Search: “evaluation”

Less is More: Label-Guided Efficient Summarization of Procedural and Instructional Videos

arXiv:2601.12243v3 Announce Type: replace Abstract: Video summarization transforms long videos into concise representations that are easier to document and analyze, especially in high-stakes domains s

safetyarxiv-cs-cv

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Model Releases

LIBERO-RIG: A Hardware-Setup Robustness Benchmark for Vision-Language-Action Models

DGX agent

arXiv:2610.18843v1 Announce Type: new Abstract: Robot policies are expected to generalize across deployment environments, including variations in the robot itself: cameras are bumped and remounted, ca

model-releasesarxiv-cs-ro

14 Oct 2026

LiDAR-based Humanoid Navigation in Dynamic, Non-Convex Environments via Spatio-Temporal Safe Corridors

arXiv:2610.17232v1 Announce Type: new Abstract: Navigating humanoid robots through dynamic, non-convex environments requires tightly coupling onboard perception with footstep planning and dynamic loco

researcharxiv-cs-ro

Lifting: Quantum State Discrimination Framework for Mid-Circuit Measurements

arXiv:2610.18482v1 Announce Type: cross Abstract: Quantum computing promises new capabilities beyond classical computation. Mid-circuit measurements (MCMs) enable error correction and outcome-dependen

Lightweight Scheduling Policies for Continuously Batched LLLM Serving Across GPU Architectures

arXiv:2610.15899v1 Announce Type: cross Abstract: Large language model serving is increasingly limited not only by model size and GPU speed, but also by scheduling during autoregressive decoding, wher

LiveAnon: Improving Privacy and Utility in Streaming Speaker Anonymization with Codec Language Models

arXiv:2610.15379v1 Announce Type: cross Abstract: Speaker anonymization (SA) aims to conceal speaker identity while preserving linguistic content and emotion, but existing streaming systems often lose

LLM Agents for Automated Post-Training via Structured Recipe Optimization

arXiv:2610.18572v1 Announce Type: cross Abstract: Automated post-training transforms pre-trained large language models (LLMs) into models capable of handling diverse domains by automatically construct

LLM Judges Have Dark Current: Stratified Null and Utility Tests for LLM Judge Reliability

arXiv:2606.15610v2 Announce Type: replace-cross Abstract: Passing an exact-clone null gate does not entail passing a matched target-selection utility gate. We call a non-tie preference between exact d

LLM Value Functions for Credit Assignment in Agentic RL

arXiv:2610.15840v1 Announce Type: new Abstract: Reinforcement learning (RL) for large language model (LLM) agents remains challenging in long-horizon tasks with sparse outcome rewards, where assigning

Load-Aware Quadruped Navigation with Online Contact-based Geometry Estimation

arXiv:2610.14596v1 Announce Type: new Abstract: Navigating cluttered environments while carrying objects remains a challenging problem for quadruped robots. Compared with works that focused on load-aw

Locomotion with Online Awareness of Dynamics for Precision Footholds

arXiv:2610.17930v1 Announce Type: new Abstract: Unknown payloads alter robot dynamics and make precise contact execution difficult when foothold margins are small. We present LOAD, a perceptive locomo

LongForcing: Scaling Temporal Manifold Matching for Long-Horizon World Rollout

arXiv:2610.18289v1 Announce Type: new Abstract: Autoregressive video diffusion models have emerged as a foundation for long-horizon world rollout. However, when extended far beyond their training wind

safetyarxiv-cs-cv

LoRAtorio: An intrinsic approach to LoRA Skill Composition

arXiv:2508.11624v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has become a widely adopted technique in text-to-image diffusion models, enabling the personalisation of visual concepts

Make {pi}0.5 Learn to Call Astra for Reliable Robot Manipulation

arXiv:2610.14117v1 Announce Type: new Abstract: GPT-6 Astra provides robust embodied reasoning, but frequent external queries increase inference time and token costs. We equip a frozen pi_{0.5} policy

mathbf{S^2LM}: Towards Semantic Steganography via Large Language Models

model-releasesarxiv-cs-cv

arXiv:2511.05319v3 Announce Type: replace Abstract: Despite remarkable progress in steganography, embedding sentence-level information into cover media remains challenging. In this work, we present th

Meaningful Moments: A Corpus of VLM-Derived Temporal Importance Labels for Video Action Recognition

arXiv:2610.16009v1 Announce Type: new Abstract: Not every moment in a video is equally useful for recognizing an action. A few decisive moments often carry the evidence: the instant an object moves, t

Measure Neural Mappings

arXiv:2610.17384v1 Announce Type: new Abstract: We introduce and define measure neural mappings (MNMs), which combine measure-dependent neural transport with ensemble consistency for learning operator

MemAct: Streaming Spatial Understanding with Memory and Active Exploration

arXiv:2610.17640v1 Announce Type: new Abstract: Spatial understanding is essential for embodied agents navigating and interacting with the physical world. As observations arrive incrementally, agents

agentsarxiv-cs-cv

Merit: Making every modality earn its contribution in multimodal attention decoding

arXiv:2610.17507v1 Announce Type: new Abstract: More than 1.5 billion people have hearing loss. When several people talk at once, hearing aids amplify every voice alike. Auditory attention decoding (A

MERIT: Multimodal Evidence Reasoning over Image Tables

arXiv:2610.17937v1 Announce Type: new Abstract: Table reasoning with language models typically assumes access to clean textual tables. In practice, tables are often serialized into text, which can cor

safetyarxiv-cs-cv

Mesh-Free Convolution: Learned Spectral Attenuation and Transport

arXiv:2610.15931v1 Announce Type: new Abstract: Learning solution operators for partial differential equations (PDEs) requires models that can represent spatial structure across grids and scales. This

Metadata-Guided Adaptable Frequency Scaling across Heterogeneous Applications and Devices

arXiv:2509.22707v2 Announce Type: replace-cross Abstract: Dynamic Voltage and Frequency Scaling is essential for enhancing energy efficiency in mobile platforms. However, traditional heuristic-based g

Metric-Driven Reinforcement Learning for Object Hallucination Reduction in LVLM-Based Image Captioning

arXiv:2610.14976v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have excelled in joint visual and language understanding, particularly in image captioning. However, LVLMs remain p

MFG: Multi-turn Feedback Guided Molecular Optimization

arXiv:2610.18851v1 Announce Type: cross Abstract: Multi-objective molecular optimization is a critical process in drug discovery that aims to modify a given molecule to simultaneously improve multiple

Local Ai

MFlowHOI: Whole-Body Human-Object Interaction Generation via Part-Aware MeanFlow

arXiv:2610.16252v1 Announce Type: new Abstract: Whole-body human-object interaction (HOI) generation requires coordinating body and finger motion, object trajectories, and time-varying contacts. Exist

local-aiarxiv-cs-cv

MIRRA: Fast, High-Fidelity Molecular Generation with Chemistry-Informed Discrete Flow Matching

arXiv:2610.17244v1 Announce Type: new Abstract: Fast, high-fidelity molecular generation requires accurate chemical choices and efficient sampling. Chemical building blocks reduce graph size, but make

MissPath-FM: Flow Matching with Structured Priors for Partially Observed Time Series

arXiv:2610.17715v1 Announce Type: new Abstract: Flow matching has emerged as a powerful alternative to diffusion models for generative modeling, but standard conditional flow matching is fundamentally

Mixed Precision Scaling Laws for Quantized Pretraining

arXiv:2610.17637v1 Announce Type: new Abstract: Since scaling laws were introduced for modern LLMs (Kaplan et al., 2020), several works have extended them to account for quantization, tracking the eme

Mixture of GFlowNets

arXiv:2610.17007v1 Announce Type: new Abstract: Generative Flow Networks (GFlowNets) learn a policy that samples compositional objects in proportion to an unnormalized reward R(x). This makes them use

Applications

ML-CLAPPS: A Probabilistic Framework for Imbalanced Multilabel Learning under Class Prioritization

arXiv:2610.15816v1 Announce Type: cross Abstract: Real-world datasets often exhibit severe class imbalance, degrading the performance of deep learning models, particularly on rare classes. While imbal

applicationsarxiv-cs-cv

ML Engineering Agents - A Data Management Perspective

arXiv:2610.16919v1 Announce Type: cross Abstract: Machine learning engineering (MLE) agents are emerging as a new paradigm for automating end-to-end ML pipeline development. Using large language model

MMTA: Benchmarking Multimodal Temporal Analysis with Time Series, Text, and Vision

arXiv:2610.17856v1 Announce Type: new Abstract: Time-series analysis is increasingly studied in multimodal settings, yet most benchmarks pair temporal signals with text or with visualizations derived

Model-Based Trailer-Sway Suppression for Autonomous Passenger Vehicles

arXiv:2610.15747v1 Announce Type: new Abstract: Trailer sway is a persistent contributor to severe crashes among light passenger vehicles towing trailers, yet it remains largely unaddressed by the aut

agentsarxiv-cs-ro

ModRes: A modification of the ResPlan dataset ready for floor plan analysis and graph machine learning

arXiv:2610.17178v1 Announce Type: new Abstract: Floor plan datasets underpin computational analysis of building layouts, spatial connectivity and graph machine learning. However, publicly available da

Moment-Based Anomaly Detection in High-Dimensional Mixed Data

arXiv:2610.16285v1 Announce Type: cross Abstract: We propose an anomaly detection method for high-dimensional mixed-type data that maps heterogeneous features to a common scale via standardized moment

Morphology-aware deep learning predicts colorectal cancer survival from whole-slide images

arXiv:2610.17603v1 Announce Type: new Abstract: Background: Five-year survival prediction from hematoxylin-and-eosin whole-slide images could support risk stratification, but the task is weakly superv

MOSAIC: Mode- and Support-Aware Inference-Time Control of Robot Diffusion Models

arXiv:2610.17001v1 Announce Type: new Abstract: Generative policies such as diffusion models provide expressive data-driven priors for robot behavior, yet the situations a robot faces at execution tim

MP-MNCA: Morphology-Prior Masked Neighbor Cross-Attention for Efficient Spatial Domain Identification

arXiv:2610.16212v1 Announce Type: new Abstract: Spatial transcriptomics jointly captures molecular state, tissue morphology, and spatial organization, yet spatial-domain methods are typically compared

Multi-modal Representation Fusion for Long-term Microsurgical Anastomosis Trajectory Anticipation

arXiv:2610.14492v1 Announce Type: cross Abstract: Microsurgical anastomosis is one of the most challenging and sophisticated procedures for surgical robotics, requiring accurate manipulation of surgic

agentsarxiv-cs-cv

Multimodal Fusion of RGB and Complementary Modalities for Semantic Segmentation

model-releasesarxiv-cs-cv

arXiv:2610.17800v1 Announce Type: new Abstract: Multi-modal semantic segmentation adds an auxiliary sensing stream to RGB images (RGB-X), such as thermal, LiDAR, depth, event, polarization, or light f

Naga: Vedic Encoding for Deep State Space Models

arXiv:2511.13510v2 Announce Type: replace Abstract: This paper presents Naga, a deep State Space Model (SSM) encoding approach inspired by structural concepts from Vedic mathematics. The proposed meth

Natural Code Transformation Confuses Agents in Vulnerability Analysis

arXiv:2610.14350v1 Announce Type: cross Abstract: Having demonstrated a strong potential for automating vulnerability discovery, AI agents can also be used to attack software systems at scale. Today's

agentsarxiv-cs-lg

Natural Language Generation from Visual Events: State-of-the-Art and Key Open Questions

arXiv:2502.13034v4 Announce Type: replace-cross Abstract: In recent years, a substantial body of work in visually grounded natural language processing has focused on real-life multimodal scenarios suc

Neuro-Symbolic Graph Transformers for Hierarchical Intention Recognition from Multimodal Human Activity Sequences

arXiv:2610.18176v1 Announce Type: cross Abstract: Proactive human-robot collaboration requires autonomous systems to infer not only immediate actions but also the underlying hierarchical intentions go

agentsarxiv-cs-lg

Local Ai

NeuroVLA: A Brain-inspired Embodied Intelligence for Fluid and Fast Reflexive Robotics Control

arXiv:2601.14628v2 Announce Type: replace Abstract: Vision-language-action (VLA) models inherit powerful semantic representations from large language models, but carrying over their design priorities

local-aiarxiv-cs-ro

Applications

NeuSE: Neural SE(3)-Equivariant Embedding for Long-Term Object-Based Simultaneous Localization and Mapping

arXiv:2303.07308v3 Announce Type: replace-cross Abstract: We present NeuSE, a novel Neural SE(3)-Equivariant Embedding for objects, and illustrate how it supports object-based Simultaneous Localizatio

applicationsarxiv-cs-cv

Local Ai

NoduleFlow: Automatic 3D Lung Nodule Detection and Segmentation

arXiv:2610.16548v1 Announce Type: new Abstract: Low dose Computed Tomography (CT) is the standard imaging modality for lung cancer screening. On CT scans, lung cancer typically manifests as pulmonary

local-aiarxiv-cs-cv

Not All Drift Is a Mechanism: Tracing Prompt Adaptation in LLMs

arXiv:2610.18412v1 Announce Type: new Abstract: Prompt-based adaptation offers several ways to specialize a frozen language model, ranging from natural-language prompt optimization to learned continuo