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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 170
PORA: Learning When More Reasoning Pays Off for LLM Agents
LLM agents perform tasks over multiple steps and revise their actions based on feedback.EDMA: Entropy-Driven Multimodal Answering
Multimodal question answering (MMQA) is based on integrating heterogeneous data sources, selectively leveraging relevant modalities, and ignoring distractors.Reconstruction-Optimized Expert Pruning for Mixture-of-Experts Language Models
Mixture-of-Experts (MoE) models reduce computation through sparse expert activation, but deployment still requires storing a large number of expert parameters.Mind Your Boundaries: Boundary-Aware Model Obfuscation against Cross-node Attack
With the advancement of powerful AI chips, on-device machine learning is gaining traction for its low latency and privacy protection.Ontic state recovery through prediction
We encounter a system through its responses, yet its state concerns how the system is.Representing short-term movement to reveal animal identity and learning progress
How learning progresses over time and varies across individuals is a longstanding question in cognitive and behavioral science.ICLHerd: Herding-Based Data Selection for LLMs with In-Context Learning as a Proxy
Data selection plays a central role in modern large language model training, as the quality of training data strongly influences downstream performance.Model Exposure on One Device Endangers Others: Rethinking Edge Neural Network Security across Devices
Neural networks (NNs) are increasingly deployed on edge devices such as mobile and IoT platforms, offering low latency and improved privacy compared to cloud-based deployment.MoSAIK: Motion Search with Artificial Intelligence in K-space
Object: Motion artefacts remain a major limitation of routine two-dimensional T2-weighted turbo spin-echo (TSE) brain MRI, reducing diagnostic confidence and often necessitating repeated acquisitions.Understanding the Benefits of Scaffolds through Computational Separations
Inference-time harnesses, i.e., external procedures that call a model many times and keep state across calls, can substantially improve model capabilities.Learned Control Variates for Rare Grid-Outage Estimation at Electric Vehicle Charging Stations
Public charging of electric vehicles (EVs) adds a large and synchronized load to the distribution feeders.Visual Task Modeling and Automated Planning for Humanoid Robots in Education of Individuals with Autism Spectrum Disorder
In robot-assisted education, a robot must understand how to complete a task in order to effectively guide a student through it.On the Fragility of Tasks under Composition: Implicit Budgeting in Language Models
Modern language models are increasingly asked to handle several tasks within a single prompt.CARLAR Influence: A Structured Hallucination Risk in Multimodal Cheque Extraction and an Exploratory Compressed-Image Countermeasure
Multimodal large language models (LLMs) are increasingly used for structured extraction from financial documents, but their behavior under visual ambiguity is poorly understood.LSA-PAST: Layer-Specific Adaptation and Prototype Transport for Compositional Incremental Learning
Class-Incremental Learning (CIL) enables models to recognize new classes over time while retaining prior knowledge, but many real-world problems are compositional, where visual concepts arise from…LoWAgent: A Low-Resource Multilingual Benchmark for Web Agents
Web agents are typically evaluated on English-language interfaces, leaving their ability to operate across the world's multilingual websites largely unexplored.Language Guidance for Supervised Vision Training: An Empirical Study of Generalization
Deep neural networks have achieved remarkable success on vision benchmarks, yet they continue to struggle with many generalization challenges.Profile-DP: Differential Privacy for User-Controlled Profile Release in Personalized LLM Inference
Personalized large language models (LLMs) increasingly rely on profile-conditioned inference, pairing public requests with rich, user-specific facts.Sparse RL Relaxation for LLM Reasoning
Recent work has explored continuous representations in place of discrete tokens during Chain-of-Thought (CoT) reasoning, often referred to as soft CoT.Magnolia: A Persistent-Memory Agent Framework for Computational Chemistry
Chemistry has recently entered a high-data regime as molecular databases from high-throughput platforms or computational studies have become available.