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Artificial Intelligence
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The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,998 arXiv preprints and 2 OpenAlex records.
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Newest papers, page 178
Learning Which Device to Call: Online Tool Grounding for LLM Agents in IoT
The Internet of Things (IoT) gives large language model (LLM) agents access to physical observations, but one requested capability is usually offered by several devices, and the agent's plan does…Design and Cross-Domain Evaluation of an Agent Execution Harness
Completing complex tasks with language-model agents requires coordinating planning, execution, and review so the final result addresses the user's original objective.Benchmark for Structured Retrieval-Augmented Generation in Perovskite Photovoltaics
While retrieval-augmented language models increasingly serve as literature assistants in the physical sciences, existing benchmarks evaluate them primarily on qualitative text overlap or through…Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing
Large language models (LLMs) are enabling agents to move beyond predefined workflows toward autonomous planning and execution, creating new opportunities for smart manufacturing.Fix, Not Just Resample: Bounded Compiler-Guided Repair in Lean 4
Automated theorem provers often rely on sampling language models, but proof assistants like Lean reject each failed step with a precise error message --- information that pure sampling discards.MAMath-Bench: Process-Aware and Robust Evaluation of Multimodal Multi-Agent Mathematical Reasoning
Mathematical reasoning is a fundamental capability for educational applications of Large Language Models (LLMs), where reliable problem solving requires not only correct answers but also coherent…LightCRS: Lightweight Multi-Domain Conversational Recommendation System
Conversational recommender systems have recently adopted vision-language models to match user dialogue intents with multimodal product information.Beyond Policy Discrepancy: Capability-Aware Multi-Teacher On-Policy Distillation
Multi-teacher on-policy distillation (MOPD) integrates domain specialists into a shared student, but determining how strongly each teacher should supervise remains challenging.FoundPDE: A generative foundation model for data-driven symbolic discovery of partial differential equations
Discovering governing partial differential equations (PDEs) from observed data is a central inverse problem in computational science and engineering: the goal is not only to predict trajectories…When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability
Large language models (LLMs) struggle with classical planning, but benchmarks rarely distinguish structural difficulty from the difficulty of interpreting symbolic vocabulary.SZED at ArGuard Shared Tasks: Multi-Task Label-Attention and Cross-Modal Fusion for Arabic Hateful Meme Detection
We present SZED's submission to ArGuard 2026 Track A: Arabic hateful meme detection.Neural Networks with Differentiable Belief-Function Layers
Yager's 1987 rule of combination $\boxplus$ was proposed on epistemic grounds: under high conflict, mass should be redistributed to ignorance rather than renormalised onto the class simplex.Screening LLM Judges Without Ground Truth: A Preliminary Evaluation of an AI Dental Hygiene Coach
Evaluating a fine-tuned coaching model with expert graders is slow and expensive, and an LLM judge cannot be trusted without ground truth.What Matters for NVFP4 Training? A Comparative Study of Low-Precision Pretraining Recipes
Training large language models directly in 4-bit floating-point (FP) formats promises substantial improvements in throughput and energy efficiency.FlashRT-PAI: Fast Kernels Are Not Fast Pipelines for Physical AI Inference
Vision-language-action (VLA), video-action (VA), and world action models (WAMs) form the backbone of modern physical AI systems, yet their real-time single-batch inference remains a defining…Koi: Evidence-Guided, Self-Calibrating Planning for Multi-Cloud, Heterogeneous LLM Inference Fleets
Deploying a large language model (LLM) requires choosing the right accelerator, parallelization strategy, engine configuration, and replica count amongst ~140 other variables across clouds, regions…DKnown-Jev: Fine-Tuning and Evaluation of a JEV-Style Model for Tasks Involving Normative Knowledge
Tasks involving normative knowledge include concept interpretation, eligibility determination, procedure explanation, material requirements, and service-outcome assessment, all of which require…A Two-Stage Hybrid Framework for Inferring Air Trips from Mobile Location-based Service (LBS) Data under Incomplete Airport Sightings
Mobile device location-based service (LBS) data provide large-scale spatiotemporal observations that can help airport planners understand air travelers' mobility patterns.WAQS: Weight Absorption for Quadratic Probing and Affine Steering
Activation steering provides a lightweight alternative to fine-tuning for controlling large language model behavior.Tactix: Towards a Programmable Strategy Interface for Flexible SAT Solving
Modern SAT solvers combine a rich repertoire of proof rules with sophisticated strategies that determine when and how to apply them.