Search: “models”

Discovery of fully efficient fault indicators along a data-based diagnosis process

arXiv:2609.28087v1 Announce Type: new Abstract: The integration of model-based and data-driven paradigms provides a powerful framework for fault diagnosis by combining the interpretability of analytic

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Evaluation Choices Decide the Forecasting Leaderboard: Evidence from a Production Marketplace Panel

DGX agent

arXiv:2609.27867v1 Announce Type: new Abstract: A forecasting benchmark reports which method won. We show that the answer is set by the evaluator's choices before any model is fitted. We benchmark 24

model-releasesarxiv-cs-lg

24 Sept 2026

Research

EvoAudio: Recursive Self-Improvement for Audio Understanding

arXiv:2609.27389v1 Announce Type: cross Abstract: Audio language models understand what is said far better than how it sounds. Closing this gap takes more than data. Detailed acoustic annotation is co

researcharxiv-cs-lg

Fed-ReMasker: Federated Tabular Imputation under Feature-Level Missingness

arXiv:2609.28105v1 Announce Type: cross Abstract: Multi-center clinical studies and biomedical research collaborations increasingly seek to utilize data across centers to build models that generalize

Guides That Cause Actions: An Offline Study of Guide-Action Mutual Reinforcement in Multimodal Web Agents

arXiv:2609.27353v1 Announce Type: new Abstract: Web agents are usually evaluated in live environments, where environment state and judge models drift between runs, so the same checkpoint rarely reprod

I-SplineFlow: Learning Monotone Spline Stochastic Interpolant Schedulers for Few-Step Generation

arXiv:2609.27963v1 Announce Type: new Abstract: Few-step generation with pretrained diffusion and flow models can be accelerated by lightweight training that optimizes the sampling trajectory rather t

Learning Stiffness Dependent Fluid Structure Dynamics from Coarse Flow Representations

arXiv:2609.26816v1 Announce Type: cross Abstract: This paper develops a data-driven framework for long-term prediction of fluid--structure interaction (FSI) dynamics, focusing on the flow-induced vibr

Research

Linear RNN Scaling Laws: When Longer Sequences Beat More Sequences

arXiv:2609.27964v1 Announce Type: new Abstract: Empirical scaling laws for autoregressive language models relate prediction loss to model size, data size, and optimization compute, but their theoretic

researcharxiv-cs-lg

PASTABench: Proactive Assessment of Sequential Trajectories for Agent Safety

arXiv:2609.28197v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into autonomous agents that alter real-world states, ensuring operational safety across multi-step workflows has

SafeTutors: Benchmarking Pedagogical Safety in AI Tutoring Systems

arXiv:2603.17373v2 Announce Type: replace Abstract: Large language models are rapidly being deployed as AI tutors, yet current evaluation paradigms assess problem-solving accuracy and generic safety i

The Tasteful Agent: Measuring and Improving Taste in Long-Horizon Tasks

arXiv:2609.25804v2 Announce Type: replace Abstract: LLM agents increasingly work on long-horizon tasks, and the decisions they make along the way, such as which hypothesis to test or which implementat

Validation and Simulation Catch Different Errors: Four Levels of Evaluation for LLM-Generated Circuits

arXiv:2609.26830v1 Announce Type: cross Abstract: Simulation success is not equivalent to structural correctness for LLM-generated circuits. We define and measure four evaluation levels -- schema vali

Component Type, Not Reconstruction Error, Predicts Attention Quantization Sensitivity

arXiv:2609.26173v1 Announce Type: new Abstract: Many post-training quantization (PTQ) methods use layer-wise reconstruction, second-order proxy objectives, or activation-aware transformations to reduc

Discrete vs. Continuous: A Comprehensive Study of Unified Audio Understanding in LALMs

arXiv:2609.22851v2 Announce Type: cross Abstract: Large Audio Language Models (LALMs) utilize either continuous features or discrete tokens, yet the optimal representation paradigm for general audio u

Do Not Trust the Benchmark: Limitations of General LLM Rankings and a Case for Task-Specific Evaluation

arXiv:2609.23201v1 Announce Type: new Abstract: Benchmark scores increasingly influence the development, marketing, and selection of large language models (LLMs). Yet an overall score is interpretable

From Capability to Assurance in Autonomous Penetration-Testing Harnesses: A Framework and Reference Implementation

arXiv:2609.22664v1 Announce Type: cross Abstract: Research on large language model agents for penetration testing is evaluated almost entirely by capability: whether the agent captures a flag or repro

Hill Sampling for Test-Time Scaling: A Simple and Better Alternative to Repeated Sampling, Evolution, and Training

arXiv:2609.25510v1 Announce Type: new Abstract: Large language models (LLMs) can improve solutions to verifiable scientific and algorithmic problems by spending additional computation at test time. Re

MATE: Policy-Aware Security Auditing for Mobile Agents via Synthesis-Driven Trajectory Learning

arXiv:2609.22724v1 Announce Type: cross Abstract: Mobile agents powered by foundation models now automate complex, multi-step workflows on real devices, but their trajectories can violate app-specific

Metric-Bench: Exploring In-context Spatial Metric Reasoning in VLMs for Indoor Scenes

arXiv:2609.25841v1 Announce Type: new Abstract: Metric reasoning is a critical and challenging task for Vision Language Models (VLMs), playing a pivotal role in embodied AI tasks such as robotic manip

Optimizing Canaries for Privacy Auditing with Metagradient Descent

arXiv:2507.15836v2 Announce Type: replace Abstract: In this work we study black-box privacy auditing, where the goal is to lower bound the privacy parameter of a differentially private learning algori

Reasoning Topology Matters: A Controlled Study of LLM-Based Cybersecurity Analysis

arXiv:2609.24710v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in cybersecurity, where accurate analysis often requires multi-step and context-dependent reasoning

Research

ReasonLab: A Controlled and Auditable Evaluation of Prompting Techniques for Multiple-Choice QA

arXiv:2607.14109v2 Announce Type: replace Abstract: Probing the capabilities of Large Language Models (LLMs) and building robust solutions for Multiple-Choice Question Answering (MCQA) remain central

researcharxiv-cs-cl

Terminal Shrinkage Averaging Reveals a Schedule-Estimator Interaction in LLM Pretraining

arXiv:2609.25482v1 Announce Type: new Abstract: Large language model (LLM) pretraining conventionally returns the raw final iterate. This couples two design choices: the learning-rate schedule that ge

TV-AudioRemover: Joint Text-Visual Guided Sound Removal with Multi-Task Hard-Mixture Curriculum

arXiv:2609.25864v1 Announce Type: cross Abstract: Visual object removal can eliminate a target from video frames, yet its acoustic trace persists in the soundtrack, causing obvious audio-visual incons

0.5%>100%: Bidirectional Reciprocal Learning for Referring Image Segmentation

arXiv:2609.24510v1 Announce Type: new Abstract: Recent advances in vision foundation models (VFMs) have shown remarkable capabilities across diverse unimodal visual tasks. However, adapting VFMs to re

Artificial Structure Function Search: Preserving Artificial Functional Connectivity for Structured Pruning

arXiv:2609.24401v1 Announce Type: new Abstract: Structured pruning is a model compression technique that is used to reduce the computational cost of deploying deep neural networks on resource-constrai

BabelArena: A Large-Scale Multilingual Benchmark for LLM Agents

arXiv:2609.23490v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly execute multi-step workflows through tool use and interaction with users and environments. However, curre

ChemCLIR-Bench: Benchmarking Cross-Lingual Information Retrieval in Multilingual Chemical Patents

arXiv:2609.23231v1 Announce Type: new Abstract: Cross-lingual information retrieval (CLIR) is increasingly important in multi-national industries, where critical technical evidence may exist in a diff

CleanScore: Black-Box Benchmark Audits with Negative Controls and Sensitivity Bounds

arXiv:2609.22183v1 Announce Type: new Abstract: Public benchmark scores may reflect skill, prior exposure to the questions, or both, and for most models the training data are unknown. We present Clean

Safety

D-IMPL: A Diffusion-based Solver for Parameterized BBOs

arXiv:2609.22752v1 Announce Type: new Abstract: Diffusion models have demonstrated strong power in generative modeling tasks across multiple domains, exhibiting a remarkable capability of learning com

safetyarxiv-cs-lg

'Dear LLaVA, Please Drive': A Depth-Aware Vision-Language Agent for Closed-Loop Robotic Control

model-releasesarxiv-cs-ro

arXiv:2609.22925v1 Announce Type: new Abstract: Vision-language models (VLMs) provide a compelling foundation for reasoning-driven mobile navigation, offering rich contextual understanding and strong

Enabling Vision and Cross-Modal Learning for Multimodal Stroke Recurrence Prediction: An Interpretable Two-Step Framework

arXiv:2609.22271v1 Announce Type: new Abstract: Multimodal stroke recurrence prediction requires effective integration of heterogeneous clinical and imaging data, yet modality imbalance often causes m

Euston: Training Away Mathematical Sycophancy Without Losing the Mathematics

arXiv:2609.23205v1 Announce Type: new Abstract: Reasoning language models are trained to produce solutions, not to refuse them, and this bias persists when the problem they are handed is false. Asked

Explain Less, Understand More: Data-Efficient Personalization of Reader-Dependent Jargons

arXiv:2505.16227v4 Announce Type: replace Abstract: Personalizing jargon detection and explanation is essential for making technical documents accessible to readers with diverse disciplinary backgroun

Fairness Beyond Anonymization? Demographic Leakage in German LLM-Generated Resumes

arXiv:2609.22188v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into AI-assisted hiring pipelines, including automated resume generation and screening. Under t

Glass-Box Deep Learning for FDIA Detection in Nonlinear Automatic Generation Control: A Kolmogorov-Arnold Network Approach

arXiv:2509.05259v2 Announce Type: replace Abstract: Automatic Generation Control (AGC) plays a critical role in maintaining power balance across multi-area power systems. However, its complete relianc

Holographic generative flows with AdS/CFT

arXiv:2601.22033v2 Announce Type: replace Abstract: Holography, in the form of the anti-de Sitter/conformal field theory (AdS/CFT) correspondence, offers a natural setting for generative modelling. Da

LoRA-generating hypernetworks for efficient on-device LLM generative personalization

arXiv:2609.24979v1 Announce Type: new Abstract: On-device large language models (`LLMs'), e.g. running on mobile phones, are ripe for improvement via personalization. The limited compute resources of

Machine-Interpretable Information: Compiling Documents into Searchable and Readable Protocol States

arXiv:2609.23371v1 Announce Type: new Abstract: Long-context language models interface with external knowledge through raw natural language. In retrieval-augmented systems, this creates a persistent i

MCP-GRANITE Benchmark: GRANularity Interface TEsting for MCP-Based LLM Agents

arXiv:2609.24161v1 Announce Type: cross Abstract: As LLM agents increasingly interact with external tools through standardized protocols such as MCP, tool-interface design becomes a critical yet under

MIS-Bench: Benchmarking Multimodal LLMs for Psychotherapeutic Interpersonal Skills Assessment

arXiv:2609.22778v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly used as evaluators, yet their reliability in professional assessment tasks that require expert

Omni2Web: Benchmarking Audiovisual Website Development

arXiv:2609.23417v1 Announce Type: cross Abstract: Screen-recorded web editing requests contain weak deictic expressions such as ``this'' and ``there,'' whose referents depend on speech, cursor traject

onPanda: Efficient Annotation of On-Policy Alignment Data for LLMs and Agents via Token-Level Correction

arXiv:2609.24983v1 Announce Type: new Abstract: We present onPanda, an interactive tool for efficiently annotating LLM alignment data and agent trajectories. onPanda adopts token-level correction as i

Opinion Leader Dynamics: How Sparse Attention Shapes Token Clustering

arXiv:2609.24202v1 Announce Type: new Abstract: Sparse attention reduces the quadratic cost of global self-attention while retaining strong empirical performance, but how its restricted interactions s

Safety

Reinforcement Learning Inspired Black-box Adversarial Attacks for Computer Vision

arXiv:2609.24249v1 Announce Type: cross Abstract: Neural networks, both convolution or transformer based, are essential for modern computer vision systems. However, they are vulnerable to small pertur

safetyarxiv-cs-cv

Replication Without Persistence in Hosted LLMs: Measurement Sensitivity in Action-Time Belief Evaluation

arXiv:2609.22478v1 Announce Type: cross Abstract: Behavioural evaluations of hosted language models can vary because the evaluated service, the measurement instrument, or both differ across runs. We s

Resist, Update, Reject: Preference Optimization Installs a Prior-Dependent Reliability Switch

arXiv:2609.22359v1 Announce Type: new Abstract: An aligned model asked to hold its answer against a manipulative source must still update on a reliable one and reject an unreliable one: resistance, re

RS-Claw-Evolution: Environment-Feedback-Driven Evolution for Lightweight Remote Sensing Agents in Long-Horizon Tasks

arXiv:2609.22258v1 Announce Type: cross Abstract: Large language model-driven remote sensing (RS) agents offer a promising approach to automating geospatial analysis. However, lightweight RS agents ba