safetyarxiv-cs-ai

Preserving Unstable Modes Through Inverse Dynamics in JEPA World Models

arXiv:2610.07540v1 Announce Type: new Abstract: Robotic systems often exhibit unstable modes, along which small perturbations and disturbances can cause unbounded growth unless corrected through feedb

Principles that Guide, Actions that Inform: Agent Evolution via Knowledge Abstraction

arXiv:2610.06964v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong capabilities in interactive environments, yet their ability to continually evolve from experi

Probabilistic Counterfactual Inference for Discrete Outcomes in Gaussian-Process Causal Models

arXiv:2610.08689v1 Announce Type: new Abstract: Counterfactual inference in Gaussian-process structural causal models (GP-SCMs) has been developed primarily for continuous endogenous variables, limiti

PRUE: A Practical Recipe for Field Boundary Segmentation at Scale

model-releasesarxiv-cs-cv

arXiv:2603.27101v2 Announce Type: replace Abstract: Large-scale maps of field boundaries are essential for agricultural monitoring tasks. Existing deep learning approaches for satellite-based field ma

Applications

QiYao-I: A Manifold Based Foundation Model for Irregular Multivariate Time Series Forecasting

arXiv:2610.06936v1 Announce Type: new Abstract: Irregular multivariate time series forecasting is a challenging yet important problem in real-world applications, where observations are often irregular

applicationsarxiv-cs-lg

Qubit-centric Transformer for Surface Code Decoding

arXiv:2510.11593v3 Announce Type: replace-cross Abstract: For reliable large-scale quantum computation, quantum error correction (QEC) is essential to protect logical information distributed across mu

researcharxiv-cs-ai

RA-MoWE: Workflow-Affinity Embeddings for Query Clustering and Agentic Workflow Generation

arXiv:2610.07851v1 Announce Type: new Abstract: Agentic workflows enable large language models (LLMs) to solve complex tasks by coordinating reasoning, tool use, and verification. However, a workflow

RACE-FPP: A Robust AI-assisted Characterisation Enhancement for Fringe Projection Profilometry

arXiv:2610.08213v1 Announce Type: new Abstract: Fringe Projection Profilometry (FPP) requires precise system characterisation to achieve reliable three-dimensional (3D) reconstructions; however, chara

researcharxiv-cs-cv

Rationale-Guided Policy Optimization: Learning to Reason with Adaptive Rationale Scaffolding

arXiv:2610.07342v1 Announce Type: new Abstract: On-policy reinforcement learning has become a central paradigm for improving the reasoning abilities of large language models. However, its effectivenes

safetyarxiv-cs-ai

RBMatch: Dual-Level Class Rebalancing for Semi-Supervised Building Footprint Extraction

arXiv:2610.07698v1 Announce Type: new Abstract: Accurate building footprint extraction from high-resolution remote sensing imagery is essential for urban planning, disaster response, and environmental

ReDex: Repairing Sim-to-Real Dexterous Policies by Finger-Level Compliant Interaction

arXiv:2610.07525v1 Announce Type: new Abstract: Dexterous manipulation policies trained in simulation often fail to transfer to the real world because of errors in contact timing and force regulation.

safetyarxiv-cs-ro

RefRoute: Decoupling Conditioning Cost from References via Compact Residual Conditioning and Spatial Routing

model-releasesarxiv-cs-cv

arXiv:2610.07720v1 Announce Type: new Abstract: Multi-reference image generation requires preserving the appearance of multiple subjects while composing them into a coherent scene. However, existing d

Reinforcement Learning with Segment Reward Feedback under Linear Function Approximation

arXiv:2610.08271v1 Announce Type: new Abstract: Classical reinforcement learning (RL) assumes that a reward is observed for every visited state-action pair. However, in real-world applications such as

agentsarxiv-cs-lg

Local Ai

RELACE: retrospective likelihood-based action credit estimation for long-horizon language agents

arXiv:2610.07349v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) avoids a separate critic by estimating advantages from rollout groups. For multi-turn agents, however, traje

local-aiarxiv-cs-ai

REPA-G: Test-Time Conditioning with Representation-Aligned Visual Features

arXiv:2602.03753v2 Announce Type: replace Abstract: While representation alignment with self-supervised models has been shown to improve diffusion model training, its potential for enhancing inference

Retrieval Is Not Enough: Refreshing Memory for Frozen Time-Series Forecasters

arXiv:2610.07834v1 Announce Type: new Abstract: Retrieval-augmented time-series forecasting uses the continuations of historical segments similar to the current context as references for a forecaster.

safetyarxiv-cs-lg

Revisiting Numerical Forecasting Models for Language-Based Trajectory Prediction

arXiv:2610.07954v1 Announce Type: new Abstract: Language-based trajectory predictors represent coordinates as discrete tokens and learn auxiliary tasks such as destination and group reasoning. This fo

Risk-Sensitive Crowd Navigation with Adaptive Ellipsoidal Conformal Prediction

arXiv:2610.07474v1 Announce Type: new Abstract: Safe crowd navigation under distribution shift requires uncertainty representations that capture structured human-motion prediction errors and safety ob

safetyarxiv-cs-ro

Local Ai

RIWANav: Recursive World-Action Models with Self-Improvement for Urban Navigation

arXiv:2610.08640v1 Announce Type: new Abstract: Long-horizon urban navigation requires sequential local decisions whose errors can compound over time. Imitation learning (IL) rarely learns from failur

local-aiarxiv-cs-ro

Robust Importance Sampling for Rare Events via Constrained Gaussian Mixtures

arXiv:2610.07485v1 Announce Type: new Abstract: We study estimating rare-event probabilities I = P(g(mathbf{X}) > gamma) with mathbf{X} sim N(oldsymbol{mu}, oldsymbol{Sigma}) and general g : R^d o R.