Search: “evaluation”

EvolveTrade: Experience-Driven Policy Refinement for Self-Evolving LLM Trading Agents

arXiv:2609.17632v1 Announce Type: new Abstract: Large language model (LLM) trading agents can combine market data, news, and executable analysis, but their behavior is often controlled by static hand-

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Fourier Analysis of Parametrized Interactive Quantum Classifiers

DGX agent

arXiv:2609.17991v1 Announce Type: cross Abstract: Interactive Quantum Classifiers (IQCs) constitute a family of quantum machine learning models inspired by open quantum systems, in which the interacti

model-releasesarxiv-cs-lg

17 Sept 2026

From a River in Gilead to the Inference Distributions of Large Language Models: Covert Dialect Bias and Linguistic Profiling at Scale

arXiv:2609.18068v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains such as housing screening. While alignment techniques mitigate explicit

FuseFi: Combining Irregularly Sampled CSI from Diverse Communication Packets and Frequency Bands for Wi-Fi Sensing

arXiv:2512.22143v2 Announce Type: replace-cross Abstract: Existing Wi-Fi sensing systems rely on injecting high-rate probing packets to extract channel state information (CSI), leading to communicatio

G-Mamba: Sparse Graph-Guided Mamba for Audio-Visual Speech Enhancement

arXiv:2609.18009v1 Announce Type: cross Abstract: Lightweight audio-visual speech enhancement (AVSE) models face a critical trade-off between computational efficiency and cross-modal alignment accurac

safetyarxiv-cs-cl

GraphPoint: Semantic Entity Graphs and Point Trajectories for Compositional Robot Manipulation

arXiv:2609.18358v1 Announce Type: new Abstract: Robot manipulation policies often struggle to generalize beyond their demonstrations, even when new instructions involve familiar objects and behaviors.

HINT-Plan: Human Intention-Aware Robot Task Planning in Context-Rich Environments using Vision Language Models

arXiv:2609.17771v1 Announce Type: cross Abstract: Approaches to incorporating human awareness into mobile robot decision-making mainly focus on collision avoidance in low-level motion planning, often

agentsarxiv-cs-ai

How AI Assistants Respond to Repeated Abuse

model-releasesarxiv-cs-cl

arXiv:2609.17547v1 Announce Type: new Abstract: AI assistants are expected to remain useful during difficult interactions, but little is known about how repeated verbal abuse changes their engagement

Human Resilience in the AI Era -- What Machines Can't Replace

arXiv:2510.25218v2 Announce Type: replace-cross Abstract: AI is changing work and decision making faster than many institutions can adapt their operating practices. We argue that this adaptation gap m

applicationsarxiv-cs-ai

Hyperbolic Graph Representation Learning for Differential Diagnosis on Biomedical Knowledge Graphs

arXiv:2609.18481v1 Announce Type: new Abstract: Biomedical knowledge graphs combine ontology-derived hierarchies with transversal associations among heterogeneous entities such as phenotypes, diseases

researcharxiv-cs-ai

'If I Had to Buy Just ONE: Galaxy S26 Ultra': Auditing AI-Generated Product Recommendations

model-releasesarxiv-cs-cl

arXiv:2609.18729v1 Announce Type: cross Abstract: Consumers increasingly use AI chatbots for advice on what to buy. With companies like OpenAI and Google monetising their AI through advertising, this

Imitation Learning for Autonomous Driving in CARLA

arXiv:2609.17757v1 Announce Type: new Abstract: Behavioral cloning trains a policy offline on expert demonstrations, but deployment is closed loop: each action affects the observations the policy rece

In-Context Robot Learning with VLM Agents

arXiv:2609.19138v1 Announce Type: cross Abstract: Enabling robots to adapt to unfamiliar environments as readily as humans remains a moonshot goal of embodied AI. No finite collection of demonstration

safetyarxiv-cs-ro

Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data

arXiv:2609.18842v1 Announce Type: new Abstract: The scaling laws hold that a language model grows more capable with more parameters and more training data, and Mixture-of-Experts (MoE) architectures h

Is Luke the Author of a Gospel and the Acts of the Apostles?

arXiv:2609.17762v1 Announce Type: cross Abstract: According to Christian tradition, Luke is credited with authoring a Gospel and the Acts of the Apostles, even if his name does not appear in either bo

researcharxiv-cs-ai

KDTwin: Task-Aware Knowledge Distillation for Lightweight Multi-Task Driving Scene Segmentation

arXiv:2609.18955v1 Announce Type: new Abstract: Efficient perception models are essential for real-time autonomous driving, where accuracy and computational cost must be carefully balanced. However, a

agentsarxiv-cs-cv

KINO: A Keyframe Interface for VLM Planning and Whole-Body Control in Humanoid Loco-Manipulation

arXiv:2609.18869v1 Announce Type: new Abstract: Humanoid loco-manipulation requires robots to interpret task instructions and scene semantics while executing coordinated whole-body motions. We propose

safetyarxiv-cs-ro

LaSeD: Label-Semantic Self-Distillation for Visual-Only Surgical Phase Recognition

arXiv:2609.18971v1 Announce Type: new Abstract: Surgical phase recognition maps each video frame to a clinically meaningful workflow phase, supporting context-aware assistance, documentation, and post

researcharxiv-cs-cv

LEAP: Learning Emergent Active Perception for Quadruped Navigation

arXiv:2609.17628v1 Announce Type: new Abstract: Active perception allows autonomous agents to select their viewpoints rather than passively process the viewpoints given to them, enabling them to targe

agentsarxiv-cs-ro

Learning Heterogeneous Preferences

arXiv:2609.17847v1 Announce Type: new Abstract: Learning from human feedback has become a central paradigm for training modern AI systems, where models of human utility are used as reward models in po

Learning to Stack: Cube-Stacking Imitation Learning from Virtual Reality Demonstrations

arXiv:2609.19040v1 Announce Type: new Abstract: Imitation learning is attractive for robot manipulation, but collecting demonstrations remains a bottleneck for multi-stage tasks requiring repeated sce

safetyarxiv-cs-ro

Hardware

Lecture notes on Physics Informed Neural Networks, Neural Operators, and their applications

arXiv:2609.17638v1 Announce Type: cross Abstract: This is the set of lecture notes for the PhD course href{https://www.unibz.it/en/faculties/engineering/phd-computer-science/study-course-offering/2025

hardwarearxiv-cs-ai

Tutorials

LIGE-GR: A Smooth Leap from Ranking to Generative Recommendation in the LLM Era

arXiv:2609.18148v1 Announce Type: new Abstract: The remarkable success of large language models (LLMs) has provided important inspiration for the next generation of recommender systems. Structurally,

tutorialsarxiv-cs-lg

Long-Context Demonstration Selection Using State Space Models

arXiv:2609.17888v1 Announce Type: cross Abstract: We study the problem of demonstration selection, which involves selecting a subset of examples for prepending to a query to a language model. This pro

applicationsarxiv-cs-cl

Look Less, Hear Better: Jointly Rewarded GRPO for Streaming ASR

arXiv:2609.18333v1 Announce Type: cross Abstract: Streaming automatic speech recognition (ASR) must be judged jointly on what it transcribes and on how quickly it commits each word. Delayed streams mo

LSR-Net: Learning the Forward Evolution Operator for Nonlinear Fluid Dynamics

arXiv:2609.19039v1 Announce Type: cross Abstract: We introduce the Long-Short-Range Neural Network (LSR-Net), a novel neural operator architecture designed for data-driven forward evolution modeling,

researcharxiv-cs-lg

Lumen: Parameter-Efficient Alignment of Pretrained Vision and Language Encoders for Zero-Shot Computational Pathology

model-releasesarxiv-cs-cv

arXiv:2609.17868v1 Announce Type: new Abstract: Pathology vision-language models are commonly built by pretraining or fine-tuning large encoders on paired image-caption data. We asked whether a pathol

M-SQE: Multilingual Skill Quality Estimation for Enhancing Language Equality in Agentic Skill Use

arXiv:2609.18445v1 Announce Type: new Abstract: Agent skills, reusable procedural documents that extend LLM agents beyond their parametric memory, have become an important interface for deploying agen

agentsarxiv-cs-cl

{M}^2Tok: Multi-head Multi-codebook Discrete Action Tokenization for Vision-Language-Action Models

arXiv:2609.18259v1 Announce Type: cross Abstract: Recent advancements have successfully adapted autoregressive language models to process multimodal signals, such as images and actions. Since raw acti

Local Ai

Making AI-Assisted Claims Independently Challengeable: Publication Authority and a Protocol for Falsifiable Publication Records

arXiv:2609.17631v1 Announce Type: new Abstract: AI-assisted claims can appear authoritative when evidence, analysis, human authorization, presentation, and correction history refer to different states

local-aiarxiv-cs-ai

Tutorials

MechSparse: Mechanism-Guided Sparse PEFT Selection Is Task-Shaped

arXiv:2609.18961v1 Announce Type: new Abstract: Mechanistic interpretability identifies sparse subsets of heads and MLP blocks that carry specific behaviors. We ask whether such causal signals can gui

tutorialsarxiv-cs-cl

Model-Based Adaptive Precision Control for Tabletop Planar Pushing Under Uncertain Dynamics

arXiv:2510.03768v2 Announce Type: replace Abstract: Data-driven planar pushing methods have recently gained attention as they reduce manual engineering effort and improve generalization compared to an

applicationsarxiv-cs-ro

MS-RFD: Multi-Signal Release Frame Detection in Hammer Throw from Reconstructed 3D Trajectories

arXiv:2609.18260v1 Announce Type: new Abstract: Recent advances in artificial intelligence and computer vision are reshaping sports performance analysis by enabling automated detection, tracking, and

applicationsarxiv-cs-cv

Multimodal Behavior Tree Generation: A Small Vision-Language Model for Robot Task Planning

arXiv:2603.06084v2 Announce Type: replace Abstract: Large language models have been widely used for robotic task planning, often taking advantage of representations such as Behavior Trees (BTs). Visio

Multimodal Conditioning of Fine-Tuned Stable Diffusion XL for Controllable and Culturally Faithful Ulos Motif Generation

arXiv:2609.17987v1 Announce Type: new Abstract: The traditional Batak Ulos weaving industry faces growing challenges in producing diverse, innovative motifs due to limitations in conventional, manuall

NanoBench: A Multi-Task Benchmark Dataset for Nano-Quadrotor System Identification, Control, and State Estimation

arXiv:2603.09908v2 Announce Type: replace Abstract: Existing aerial-robotics benchmarks target vehicles from hundreds of grams to several kilograms and typically expose only high-level state data. The

NeuroSketch: A Practical Design Recipe for Neural Decoding

arXiv:2512.09524v2 Announce Type: replace-cross Abstract: Neural decoding is fundamental to brain-computer interfaces, with growing applications in healthcare. Previous research has focused on leverag

applicationsarxiv-cs-ai

Newer Is Not Fairer: Gender Stereotyping in Text-to-Image AI Across Model Generations

arXiv:2609.18007v1 Announce Type: cross Abstract: Text-to-image generative models are widely used in professional and creative settings, yet how they represent gender across occupations -- and whether

NObSP: Functional Decomposition of Neural Networks via Oblique Subspace Projections

arXiv:2609.17825v1 Announce Type: new Abstract: Understanding how deep neural networks make decisions remains a fundamental challenge. We present NObSP (Nonlinear Oblique Subspace Projections), a fram

NormLift: From Lifted Features To Semantic Reliability In 3D Gaussian Splatting

arXiv:2609.18898v1 Announce Type: new Abstract: Training-free weighted aggregation is widely used to lift 2D semantic features onto 3D Gaussians for open-vocabulary scene understanding, yet its theore

safetyarxiv-cs-cv

Not All Layers Need Tuning: Diagnosing and Directing Adaptation in Vision-Language-Action Models

arXiv:2609.18084v1 Announce Type: cross Abstract: Fine-tuning a Vision-Language-Action (VLA) model for a new deployment environment is expensive, yet most methods apply uniform-capacity adapters to ev

On the Identifiability of Mixed Ordinal and Exponential Family Causal DAGs under Linear Parametric Models

arXiv:2609.17942v1 Announce Type: new Abstract: The problem of identifiability in linear parametric models (LPMs) whose nodes follow either an ordered logit model or a regular one-parameter exponentia

One Color Preprocessing Improves DSATUR

arXiv:2609.17633v1 Announce Type: new Abstract: The Graph Coloring Problem (GCP) is NP-hard and DSATUR stands as one of the fastest heuristics for it despite producing colorings that typically use mor

Tutorials

Opt-In Art: Learning Art Styles Only from Few Examples

arXiv:2412.00176v4 Announce Type: replace Abstract: We explore whether pre-training on datasets with paintings is necessary for a model to learn an artistic style with only a few examples. To investig

tutorialsarxiv-cs-cv

Patch the Distribution Mismatch: RL Rewriting Agent for Stable Off-Policy SFT

arXiv:2602.11220v2 Announce Type: replace-cross Abstract: Large language models are commonly adapted to downstream tasks through supervised fine-tuning (SFT), but substantial distribution mismatch bet

safetyarxiv-cs-cl

PentestChain: A Cost-Aware, MCP-Orchestrated Framework for Automated Penetration Testing with Free-Tier LLMs

arXiv:2609.18120v1 Announce Type: cross Abstract: AI-driven penetration testing has been demonstrated with premium frontier models such as GPT-4, but the per-engagement token cost makes continuous, au

Physics-Informed Neural Networks for Fast Multilayer Spectral Inversion of H{alpha} 6562.8 A and Ca II 8542.1 A Spectra

arXiv:2609.18025v1 Announce Type: cross Abstract: Strong chromospheric absorption lines such as Halpha 6562.8 A and Ca II 8542.1 A provide vital diagnostics of plasma dynamics and thermal structure in

PointZero: 3D Point Track Completion for Learning Transferable 3D Dynamics

arXiv:2609.19142v1 Announce Type: cross Abstract: World models endow perceptual systems with the ability to predict how scenes evolve under interaction. They are most beneficial when trained on divers