Search: “models”

Relation Before Entity: Deferred Commitment in Language Model Factual Recall

arXiv:2609.17537v1 Announce Type: new Abstract: We ask whether relation-type information (e.g., capital-of) and entity-specific information (e.g., France to Paris) become causally active at the final-

researcharxiv-cs-cl

17 Sept 2026

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rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference

DGX agent

arXiv:2609.19104v1 Announce Type: cross Abstract: Factory work is a promising early scenario for embodied AI: assigning repetitive manual jobs to robots has clear economic payoff, and a structured sta

safetyarxiv-cs-ai

17 Sept 2026

Understanding LLM Failures: A Multi-Tape Turing Machine Analysis of Systematic Errors in Language Model Reasoning

arXiv:2602.15868v3 Announce Type: replace Abstract: Large language models (LLMs) exhibit failure modes on seemingly trivial tasks. We propose a formalisation of LLM interaction using a deterministic m

local-aiarxiv-cs-cl

17 Sept 2026

Det-LIME: Detector-Aware, Multi-Instance Local Interpretable Model-Agnostic Explanations for Automated Marine Mammal Detection

arXiv:2609.17479v1 Announce Type: cross Abstract: Despite the rapid uptake of black-box object detectors in marine mammal research and monitoring, explainability techniques are rarely integrated into

local-aiarxiv-cs-ai

Applications

Finding Common Mistakes In Modelling With Mathematical Formalisms Using LLMs

arXiv:2609.17111v1 Announce Type: cross Abstract: Modelling with mathematical formalisms like logical formulas, mathematical equations, or regular expressions is an important yet challenging task for

applicationsarxiv-cs-ai

From Manual Construction to AI-Driven Scenario Emergence: Rethinking Catastrophe Risk Modeling

arXiv:2609.16493v1 Announce Type: new Abstract: Traditional catastrophe (CAT) risk models rely on costly manual construction to generate extreme weather scenarios, an approach largely unchanged since

researcharxiv-cs-ai

Gaussian Processes for Modelling Spatial Fields with Robot Swarms

arXiv:2609.17463v1 Announce Type: new Abstract: Robot swarms, by virtue of their decentralised architecture, are a natural tool for scalable, robust modelling of spatial fields, such as water temperat

local-aiarxiv-cs-ro

little m: An AI Agent for Industrial Process Optimization

arXiv:2609.16680v1 Announce Type: new Abstract: Manufacturing consumes one third of global energy and still has significant room for improvement in terms of energy efficiency. Optimal process control

An Uncertainty-Aware Hybrid Mathematical-Machine-Learning Model for Smart Irrigation Decision Support

arXiv:2609.13864v1 Announce Type: new Abstract: Agriculture accounts for roughly 70% of global freshwater withdrawals, yet irrigation is still commonly scheduled reactively, with no forecast of where

Can a Neural Encoding Model Replicate an fMRI Visualization Study?

arXiv:2609.15685v1 Announce Type: cross Abstract: Most knowledge of graphical perception comes from behavioral studies. Understanding from a neural perspective is much more limited due in part to neur

safetyarxiv-cs-cv

Applications

Data storytelling meets interpretable machine learning: Decoding AI decisions for non-experts without revealing sensitive data and model details

arXiv:2609.15722v1 Announce Type: new Abstract: AI-driven automated decision-making requires both predictive performance and interpretability. Recent advances in interpretable machine learning (IML) p

applicationsarxiv-cs-ai

Diffusion Trajectory Modeling for Semantic Correspondence

arXiv:2609.15357v1 Announce Type: new Abstract: Diffusion models generate images through an iterative diffusion process, and recent studies have demonstrated that the intermediate feature maps produce

Evaluating LLM-Generated Rules for Heart Disease Prediction

arXiv:2609.13192v1 Announce Type: new Abstract: This study compares traditional machine learning models and Large Language Model (LLM)-generated rule-based systems for heart disease prediction using t

Mobile Multi-Robot Navigation under Runtime Uncertainty via Koopman Operator Learning and Nonlinear Model Predictive Control

arXiv:2609.14058v1 Announce Type: new Abstract: In this work, we developed a nonlinear model predictive control (NMPC) framework that employs learned dynamics via the Koopman Operator theory for mobil

researcharxiv-cs-ro

Beyond ID Embeddings: Process-Grounded Language Modeling for Cognitive Diagnosis

arXiv:2609.12403v1 Announce Type: cross Abstract: Cognitive Diagnosis Models (CDMs) play a pivotal role in personalized online learning. Traditional CDMs rely on discrete, ID-based embeddings to repre

researcharxiv-cs-cl

14 Sept 2026

Global Path Planner with Multi-Model Switching

arXiv:2609.13015v1 Announce Type: new Abstract: This work enhances global path planning via a pure-pursuit controller with multi-model kinematic switching that sustains plan fidelity across diverse te

researcharxiv-cs-ro

14 Sept 2026

Towards Sustainable Hydrogen Systems: Supply Chain Optimization with Model Predictive Control and Reinforcement Learning

arXiv:2609.11933v1 Announce Type: cross Abstract: Hydrogen supply chains are expected to play a central role in future low-carbon energy systems by enabling renewable energy integration, long-duration

14 Sept 2026

An Open Recipe for IMO Gold: Training Nemotron for Olympiad Mathematics

arXiv:2609.10712v1 Announce Type: new Abstract: We study how model post-training and test-time inference design affect natural-language proof generation for hard olympiad mathematics. Starting from Ne

12 Sept 2026

Beyond Surface Imitation: Contrastive Modeling for Reasoning Path Alignment in Multimodal In-Context Learning

arXiv:2609.10177v1 Announce Type: new Abstract: In-context learning (ICL) is widely used in multimodal large language models (MLLMs) and achieves strong performance across a wide range of multimodal t

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Dynamic language model representations for multi-objective reaction optimisation

arXiv:2609.11790v1 Announce Type: new Abstract: Optimising chemical reactions across multiple objectives, such as yield, selectivity, and safety, is central to chemical synthesis, and model-driven app

FastMap: Real-Time Semantic Map Completion via Bitwise Masked Modeling

model-releasesarxiv-cs-cv

arXiv:2506.07350v2 Announce Type: replace-cross Abstract: Semantic map completion, which predicts the layout of unobserved regions from partial observations, is a critical capability for indoor robot

Kalman Filtering Based Flight Management System Modeling for AAM Aircraft

model-releasesarxiv-cs-ro

arXiv:2602.14948v2 Announce Type: replace Abstract: Advanced Air Mobility (AAM) operations are planned to utilize strategic flight planning services that predict temporal uncertainties to validate fli

Applying foundation model embeddings towards urban livability evaluation

arXiv:2609.09429v1 Announce Type: new Abstract: While accurate measurement of socioeconomic indicators remains challenging in data-scarce regions, which limits policy interventions and resource alloca

Elastoformer: Enabling Dynamic Adaptivity via Elastic Model Transformation

arXiv:2609.10018v1 Announce Type: new Abstract: EdgeAI systems are increasingly employing computer vision applications to enable intelligent, on-device decision-making in real-time. However, these dep

local-aiarxiv-cs-cv

Fine-Tuning a KV Cache Concatenation-Aware Model or Recomputing KV Caches? Why Not Both?

model-releasesarxiv-cs-cl

arXiv:2609.09768v1 Announce Type: cross Abstract: In Retrieval-Augmented Generation (RAG) systems, a large number of retrieved chunks are concatenated to form the input context so that users can recei

Physics-Informed Multi-Task Surrogate Model for the Martian Nightside Thermosphere

arXiv:2609.10077v1 Announce Type: cross Abstract: Modeling the Martian nightside thermosphere remains challenging due to sparse in situ sampling and strong coupling among transport, magnetic, and seas

Agents

TamilEOT: A Dataset and Model for Semantic End-of-Turn Detection in Tamil Telephone Speech

arXiv:2609.05631v1 Announce Type: cross Abstract: A voice agent has to decide, at every pause, whether the user has finished speaking. Without a model of the language that decision falls back to a fix

agentsarxiv-cs-ai

We're Cooked! - Probing LLM Political Alignment Via Conflict-Framed Recipe Translation

arXiv:2609.07568v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed for translation tasks, yet their implicit political positioning in such contexts remains unders

XAI-Refine: An Automated Explanation-Knowledge Loop for Brain-Age Prediction

arXiv:2609.09388v1 Announce Type: new Abstract: Brain-age prediction models are commonly evaluated by predictive accuracy, yet accurate predictions alone do not establish that a model relies on reprod

Beyond Task Success: Stage-Wise Reliability of World Model Planning under Sensing Degradation

arXiv:2609.07126v1 Announce Type: cross Abstract: In world model planning, sensing inputs pass through an encoder and predictor before affecting planner decisions, so final task success alone cannot r

Deep Learning to Automate Parameter Extraction and Model Fitting of Two-Dimensional Transistors

arXiv:2507.05134v2 Announce Type: replace Abstract: We present a deep learning approach to extract physical parameters (e.g., mobility, Schottky contact barrier height, defect profiles) of two-dimensi

GIFT: Goal-Injected Fine-Tuning for Efficient Manipulation Policy Adaptation

arXiv:2609.07006v1 Announce Type: new Abstract: Compared with relying solely on initial observations and language instructions, predicting goal images with generative models as high-level visual guida

safetyarxiv-cs-cv

Learning Quantum Data Distribution via Chaotic Quantum Diffusion Model

arXiv:2602.22061v3 Announce Type: replace-cross Abstract: Generative models for quantum data pose significant challenges but hold immense potential in fields such as chemoinformatics and quantum physi

MV-STRIDE: Enabling MLLMs to Master Multi-View Spatial Reasoning via Hierarchical Capability Modeling

arXiv:2609.07258v1 Announce Type: new Abstract: Despite the rapid progress of Multimodal Large Language Models (MLLMs) in 2D vision-language tasks, robust multi-view spatial reasoning remains a fundam

PatchFormer: A Patch-Based Time Series Foundation Model with Hierarchical Masked Reconstruction and Cross-Domain Transfer Learning for Zero-Shot Multi-Horizon Forecasting

arXiv:2601.20845v2 Announce Type: replace Abstract: Time series forecasting is a fundamental problem with applications in climate, energy, healthcare, and finance. Many existing approaches require dom

Q-Guided Stein Variational Model Predictive Control via RL-informed Policy Prior

arXiv:2507.06625v4 Announce Type: replace-cross Abstract: Model Predictive Control (MPC) enables reliable trajectory optimization under dynamics constraints, but often depends on accurate dynamics mod

Reliable iToF Depth Sensing via Sensor-Intrinsic Uncertainty Modeling and State-Space Restoration

arXiv:2609.05507v1 Announce Type: cross Abstract: Indirect time-of-flight (iToF) cameras provide compact and cost-effective dense depth measurements, but their ranging accuracy is often degraded by se

Beyond a Universal Forecasting Selector: Demand-Conditioned Model Selection across Demand Patterns and Horizons

arXiv:2609.04425v1 Announce Type: new Abstract: Forecasting-model selection remains difficult in heterogeneous demand because the most suitable decision rule may vary with demand structure, data avail

CoFreeVLA: Short-Horizon Collision-Free Dual-Arm Manipulation via Vision-Language-Action Model and Risk Estimation

arXiv:2601.21712v3 Announce Type: replace Abstract: Vision Language Action (VLA) models enable instruction-following manipulation, yet their deployment on coordinated dual-arm platforms remains severe

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Conserved Immune Topology Improves Pathology Foundation Model Generalization for Cross-Cancer MSI-H Prediction

arXiv:2609.05182v1 Announce Type: new Abstract: Pathology foundation models integrated with multiple instance learning achieve competitive accuracy within single-cancer cohorts, yet cross-cancer gener

Applications

Corporate Language Model (CLM): Transforming Tacit and Fragmented Enterprise Knowledge into a Sovereign, Auditable, and Executable Corporate Intelligence Layer

arXiv:2609.04377v1 Announce Type: new Abstract: Enterprise AI deployments fail not from model inadequacy, but because organizations lack a structured substrate encoding how they decide, negotiate, and

applicationsarxiv-cs-ai

How to Speculate about Uncertainty in Agentic Coding? A Draft-Model Gate Method

arXiv:2609.05274v1 Announce Type: new Abstract: LLM agents deployed for software engineering fail expensively: they act confidently wrong, and bad actions are recognized only after costly execution an

Measuring AI Accountability Through Argumentation Analysis: Can Model Reasoning Withstand Scrutiny?

arXiv:2609.05088v1 Announce Type: new Abstract: AI oversight methods rely on ground truth for validation, but what constitutes appropriate AI behavior is contested. This leaves evaluation of moral rea

safetyarxiv-cs-ai

ProtLingo: Efficient Protein Language Modeling via Conditional Memory and Expert Routing

arXiv:2609.04793v1 Announce Type: new Abstract: Proteins perform diverse cellular functions, and even single amino-acid substitutions can alter stability, activity, or molecular interactions. Protein

Distilled Rapid Embedding Transfer (DRET): Parameter-Efficient Biomedical Domain Adaptation via Priority-Based Embedding Transfer

model-releasesarxiv-cs-cl

arXiv:2609.02898v1 Announce Type: new Abstract: Large domain-specific language models such as BioBERT and ClinicalBERT achieve strong performance on biomedical NLP tasks, but their computational deman

High-Altitude Balloon Station-Keeping with First Order Model Predictive Control

arXiv:2511.07761v2 Announce Type: replace Abstract: High-altitude balloons (HABs) are common in scientific research due to their wide range of applications and low cost. Because of their nonlinear, un

safetyarxiv-cs-ro

IRWOZ 2.0: A Large Language Model-driven Dialogue Dataset for Industrial Robot Conversations

arXiv:2609.04030v1 Announce Type: new Abstract: IRWOZ has improved industrial human-robot interaction (HRI) dialogue systems through domain-specific annotations. However, its initial version contains

On the Interaction Between Model Compression and Test-Time Adaptation

arXiv:2609.03604v1 Announce Type: cross Abstract: Deep neural networks deployed in the wild must be both efficient and adaptable, requiring model compression and test-time adaptation (TTA). While both

researcharxiv-cs-ai