Search: “evaluation”

SG-FSM: A Self-Guiding Zero-Shot Prompting Paradigm for Multi-Hop Question Answering Based on Finite State Machine

arXiv:2410.17021v2 Announce Type: replace Abstract: Large Language Models with chain-of-thought prompting, such as OpenAI-o1, have shown impressive capabilities in natural language inference tasks. Ho

researcharxiv-cs-cl

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Model Releases

ShearFuse-UNet: Hadamard, DCT, and Shearlet Transform Fusion for Next-Day Wildfire Spread Prediction

DGX agent

arXiv:2606.14071v2 Announce Type: replace Abstract: We propose ShearFuse-UNet, a lightweight and computationally efficient deep learning model for next-day wildfire spread prediction from multi-modal

model-releasesarxiv-cs-cv

22 Sept 2026

SKstars at SHROOM: Visions Agreement-Guided Ensembling of Zero-Shot and LoRA-Adapted Vision--Language Models

arXiv:2609.24198v1 Announce Type: cross Abstract: This paper describes the SKstars submission to SHROOM-Visions 2026, a shared task on fine-grained hallucination detection in large vision-language mod

researcharxiv-cs-cv

SLICEChat: Progressive In-Encoder Token Pruning for Whole-Slide Pathology Language Models

arXiv:2609.24894v1 Announce Type: cross Abstract: Whole-slide pathology images (WSIs) contain gigapixel-scale visual content, creating a major scalability challenge for slide-level multimodal large la

researcharxiv-cs-cl

Small Gradient Norm Regret for Online Convex Optimization

arXiv:2601.13519v4 Announce Type: replace-cross Abstract: This paper introduces a new problem-dependent regret measure for online convex optimization with smooth losses. The notion, which we call the

SmoLSTM: A Compact Vision-Language-Action Model with Recurrent Memory that Persists

arXiv:2609.22854v1 Announce Type: cross Abstract: Vision-language-action models often predict actions from only the current observation, which can leave tasks involving object occlusion or visually id

Some Dialects Are More Equal Than Others: Non-Prestigious Arabic Dialectal Bias in LLMs

arXiv:2609.23955v1 Announce Type: new Abstract: Previous work on Egyptian Arabic in NLP has focused largely on the prestigious Cairene Egyptian Arabic (CEA) dialect, resulting in a lack of representat

safetyarxiv-cs-cl

Sparse Regression Distilled from a Single Robust Fit

arXiv:2609.23937v1 Announce Type: cross Abstract: Robust linear fits can resist response contamination yet remain too dense or unstable for useful global explanations. We propose penalized distillatio

Hardware

SPARSER: Sparse Variable Projection by Exploiting Separable Structure in Robotic Perception

arXiv:2609.24708v1 Announce Type: new Abstract: Robotic perception often requires solving large nonlinear least-squares (NLS) problems. While sparsity has been widely exploited to scale solvers, a com

hardwarearxiv-cs-ro

SSP-GNN: Learning to Track via Bilevel Optimization

arXiv:2407.04308v4 Announce Type: replace Abstract: We propose a graph-based tracking formulation for multi-object tracking (MOT) where target detections contain kinematic information and re-identific

researcharxiv-cs-cv

Stable and Efficient Real-World Online VLA Post-Training via Asynchronous Replay-Anchored Policy Improvement

arXiv:2609.22888v1 Announce Type: new Abstract: Online post-training of vision-language-action (VLA) models requires efficient use of robot interaction and reliable policy improvement from continually

Stagewise Anomaly Detection for E-Transaxle Quality Monitoring Using Wavelet and STFT Features

arXiv:2609.22172v1 Announce Type: cross Abstract: This paper presents two interpretable machine-learning frameworks for quality screening of e-transaxle assemblies in electric vehicles: a Stagewise Wa

applicationsarxiv-cs-lg

STAR: Scene- and Task-Aware 4D Radar Preprocessing Towards End-to-End Cognitive Radar

arXiv:2609.24151v1 Announce Type: new Abstract: Four-dimensional (4D) Radar has emerged as a key sensor for environmental perception, providing range, azimuth, elevation, and Doppler measurements whil

StateMem: Single-State Residual Memory with Adaptive Inference for Vision-Language-Action Policies

arXiv:2609.22684v1 Announce Type: cross Abstract: Memory-dependent robotic manipulation often requires later actions to use information from earlier interactions. Existing vision-language-action (VLA)

applicationsarxiv-cs-lg

Steering Through Contact: A Finite-Support Motion Model for Single-Track Center-Articulated Robots

arXiv:2609.23271v1 Announce Type: new Abstract: Trajectory planning and control in field robotics rely on predicting how propulsion and steering affect vehicle motion when contact points undergo slip.

applicationsarxiv-cs-ro

StenoVLA-3D: 3D-Aware Reasoning VLA for Navigation Through Gastrointestinal Stenoses

arXiv:2609.24187v1 Announce Type: cross Abstract: Autonomous endoscopic navigation requires the policy model to predict actions from texture-poor monocular observations, make safe control decisions, a

safetyarxiv-cs-cv

STEVE: Stabilizing Textual Gradient-Based Prompt Optimization via Error-Driven Refinement and Regularized Verification

arXiv:2609.23716v1 Announce Type: new Abstract: Textual-gradient methods automate prompt optimization through natural-language feedback, but their iterative updates can be unstable. We identify two so

Stochastic Reconfiguration as Statistical Filtering for Overparameterized Neural Quantum States

arXiv:2609.23334v1 Announce Type: cross Abstract: Stochastic reconfiguration (SR) is the standard optimizer for neural quantum states (NQS), but modern NQS often have far more parameters than Monte Ca

Agents

Strategy Accumulation and Guided Execution for Automated LLM Fine-Tuning

arXiv:2609.22257v1 Announce Type: cross Abstract: Producing task-specific large language models requires discovering effective training strategies through experimentation. Automated fine-tuning system

agentsarxiv-cs-cl

Streaming Deep Reinforcement Learning Finally Works

arXiv:2410.14606v3 Announce Type: replace Abstract: Learning from a stream of experience as it arrives, also known as streaming learning, is a core part of natural learning. However, reliable streamin

STRIDER: Stepping-Enabled Multi-Gait Hierarchical 3D Loco-Manipulation Framework for Humanoid Robots

arXiv:2609.23483v1 Announce Type: new Abstract: Humanoid loco-manipulation faces two prominent limitations: controllers using continuous velocity commands cannot precisely regulate individual foothold

StyleAT: Defending Face Recognition Against Semantic Attacks

arXiv:2609.23596v1 Announce Type: new Abstract: With face-recognition models now embedded in everyday authentication and surveillance, recent works have pinpointed a critical weakness: these models re

researcharxiv-cs-cv

SupportCal: Label-Free Calibration of Post-Trained LLMs via Reference Support and Corroboration

arXiv:2609.24303v1 Announce Type: cross Abstract: Post-training often improves task performance but can degrade confidence calibration, leaving post-trained language models (PoLMs) more overconfident

safetyarxiv-cs-cl

t_0: A Time-Series Foundation Model for Forecasting with Context

arXiv:2609.24559v1 Announce Type: new Abstract: We present t_0, a family of open-weights foundation models for forecasting with multivariate context. We release its first two members: exttt{t0-alpha}

TACIT: Tactile Contact Supervision for Spatial Attention in Dexterous Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.24507v1 Announce Type: new Abstract: Visuomotor policies trained from a few demonstrations may reproduce demonstrated trajectories without reliably following changes in object position. Exi

Taking a Second Look: Correcting Sea Ice Forecasts with Sparse Observations

arXiv:2609.24591v1 Announce Type: new Abstract: Sea ice forecasts are issued several days ahead, allowing errors to accumulate while new, often sparse sea ice concentration (SIC) observations become a

Task aware Dynamic Movement Primitives for failure detection and recovery in contact rich manipulation

arXiv:2609.23151v1 Announce Type: cross Abstract: Assembly remains a challenging robotic manipulation task in presence of tight tolerances and complex contact interactions. While Learning from Demonst

TempCore: Are Video QA Benchmarks Temporally Grounded?

arXiv:2509.01167v3 Announce Type: replace-cross Abstract: Vision-language models (VLMs) can ingest only a limited number of video frames, making frame selection a practical necessity. But do current V

researcharxiv-cs-cl

TEMPER: Temporal Encoder-Masked Probabilistic Ensemble Regressor for Time-Series Forecasting

arXiv:2609.23701v1 Announce Type: cross Abstract: Probabilistic forecasting requires accurate central predictions and calibrated uncertainty estimates. This paper presents TEMPER, the Temporal Encoder

The Bairong System for MLC-SLM 2026: Dynamic Question-Aware Evidence Routing for Multilingual Conversational Speech Understanding

arXiv:2609.22214v1 Announce Type: new Abstract: Long multilingual conversational spoken question answering requires systems to balance long-range transcript semantics with sparse acoustic and speaker-

safetyarxiv-cs-cl

The Effect of Quantization on Clinical Benchmarks: Accuracy and Safety Across Model Families

arXiv:2609.22216v1 Announce Type: cross Abstract: Quantization enables deployment of large language models on resource-constrained clinical edge devices, but its effect on clinical accuracy and safety

The Role of Dataset Linguistic Structure in the Cultural Awareness of Large Language Models

arXiv:2602.01161v2 Announce Type: replace Abstract: The global deployment of large language models (LLMs) has raised concerns about cultural misalignment, yet the linguistic properties of fine-tuning

Time Series Foundation Models for Process Model Forecasting

arXiv:2512.07624v2 Announce Type: replace Abstract: Process Model Forecasting (PMF) aims to predict how the control-flow structure of a process evolves over time by modeling the temporal dynamics of d

Toollery: Scaling LLM Agents to Thousands of Skills and Tools

arXiv:2609.22218v1 Announce Type: cross Abstract: As LLM agents are exposed to hundreds to tens of thousands of skills, tools, and API functions, full-library prompting becomes costly, slow, and less

Toscani-Fourier Distance on Probability Measures: Wasserstein Control, Topological Equivalence on Model Classes, and Duality

arXiv:2609.23163v1 Announce Type: cross Abstract: Comparing probability measures in machine learning trades transport geometry against computational cost: Wasserstein distances encode the geometry of

Tutorials

Toward a foundation model for forest point clouds

arXiv:2609.24787v1 Announce Type: new Abstract: Forest inventories increasingly rely on artificial intelligence (AI) models to derive forest attributes from large-scale 3D point clouds. Current models

tutorialsarxiv-cs-cv

Toward a Unified Mathematics of Concepts

arXiv:2609.24554v1 Announce Type: new Abstract: Concepts are commonly defined as abstract, compact representations of knowledge and treated as basic units of intelligent behavior. Yet, cognition, psyc

applicationsarxiv-cs-cl

Local Ai

Toward Personalized Sleep Guidance from Wearable Data Using Language Models

arXiv:2609.22463v1 Announce Type: new Abstract: Sleep monitoring using wearable data has shown promise for personal health, yet large language model (LLM)-based summarization and question answering re

local-aiarxiv-cs-cl

TRACE: Tractable Routing Autoencoder for Clinical ECG

arXiv:2609.23460v1 Announce Type: new Abstract: Deep learning has advanced automated electrocardiogram (ECG) diagnosis, but the field's most accurate models, foundation models pretrained on millions o

Training-Free Spectral Transductive Refinement for Cross-Domain Few-Shot Classification

arXiv:2609.23758v1 Announce Type: new Abstract: Few-shot recognition with frozen visual features is especially fragile under domain shift and one-shot supervision, where a single labelled image is an

Transformer-Based Warm-Starting for Feasible and Optimal Terminal Approach to Tumbling Objects with Space Manipulators

arXiv:2606.17317v2 Announce Type: replace Abstract: Autonomous capture of a tumbling object with a space manipulator requires trajectory generation under real-time onboard constraints. However, couple

Hardware

TriFleetRCA: On-Premise LLM Root Cause Analysis for Kubernetes

arXiv:2609.23766v1 Announce Type: cross Abstract: Root cause analysis at a remote site is slow: evidence is scattered across pod logs, Kubernetes events and cluster-level objects, and many operators c

hardwarearxiv-cs-lg

Triggers and Diagnostics for LLM-Based Interpretability Failures in Active Inference Agents

arXiv:2609.23215v1 Announce Type: new Abstract: LLM explainers are increasingly attached to autonomous agents as runtime oversight, with operators reading a generated account of the agent's beliefs an

TWIG: A Time-Causal Wavelet Operator for Autoregressive Forecasting on Irregular Graphs

arXiv:2609.22585v1 Announce Type: new Abstract: We introduce TWIG (Time-Causal Wavelet Operator for Irregular Graphs), a graph-native neural operator for autoregressive surrogate modeling on static ir

U-PEN Mamba: Progressive Expansion with Selective State-Space Modeling for Efficient Retinal Vessel Segmentation

arXiv:2609.24049v1 Announce Type: new Abstract: Accurate retinal vessel segmentation is important for computer-aided ophthalmic analysis, yet thin vessels, low contrast, and severe foreground-backgrou

Unified Learning of Temporal Task Structure and Action Timing for Bimanual Robot Manipulation

arXiv:2603.06538v2 Announce Type: replace Abstract: Bimanual manipulation requires both temporal task structure - which actions precede or overlap others - and concrete timing - when each action start

researcharxiv-cs-ro

UniK: Universal Knowledge Perception for Digital and Physical AI

arXiv:2609.23971v1 Announce Type: cross Abstract: Two transformative classes of AI systems are reshaping how organizations operate: extit{digital AI}, which reasons over enterprise knowledge to power

Agents

Universal Observatory Graphs for Distributed Sky Coverage and Artificial Intelligence Based Interplanetary Routing

arXiv:2609.22244v1 Announce Type: new Abstract: This research proposes the Universal Observatory Graph (UOG), an AI-driven framework for distributed astronomical observation across the Solar System. T

agentsarxiv-cs-lg