Search: “evaluation”

Efficient Test-Time Adaptation through Latent Subspace Coefficients Search

arXiv:2510.11068v4 Announce Type: replace Abstract: Real-world deployment often exposes vision models to distribution shifts, making test-time adaptation (TTA) important for reliable prediction. Exist

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Research

EgoExplorer: A Vision-Motion-Touch Observatory for Human Loco-Manipulation In Situ

DGX agent

arXiv:2610.18872v1 Announce Type: cross Abstract: Learning humanoid loco-manipulation from human demonstrations rests on observing how locomotion, posture, and object interaction evolve together as ta

researcharxiv-cs-cv

14 Oct 2026

ELECT: Settling Identity Before Rendering for Scalable Story Visualization

arXiv:2610.15555v1 Announce Type: new Abstract: Training-free story visualization without reference images must preserve recurring entities across frames while scaling to long narratives. Existing met

Embedding Graph Kernel Entropy (EGKE): Fine-grained Hallucination Detection for LLMs from Embeddings

arXiv:2610.14214v1 Announce Type: new Abstract: Hallucination detection is critical for ensuring the reliability of Large Language Models (LLMs) in real-world deployments. While recent works, such as

Embodied Zero-Shot Task Planning via Hardware-Aware LLM-VLM Integration for Grounded Robotic Manipulation

arXiv:2610.14106v1 Announce Type: new Abstract: Large language models can translate natural-language instructions into plausible manipulation plans, but robotic execution requires physically grounded

local-aiarxiv-cs-ro

Embodiment-Aware Inference-Time Search for Human Reaction Selection in Humanoid Retargeting

model-releasesarxiv-cs-ro

arXiv:2610.15274v1 Announce Type: new Abstract: Training humanoid robots to learn human behaviors requires expensive data collection, and human-robot interaction data can be even more difficult and co

Agents

EnactOpt: Diagnosis-Guided Harness Evolution for Embodied Agents

arXiv:2610.14977v1 Announce Type: new Abstract: Embodied agents built on foundation models rely on an execution harness to organize observations, guide actions, and incorporate execution feedback into

agentsarxiv-cs-ro

Engram Neuron Inspired Adaptive Memorization for Lifelong Learning

arXiv:2610.14940v1 Announce Type: new Abstract: Lifelong learning enables artificial systems to adapt to changing environments. To achieve this, an effective artificial learner should dynamically reor

Ensemble-MIX: Enhancing Sample-Efficiency in Multi-Agent RL via Selective Ensemble-Based Exploration

arXiv:2506.02841v5 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning (MARL) methods have achieved state-of-the-art results on a range of multi-agent tasks. Yet, MARL algorithms

Equilibrium Learning in Unbounded Stochastic Games with Gaussian Transitions

arXiv:2610.16149v1 Announce Type: cross Abstract: Learning equilibria from data is difficult when several decision makers interact indefinitely and the system state has no prescribed bounds. We examin

EvoSpatial: Experience-Driven Skill and Tool Evolution for Spatial Reasoning Agents

arXiv:2610.16679v1 Announce Type: new Abstract: Tool-augmented vision-language agents compose perception and measurement to reason about spatial relationships, but effective execution also requires tr

Exploration strategies for Gaussian process bandit optimization with inference regret guarantees

arXiv:2610.16187v1 Announce Type: cross Abstract: Existing cumulative regret guarantees for Bayesian optimization (BO) do not necessarily characterize the quality of the algorithm's final output. This

Exploring the Latent Structure of AMD Severity Using Retinal Foundation Models

arXiv:2610.14138v1 Announce Type: cross Abstract: Retinal foundation models have demonstrated strong performance across a wide range of ophthalmic tasks, yet relatively little is known about how disea

applicationsarxiv-cs-cv

Failure Recovery via Belief Updates and World Modeling for Long-Horizon Agents

arXiv:2610.18082v1 Announce Type: new Abstract: Long-horizon agents often struggle to recover from failures whose causes lie several steps earlier, beyond what local reflection or backtracking can res

local-aiarxiv-cs-lg

FALLNEST: Dual-Domain Dataset Condensation of Imbalanced IMU Data for Wearable Fall Detection

arXiv:2610.18260v1 Announce Type: new Abstract: Wearable fall detection is hampered by rare fall events, scarce labeled IMU data, and the cost of training deep models on large, imbalanced corpora. Exi

Hardware

FastEEP: Fast Intra-Instance Elastic Scaling for Expert-Parallel MoE Serving

arXiv:2610.18451v1 Announce Type: cross Abstract: Large-scale expert parallelism (EP) has become the standard deployment configuration for Mixture-of-Experts (MoE) models in production. Meanwhile, the

hardwarearxiv-cs-lg

Tutorials

Feature Normalization under Finite Training Budgets

arXiv:2610.16845v1 Announce Type: cross Abstract: Standardizing a rare feature can help stochastic gradient descent learn its effect within a finite budget, but it also changes the noise cost of learn

tutorialsarxiv-cs-lg

FEM-Validated Real-Time Modelling of Soft Tactile Deformation

arXiv:2610.16667v1 Announce Type: new Abstract: Accurate modelling of soft tactile sensors remains difficult because finite element methods (FEM) are computa- tionally expensive, while real-time simul

local-aiarxiv-cs-ro

FireNav: Decision-Oriented Reconstruction Evidence Routing for Vision-Language Navigation in Indoor Fire Environments

arXiv:2610.15595v1 Announce Type: new Abstract: In real-world indoor fire environments, visual degradation severely impairs instruction grounding, waypoint prediction, and long-horizon exploration in

Fitted Q-Iteration with Continuous Actions and Adaptive Data: Smoothed Coverage and Minimax Rates

arXiv:2605.05791v2 Announce Type: replace Abstract: Fitted Q-iteration (FQI) is well understood when the data come from a fixed distribution and the action set is finite, whereas value-based continuou

FlowCred: Hierarchical Credit Assignment and Functional Coordination for Joint Text-to-Video Post-Training

arXiv:2610.18142v1 Announce Type: new Abstract: Prompt optimization and generator post-training are two complementary ways to improve text-to-video (T2V) generation, and recent systems increasingly tr

local-aiarxiv-cs-cv

Tutorials

FlowVLA: Enabling World Dynamics Understanding through Pluggable 3D Flow Learning

arXiv:2610.16160v1 Announce Type: new Abstract: Recent advances in 3D reconstruction enable the extraction of temporally consistent 3D motion from RGB observations; however, current Vision-Language-Ac

tutorialsarxiv-cs-ro

FOCUS: A Subspecialty Foundation Model for Intraoperative Central Nervous System Pathology

arXiv:2610.16914v1 Announce Type: new Abstract: Intraoperative frozen-section diagnosis of central nervous system (CNS) lesions guides surgical decisions but is challenged by artefacts, diagnostic com

Formal-Verification-Guided Bayesian Optimization for Non-Intrusive Last-Mile Coverage Closure

arXiv:2610.17449v1 Announce Type: cross Abstract: Last-mile functional coverage closure for modern chip designs remains costly because a mature UVM environment exposes many controls while direct hits

Foundation Models for Event Prediction Across Heterogeneous Event Logs

arXiv:2610.17503v1 Announce Type: new Abstract: Event logs are ubiquitous across real-world domains, including business processes, manufacturing workflows, healthcare, and many other operational syste

Hardware

FoundationVIO: Enforcing Metric Scale in Feed-forward Visual-Inertial Odometry

arXiv:2610.14951v1 Announce Type: new Abstract: Feed-forward geometric foundation models (GFMs) directly predict dense geometry and camera poses from batches of images. Emerging visual SLAM methods ch

hardwarearxiv-cs-ro

From Failure Prediction to Component Selection in Semantic Segmentation

arXiv:2610.16058v1 Announce Type: new Abstract: Reliable scene understanding requires deciding which predictions to trust, retain, or inspect. In semantic segmentation, component failure predictors su

From LLM Plans to Authorized Motion: Execution-Bound Authorization for Excavators

arXiv:2610.14245v1 Announce Type: new Abstract: An LLM-directed excavator can execute mechanically feasible motion whose destination or authority no longer matches the operator's approval. We propose

researcharxiv-cs-ro

From Orbit Matching to Docking: A Hierarchical Reinforcement-Learning Approach to Multiphase Rendezvous Trajectory Design

arXiv:2610.17468v1 Announce Type: cross Abstract: As the complexity of space missions increases, autonomous spacecraft guidance must accommodate transitions between mission phases with distinct dynami

From Topology to Retrieval: Decoding Embedding Spaces with Unified Signatures

arXiv:2511.22150v3 Announce Type: replace Abstract: Studying the shape of text embedding spaces enhances our understanding of model behavior and how geometry affects downstream task performance. While

From Transfer Probes to Expert Grouping: Evidence from LoRA Post-Training

arXiv:2610.14437v1 Announce Type: new Abstract: A platform that post-trains one base model for many business lines often has more lines than experts it can maintain, so lines must share experts, yet l

From Video to Vision: Learning Generalizable Humanoid Carrying from Human Motion

arXiv:2610.14561v1 Announce Type: new Abstract: Most existing approaches rely on video or motion-capture data for reinforcement learning (RL) training; however, all of these methods require an upper-l

safetyarxiv-cs-ro

GA-SVD: Generation-aware Singular Value Decomposition for LLM Compression

arXiv:2610.15398v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong generalization across a broad range of reasoning and generation tasks, but their large parameter counts

Agents

Gaussian Process Bandits for AI System Optimization with Selectively Verified Feedback

arXiv:2610.17760v1 Announce Type: new Abstract: Gaussian process bandits exploit similarities among configurations to optimize prompts, retrieval systems, and agent workflows. In these applications, h

agentsarxiv-cs-lg

Gaussian Splatting for Real-Time Scene Reconstruction: Methods, Systems, and Trade-offs

arXiv:2610.17513v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) allows for high-quality real-time novel-view synthesis. Since its inception in 2023, its explicit and highly configurable s

Generalizable Model Editing Could Be More Than Direct Generalization

arXiv:2610.15707v1 Announce Type: new Abstract: A central desideratum in model editing is generalization to complex tasks, which prior work formalizes under a direct generalization paradigm: treating

Generalized PINN-Based Inverse Estimation of Spatially Varying Heat Transfer Coefficients with Transfer Learning

arXiv:2610.14008v1 Announce Type: new Abstract: This study investigates generalized boundary representations and transfer learning for physics-informed neural-network (PINN) estimation of spatially va

Geometric Calibration of Supervised Fine-Tuning

arXiv:2610.18634v1 Announce Type: new Abstract: Recent studies investigate the weight geometry through its spectral structure, which characterizes how the weights transform different input directions.

Geometry-Aware Predictive Control for Walk-to-Run Bipedal Obstacle Crossing

model-releasesarxiv-cs-ro

arXiv:2610.15735v1 Announce Type: new Abstract: This paper presents a geometry-aware predictive control framework for bipedal obstacle crossing across walking and running regimes. The proposed approac

GIFT: Global Irreplaceability Frame Targeting for Efficient Video Understanding

arXiv:2603.25072v2 Announce Type: replace Abstract: Video Large Language Models (VLMs) have achieved remarkable success in video understanding, but the significant computational cost from processing d

Tutorials

Gradient Routing Localizes and Removes Unintended Behaviors in RL

arXiv:2610.17062v1 Announce Type: new Abstract: We propose a mitigation to reward hacking in reinforcement learning. Our setup involves a misspecified reward function that gives rise to unintended beh

tutorialsarxiv-cs-lg

GreenWAM: A World Foundation Model for Robotics

arXiv:2610.18774v1 Announce Type: new Abstract: A robot needs a world model that predicts how its actions will change the scene and a policy that chooses those actions. Models are usually built and ev

safetyarxiv-cs-ro

GReFEM: Multimodal LLMs as Zero-Shot Semantic Assistants for Physics-Guided 3D Mesh Refinement

arXiv:2607.08798v2 Announce Type: replace-cross Abstract: Adaptive volumetric finite element meshing traditionally requires iterative PDE solvers or heavily supervised, data-driven surrogates trained

local-aiarxiv-cs-cv

Grounding Deep Learning Framework Testing in Data Flow

arXiv:2610.15808v1 Announce Type: cross Abstract: Data flow underlies deep learning (DL) framework execution, including automatic differentiation and operator-fusion optimization. Bugs involving data

GuidanceNFT: NFT-Based Reward Fine-Tuning of Guided Diffusion Models

arXiv:2610.15856v1 Announce Type: new Abstract: DiffusionNFT (NFT) fine-tunes diffusion models toward task-specific rewards, but optimizing these rewards does not guarantee fidelity to the full prompt

HaloBlock: Faster and Better Decoding for Diffusion Large Language Models

arXiv:2610.17948v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) have attracted increasing research attention due to their bidirectional attention and arbitrary order decoding.

Harmonic Representations in Symbolic Music Transformers are Localized and Controllable

arXiv:2610.15957v1 Announce Type: cross Abstract: Transformer models trained on symbolic music have become remarkably capable. However, it is yet unclear how they represent music structure, and whethe

Harnessing VLM in Embodied RL: From Reward Regressor to Success Detector via Exploration-Augmented Key-Observation Gating

arXiv:2610.15401v1 Announce Type: new Abstract: VLMs provide promising solutions to embodied reward design. Most current methods that train VLMs as reward regressors not only require extensive annotat