Search: “evaluation”

Deep Learning for Atmospheric Turbulence Mitigation: A Comparison Between GANs and Transformers

arXiv:2610.19274v1 Announce Type: cross Abstract: Atmospheric turbulence creates complex spatial and temporal distortions that significantly reduce image quality. This work compares two deep learning

researcharxiv-cs-cv

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Deleting Code Without Losing Knowledge: Regenerative Software for Python Libraries

DGX agent

arXiv:2610.17197v1 Announce Type: cross Abstract: In the age of 'Software 3.0', when a complete program can be rewritten in minutes by an agent, the traditional approach of relying on code as the sole

model-releasesarxiv-cs-ai

15 Oct 2026

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Demystifying On-Policy Distillation: Where Does the Teacher's Advantage Live?

arXiv:2610.19145v1 Announce Type: new Abstract: On-policy distillation (OPD) is increasingly studied as a cheaper alternative to reinforcement learning, yet it remains a form of knowledge distillation

safetyarxiv-cs-lg

Diagnosing Low-Confidence Patient Profiles via Localized Harmful Covariate Shift Detection

arXiv:2610.19178v1 Announce Type: new Abstract: Before deploying clinical prediction models, their reliability must be assessed to ensure safe use. Errors may arise from distribution shifts between tr

Diff Diffusion: Predicting Edit Paths with Diffusion Models for Efficient Code Editing

arXiv:2610.17831v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) are appealing for code generation because they can update many tokens in parallel, yet many are optimized for

Discovering Undisclosed Concepts in LoRA Adapters for Diffusion-Based AIGC Models

arXiv:2610.18990v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) has made diffusion model personalization affordable and widely shareable, but it also creates moderation risks when harmful

local-aiarxiv-cs-lg

Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop

arXiv:2610.15692v2 Announce Type: replace Abstract: Large language models can produce fluent tu- toring dialogue, but whether they actually help students learn remains unclear. We present a process-ce

tutorialsarxiv-cs-cl

Do Perturbation Predictors Learn Gene Interactions? Diagnosing Extrapolation in Agentic Screening

arXiv:2610.18880v1 Announce Type: new Abstract: High-throughput perturbation screens increasingly use machine-learning models to predict the effects of gene combinations that were never measured. A di

agentsarxiv-cs-lg

DoReMe: Dual optimization of Reconstruction and Motion estimation for self-navigated free-breathing abdominal MRI using Gaussian Splatting

arXiv:2610.19120v1 Announce Type: cross Abstract: Purpose: Free-breathing abdominal MRI is limited by respiratory motion, which introduces image artifacts and k-space inconsistencies. Existing reconst

researcharxiv-cs-cv

DreamHMR: From Video Generation to Human Motion Modeling via Structural Focusing

arXiv:2610.20124v1 Announce Type: new Abstract: Human mesh recovery (HMR) provides a geometric foundation for understanding human motion, but accurately reconstructing both body motion and fine hand a

local-aiarxiv-cs-cv

DSABench: Benchmarking Source Discovery, Coordination, and Execution for Multi-Database Agents

arXiv:2610.14700v1 Announce Type: new Abstract: Most text-to-SQL benchmarks provide the target database. In a large data catalog, however, choosing the sources is part of the problem: an agent must fi

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DTDD: Divergence-Triggered Dynamic Distillation for Reliable On-Policy Supervision

arXiv:2610.19302v1 Announce Type: new Abstract: On-policy distillation (OPD) provides dense token-level supervision on student rollouts, but this supervision can become unreliable when the student and

safetyarxiv-cs-lg

Dynamic Conflict Clustering with Lightweight Learning and Strategic Repair for Distributed Constraint Satisfaction

arXiv:2610.15658v1 Announce Type: cross Abstract: Distributed Constraint Satisfaction Problems (DCSPs) model distributed decision-making in multi-agent systems, where agents assign values to local var

agentsarxiv-cs-ai

EarlyCommit: Calibrated Word-by-Word Commitment for Robots Acting Before You Finish Speaking

arXiv:2610.20531v1 Announce Type: new Abstract: Human listeners can often identify the intended object several words before an instruction ends. Robots, however, are typically designed to wait until t

tutorialsarxiv-cs-ro

ECMR: Evidence-Aware Deliberation Control for Multi-Agent LLM Reasoning

arXiv:2610.17869v1 Announce Type: new Abstract: Multi-agent Large Language Model (LLM) systems typically commit to a deliberation protocol before inference. A fixed protocol cannot allocate computatio

agentsarxiv-cs-ai

Efficient contextual partial monitoring with general function approximation

arXiv:2610.19804v1 Announce Type: new Abstract: We study finite stochastic partial monitoring (PM) games with side information, a paradigm of sequential learning with partial feedback. On each round t

local-aiarxiv-cs-lg

Embedding Geometry Shapes LLM Routing: Tracing Failure Modes and Improving Generalization

arXiv:2610.19198v1 Announce Type: cross Abstract: With the growing number of LLMs available, selecting which one to use for a prompt has become a key question. A large part of the routing literature r

Encrypted Skills Can Become New Security Exploits If AI Agents Know How to Decipher

arXiv:2610.18262v1 Announce Type: cross Abstract: Third-party skills can expose LLM agents to malicious instructions hidden by encoding. We introduce Ciphered Skill Injection (CSI), which embeds such

tutorialsarxiv-cs-ai

Engram Injection: A Study of Temporal Validity in Parametric Language-Model Memory

arXiv:2610.15882v1 Announce Type: new Abstract: A stored fact may stop being valid when a user changes a preference or an event replaces an earlier one. We study whether a language model can learn the

tutorialsarxiv-cs-ai

Enhanced Detective: A Dual-Stage Proactive Defense Against Internal Poisoning Attacks in Financial Fraud Detection Using Federated Learning

arXiv:2610.17523v1 Announce Type: cross Abstract: With recent developments in Artificial Intelligence (AI), the adoption of distributed learning paradigms such as Federated Learning (FL) has emerged.

EvoQuantLab: Training-Free Dual-Loop Evolution for Auditable Quantitative Research

arXiv:2610.17130v2 Announce Type: new Abstract: Automated alpha factor discovery is critical for modern quantitative research. While large language models (LLMs) have increasingly been integrated into

agentsarxiv-cs-ai

Exhaustive Canonical Skeletons Generation: A Formal Dataset for Decomposable Symbolic Regression

model-releasesarxiv-cs-lg

arXiv:2610.20108v1 Announce Type: new Abstract: Neural symbolic regression (SR) models require diverse datasets of mathematical expressions for robust training. However, existing datasets rely predomi

Explorer-Zero: Improving Self-Play for Long-Horizon Tasks with Decomposable Verifiable Rewards

arXiv:2610.19868v1 Announce Type: cross Abstract: Training LLM agents on long-horizon interactive tasks with reinforcement learning typically relies on human-annotated tasks and reliable verification,

agentsarxiv-cs-lg

Exploring Interpretability in Deep Learning-Based Forest Classification - Separating Similar Forest Classes using Sentinel-2 Time Series

arXiv:2610.19270v1 Announce Type: new Abstract: The ecological insurance theory posits that diverse forests are more resilient and better able to adapt to changing environmental conditions. Increasing

Exposing AI Inference as a Telco Network API over the 5G User Plane

arXiv:2610.15062v1 Announce Type: new Abstract: Supporting edge Artificial Intelligence (AI) inference as a network service is challenging because current mobile systems can transport tensors but do n

Extreme-Scale Super-Resolution of Homogeneous Turbulence from a Single Realization

arXiv:2610.20305v1 Announce Type: cross Abstract: Homogeneous turbulent flows exhibit recurring multiscale structures across spatially separated regions, suggesting that a single flow realization may

tutorialsarxiv-cs-lg

Eye, Robot: Learning Expressive Gaze Dynamics via a VLM-Guided Transformer-VAE

model-releasesarxiv-cs-ro

arXiv:2610.19635v1 Announce Type: new Abstract: Gaze coordinates attention in human interaction through coupled eye, head, and eyelid motion. A humanoid robot must choose where to look while generatin

FACT: A Multimodal Force-Action-Track Foundation Model for Human-to-Robot Dexterity

arXiv:2610.19155v1 Announce Type: new Abstract: Human demonstrations offer a scalable alternative to costly robot data collection for dexterous manipulation, but most human datasets lack force measure

agentsarxiv-cs-ro

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FARL: A Fully Automated Pipeline of RL Interface and Solver Design

arXiv:2610.15691v1 Announce Type: new Abstract: Existing reinforcement learning (RL) largely focuses on optimizing learning algorithms within a pre-defined task formulation, while applying RL to new t

safetyarxiv-cs-ai

Following the Flow the Law Requires: Training Voice Agents to Transfer to Unseen Regulated Procedures in Debt Collection

model-releasesarxiv-cs-cl

arXiv:2610.18881v1 Announce Type: new Abstract: Voice agents built on large language models (LLMs) now handle customer calls, but in regulated applications completing the task is not enough: the agent

Forget About It: Mitigating Forgetting Without Replay or Auxiliary Objectives

model-releasesarxiv-cs-lg

arXiv:2501.05559v2 Announce Type: replace Abstract: Have we made mitigating catastrophic forgetting more complicated than it needs to be? Continual adaptation often degrades performance on earlier tas

ForkGRPO: Efficient Exploration and Fine-Grained Credit Assignment for Diffusion Language Models

arXiv:2610.19408v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) have advanced rapidly, yet strengthening their reasoning through reinforcement learning (RL) remains an open cha

tutorialsarxiv-cs-cl

FPV-CRASH: A Dataset for Offline Crash Moment Localization in Drone First-Person-View Videos

arXiv:2610.19785v1 Announce Type: new Abstract: Crash Moment Localization aims to localize the major physical impact that interrupts controlled flight in an onboard first-person-view (FPV) video recor

local-aiarxiv-cs-cv

From Brewing to Resolution: Tracing the Internal Lifecycle of Code Reasoning in LLMs

model-releasesarxiv-cs-ai

arXiv:2606.17648v3 Announce Type: replace Abstract: Standard accuracy metrics cannot explain why LLMs handle variable tracking but fail on semantically equivalent loops. We study an internal lifecycle

From Caricature to Collective Artifact: How Persona Construction Drives Polarization in Generative Social Simulations

arXiv:2610.16498v1 Announce Type: cross Abstract: Generative Social Simulation (GSS) leverages Large Language Models (LLMs) to create sophisticated personas that define agents with demographics, emoti

From Conceptual EneMonIE to an Executable Backend: A Modular Architecture for Energy Information Extractionand Grounded Question Answering

arXiv:2610.17243v1 Announce Type: cross Abstract: The original EneMonIE proposal describes a Web-based semantic system for continuously monitoring energy trends through targeted information extraction

From Plato to Aristotle: Toward a General Theory of Representation Hypotheses

arXiv:2610.20286v1 Announce Type: new Abstract: The Platonic Representation Hypothesis (PRH) holds that increasingly capable models converge toward a common representation. However, recent studies hav

local-aiarxiv-cs-lg

From Triage to Impact: A Multi-Hop Reasoning Benchmark for Explainable Persian Hate Speech

model-releasesarxiv-cs-cl

arXiv:2610.20370v1 Announce Type: new Abstract: Hate speech has become increasingly prevalent on social media, raising concerns about its detection, interpretation, and moderation. Persian, a relative

Full-Order Safety for Nonlinear Reduced-Order MPC

model-releasesarxiv-cs-ro

arXiv:2610.19250v1 Announce Type: new Abstract: Reduced-order models (ROMs) make model predictive control (MPC) of high-dimensional nonlinear systems tractable, but the resulting modeling error can le

GAMW: Generation-Aware Mel-Domain Watermarking for TTS Traceability

arXiv:2610.15082v1 Announce Type: cross Abstract: As text-to-speech (TTS) systems continue to advance, provenance tracking and security verification of synthesized speech have become increasingly impo

Gap Detection: Mitigating Homogenization through Demand and Defensibility

arXiv:2610.20162v1 Announce Type: new Abstract: Language models often produce semantically similar answers to open-ended questions, even when many plausible alternatives exist. Generating useful alter

researcharxiv-cs-cl

Generalizable field of view extension for diffusion MRI via conditional flow matching

arXiv:2610.17401v1 Announce Type: new Abstract: Incomplete field-of-view (FOV) diffusion MRI (dMRI) acquisitions compromise whole-brain white matter analysis by excluding brain regions from tractograp

Genesis Steering: Better Activation Steering Through Training Data

model-releasesarxiv-cs-lg

arXiv:2610.19114v1 Announce Type: new Abstract: Activation steering controls large language models at inference time, but its effectiveness depends on the choice of reference data. We introduce genesi

GenState-AI: State-Aware Dataset for Text-to-Video Retrieval on AI-Generated Videos

model-releasesarxiv-cs-cv

arXiv:2603.14426v2 Announce Type: replace Abstract: Existing text-to-video retrieval benchmarks often permit matching from static appearance, making it difficult to determine whether models capture st

GeoCloak: An Agentic Framework for Semantics-Preserving Geolocation Privacy via Peripheral Clue Manipulation

arXiv:2610.20055v1 Announce Type: new Abstract: The rapid advancement of large vision language models (LVLMs) has made geolocation inference from images highly accurate and accessible. This poses seri

agentsarxiv-cs-cv

GeoThinker-F: Endogenous Predictive World Representations for Fast Spatial Intelligence

arXiv:2610.20592v1 Announce Type: new Abstract: Existing geometry-aware Multimodal Large Language Models (MLLMs) increasingly rely on external 3D encoders to provide structural priors, but executing t

tutorialsarxiv-cs-cv

Graph Coarsening Enables Escaping Local Optima in Compute-Constrained Nonconvex MAX-CUT

model-releasesarxiv-cs-cl

arXiv:2610.19043v1 Announce Type: cross Abstract: Because its binary optimization landscape contains exponentially many local optima, MAX-CUT is highly sensitive to initialization. We study Particle P

Graph-Enhanced Disease Trajectory Discovery and Temporal Endpoint Forecasting from Longitudinal Electronic Health Records

arXiv:2610.20502v1 Announce Type: new Abstract: Longitudinal electronic health records (EHRs) can reveal disease-progression structure, while useful forecasting requires leakage-controlled discovery,