Search: “evaluation”

Dutch Books for Language Models

arXiv:2609.02797v1 Announce Type: cross Abstract: People increasingly use language models to support life decisions. Many such decisions involve a probabilistic forecast: How likely is a major life ev

frb100-40 After Two Decades: An Optimality Certificate and a Preregistered Search Study

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DGX agent

arXiv:2609.02804v1 Announce Type: cross Abstract: For more than 20 years, the Model-RB benchmark frb100-40 remained an open challenge; since 2014, its public record had stood at 99 of 100 variables. W

model-releasesarxiv-cs-ai

3 Sept 2026

From Detection to Characterization: A Large-Scale Study of Ragebait on Japanese X

arXiv:2609.02262v1 Announce Type: cross Abstract: Ragebait refers to online content intentionally designed to provoke anger or outrage and thereby increase attention and engagement. However, reliable

researcharxiv-cs-cl

FuDU: A Fuzzy Dual-dimensional Uncertainty Framework for Streaming Active Learning in Industrial Defect Detection

arXiv:2609.02212v1 Announce Type: new Abstract: Ensuring the reliability of deep learning models in real-time industrial defect detection is critical for high-stakes quality inspection. To mine uncert

researcharxiv-cs-cv

Applications

General Demographic Pre-trained Models for Enhancing Predictive Performance Across Diseases and Population

arXiv:2509.07330v3 Announce Type: replace-cross Abstract: Foundation models for healthcare require balancing robust generalization across heterogeneous clinical populations and disease settings with t

applicationsarxiv-cs-ai

GPT-6 Astra is the most intelligent and aligned model in the world, and sets a new state of the art for computer use, browsing, software eng…

GPT-6 Astra is the most intelligent and aligned model in the world, and sets a new state of the art for computer use, browsing, software engineering, cybersecurity, science, and professional work. htt

model-releasesopenai--x

HeadWiseKV: Budgeted Per-Head Cache Residency for Hybrid Long-Context Language Models

arXiv:2609.02029v1 Announce Type: new Abstract: Long-context inference retains a growing key--value (KV) cache during decoding, which consumes substantial GPU memory and can reduce generation throughp

local-aiarxiv-cs-ai

Hearing the Whispers: Black-Box Membership Inference Attacks on Finetuned TTS Models

arXiv:2609.01723v1 Announce Type: cross Abstract: Text-to-Speech (TTS) foundation models are increasingly fine-tuned on private datasets to synthesize highly personalized voices, introducing severe pr

InfraPatch: Cross-Task Targeted Grayscale Patch Attacks on Infrared-Adapted Vision-Language Models

arXiv:2609.02233v1 Announce Type: cross Abstract: Infrared vision-language models (IR-VLMs) have emerged as a promising paradigm for multimodal perception under low-visibility conditions, yet their ro

local-aiarxiv-cs-ai

Interpretable Symptom Vectors for Depression in a Large Language Model

arXiv:2609.01832v1 Announce Type: cross Abstract: Patients with depression present with diverse symptom profiles, yet clinical practice routinely reduces this variation to a single severity score. Lar

Learning-Based Reconstruction Attacks on Coordinate-Obfuscated Point Clouds

arXiv:2609.02568v1 Announce Type: cross Abstract: Volumetric video based on point cloud representations enables immersive virtual and augmented reality applications but introduces significant challeng

researcharxiv-cs-lg

Learning Evidence Sufficiency Boundaries for Selective Answering in Grounded Multi-Hop QA

arXiv:2609.01687v1 Announce Type: new Abstract: Grounded question answering systems should answer only when the supplied evidence supports the answer. In multi-hop QA, this requirement is difficult be

researcharxiv-cs-cl

Morphology signal in whole slide image foundation models can automatically triage slides

model-releasesarxiv-cs-cv

arXiv:2609.01987v1 Announce Type: new Abstract: Patient exams in the cancer diagnosis and staging process typically generate several whole slide images (WSIs). One of the initial steps in training mod

Agents

Multi-Agent Retrieval-Augmented Generation for Efficient Cloud Knowledge Base Search in Telecom SNOC Environment

arXiv:2609.01618v1 Announce Type: cross Abstract: Telecom Service and Network Operations Centers (SNOCs) rely on large collections of cloud documents, including Standard Operating Procedures (SOPs), v

agentsarxiv-cs-lg

NE-R1: Enhancing Named Entity Recognition Model via Reinforcement Learning

arXiv:2609.02366v1 Announce Type: cross Abstract: Named Entity Recognition (NER) has achieved substantial progress since the advent of large language models (LLMs). Nevertheless, the recognition of lo

Agents

NS-Copilot: An LLM-Driven Agent System for Autonomous Neuroscience Analysis

arXiv:2609.01971v1 Announce Type: new Abstract: AI is rapidly advancing neuroscience, yet many laboratories fail to fully unleash its potential due to significant interdisciplinary barriers. While pre

agentsarxiv-cs-cl

Online Reinforcement Learning in the Met Office Unified Model through Distributed Model-Agent Coupling

arXiv:2609.02566v1 Announce Type: new Abstract: Machine-learnt corrections can complement numerical weather prediction only if they adapt to the evolving model state while preserving dynamical consist

local-aiarxiv-cs-lg

Paper Instruments benchmarked sandbox providers for their RL rollouts, and E2B's tool execution came in up to 3x faster than every other san…

Paper Instruments benchmarked sandbox providers for their RL rollouts, and E2B's tool execution came in up to 3x faster than every other sandbox provider they tested, reducing idle GPU time and traini

safetyyohei-nakajima--x

PaperCompiler: Faithful Paper-to-Code Generation via Repository-Level Specification Compilation

arXiv:2609.02272v1 Announce Type: cross Abstract: Faithfully translating research papers into repository-level implementations remains challenging because papers often describe methods at a high level

Tutorials

Physics-Driven Independent Pair Generation for Iterative Self-Supervised Low-Dose CT Denoising

arXiv:2609.02654v1 Announce Type: new Abstract: Low-dose computed tomography (LDCT) measurements contain mixed Poisson-Gaussian noise. However, most self-supervised methods rely on generic image stati

tutorialsarxiv-cs-cv

PIE-APT: Abductive Planning over Temporal Dynamic Knowledge Graphs via Incremental Reasoning

arXiv:2607.27287v2 Announce Type: replace Abstract: Planning over Temporal Dynamic Knowledge Graphs (TDKGs) presents theoretical challenges in open-world environments with incomplete information. Exis

Private Computation Space: Experience with Trusted Multi-Cluster Federated Learning for Agriculture

arXiv:2609.01667v1 Announce Type: cross Abstract: Artificial Intelligence has shown to help improve agricultural practices, yet adoption remains limited: 69% of U.S. farmers have privacy concerns with

researcharxiv-cs-lg

PRO-Step: Step-level Process Reward Optimization for Retrieval-Augmented Generation

arXiv:2609.01658v1 Announce Type: cross Abstract: Retrieval-Augmented Generation enhances Large Language Models by grounding responses in external knowledge, but multi-hop reasoning remains vulnerable

safetyarxiv-cs-ai

Quantum MeanFlow: single-shot generative sampling on NISQ hardware

arXiv:2609.02186v1 Announce Type: cross Abstract: Quantum generative models offer a promising framework for exploring whether quantum computation can enhance generative machine learning. Flow matching

RecKAN: Kolmogorov-Arnold Networks with a Learnable Recursive Polynomial Basis

arXiv:2609.01729v1 Announce Type: cross Abstract: Kolmogorov--Arnold Networks (KANs) replace the fixed scalar weights of a standard network with learnable univariate functions on each edge, but existi

Reinforcement Learning and Rule-Based Peer-to-Peer Pricing in Residential PV-BES Communities

arXiv:2609.01680v1 Announce Type: new Abstract: This paper compares rule-based and learning-based pricing mechanisms for peer-to-peer (P2P) electricity trading in residential photovoltaic communities.

Repo-To-Skill: Distilling GitHub Repositories Into AI4AI Skills

arXiv:2609.02749v1 Announce Type: new Abstract: Autonomous agents are beginning to carry out machine-learning (ML) research end to end. These agents combine a model backbone with a harness for plannin

Reviewing the Reviewer: LLM-Assisted Reviewer Feedback Generation for Guideline Compliance

arXiv:2602.10118v2 Announce Type: replace Abstract: Peer review is central to scientific quality, yet reliance on simple heuristics, namely lazy thinking and non-specific critiques, has threatened rev

researcharxiv-cs-cl

Applications

RGB-to-IR image translation for infrared vehicle detection in unseen UAV domains

arXiv:2609.02556v1 Announce Type: new Abstract: Synthetic training data is crucial for developing vision AI when real-world data is scarce, as in thermal infrared (IR) aerial vehicle detection. While

applicationsarxiv-cs-cv

Seed-Anchored Budget-Bounded Graph Rendering for Question Answering on Industry-Standard Power-Grid Information and Exchange Models

arXiv:2609.02011v1 Announce Type: cross Abstract: Large language model question answering over power-grid models must respect a fixed context budget. We introduce seed-anchored graph rendering, a dete

local-aiarxiv-cs-ai

Selective Knowledge Edit Reversal via Gated Singular Vector Shrinkage

model-releasesarxiv-cs-cl

arXiv:2609.02091v1 Announce Type: new Abstract: Knowledge editing provides an efficient way to update factual knowledge in large language models. However, malicious edits may introduce safety risks, m

Signal or Noise? Auditing Rotation-Induced Saliency Drift in Medical and Aerial Imaging

arXiv:2609.02224v1 Announce Type: cross Abstract: Post-hoc saliency maps such as Grad-CAM are increasingly used to audit why a deployed vision model made a decision, yet the heatmap drifts when the in

safetyarxiv-cs-ai

Sim2Signal: Sim-to-Real Benchmarks for Traffic Signal Control

arXiv:2609.01676v1 Announce Type: new Abstract: Reinforcement learning achieves strong traffic signal control performance in simulation, yet policies trained in simulators often fail once deployed in

SkillGLoW: Procedural-Family Skill Consolidation for Self-Improving Agents on Long-Horizon Task Streams

arXiv:2609.02217v1 Announce Type: new Abstract: LLM agents increasingly self-improve by writing and reusing textual skills, kept either as one global document or as a flat pool of per-task entries, th

SSAKG 2.0: An Open-Source Package for Structural Associative Sequence Memory and Context-Based Retrieval

arXiv:2609.01849v1 Announce Type: new Abstract: This article presents SSAKG 2.0, an open-source software package for constructing and operating Structural Sequential Associative Knowledge Graphs (SSAK

T2LSC-Bench: Benchmarking Localized Semantic Control in Text-to-Image Generation

model-releasesarxiv-cs-cv

arXiv:2609.02255v1 Announce Type: new Abstract: Recent text-to-image models have become increasingly capable of rendering explicit text, but reliable localized text control requires more than generati

text2ql: Multi-Target Natural Language Querying via a Language-Agnostic Intermediate Representation

arXiv:2609.02115v1 Announce Type: cross Abstract: Natural language interfaces to databases have traditionally suffered from three structural limitations: exclusive targeting of relational SQL, uncondi

Thinking in Pictures: A Systematic Benchmark for Reasoning-driven Image Generation

model-releasesarxiv-cs-cv

arXiv:2609.02864v1 Announce Type: new Abstract: Recent advancements in unified generative models (UGMs) and world simulators have achieved unprecedented results in visual perception and synthesis. How

TikZilla: Scaling Text-to-TikZ with High-Quality Data and Reinforcement Learning

arXiv:2603.03072v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to assist scientists across diverse workflows. A key challenge is generating high-quality figures

Towards One-for-All Robustness Across a Continuum of Threat Levels

arXiv:2609.02440v1 Announce Type: cross Abstract: Adversarially robust models often overfit to a specific attack budget, necessitating multiple specialized models for diverse and dynamic adversarial e

Towards Trustworthy Autonomous Robots: An Explainable AI-Based Decision Framework

arXiv:2609.02861v1 Announce Type: cross Abstract: Autonomous robots powered by deep learning face a fundamental auditability challenge: when incidents occur, investigators cannot reconstruct why the s

safetyarxiv-cs-ai

Tri-Band Channel Measurement-Enabled Multi-Layer Digital Twin for Terahertz Wireless Data Centers

arXiv:2609.01699v1 Announce Type: new Abstract: The rapid growth of AI computing has driven increasing demands for flexible and high-capacity data-center interconnections. Owing to its ultra-wide band

researcharxiv-cs-lg

TriSAR: Task Coordination and Collision Avoidance for Aerial Robot Teams in Disaster Response

arXiv:2609.01731v1 Announce Type: new Abstract: Multi-Unmanned Aerial Vehicle (UAV) disaster-response systems require coordinated task assignment and local trajectory control, yet the individual and c

safetyarxiv-cs-ro

User Feedback Provides a Unique Signal that LLMs Can not Detect

arXiv:2609.02859v1 Announce Type: new Abstract: Harnessing naturally occurring feedback from user interactions offers a promising learning signal for Large Language Models (LLMs). However, recent stud

safetyarxiv-cs-cl

WaveSync: Constrained Wavefront Optimization for Synchronized Co-Speech Gestures in Humanoid Robots

arXiv:2606.16600v2 Announce Type: replace Abstract: Expressive co-speech gestures are crucial for natural human--robot interaction, yet generating them on physical humanoid robots remains challenging

safetyarxiv-cs-ro

WiFlow: Estimating Optical Flow using WiFi Channel State Information

arXiv:2609.02452v1 Announce Type: new Abstract: Knowing where and how fast objects are moving within a scene is important across various domains. Usually, cameras are used to capture the data necessar

researcharxiv-cs-cv

ZETA: A Controlled Study of Zero-Shot Cross-Embodiment VLA Transfer for Tabletop Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.02546v1 Announce Type: new Abstract: Zero-shot generalization to unseen embodiments is important for generalizable vision-language-action (VLA) models as robot hardware evolves and task-spe

A Checklist to assess the energy and carbon impacts of ML/AI applications in Earth System Modeling

arXiv:2609.00847v1 Announce Type: cross Abstract: As machine learning and artificial intelligence find their way into nearly every aspect of climate, weather, and Earth system modeling, it is worth pa