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Artificial Intelligence
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The newest 5,000 papers, from 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
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Newest papers, page 238
Certifying Almost-Sure Reachability in Unknown MDPs
{\em Specification-Guided Reinforcement Learning (RL)} has largely concerned itself with \emph{learning} an optimal policy against a formal specification in an unknown {\em Markov Decision Process…H-DDCM: Hadamard Codebooks for Fast Generative Image and Video Compression
Training-free diffusion-based compression methods repurpose the generative priors of a diffusion or a flow model to compress data without retraining them as task-specific codecs.Fresh at Decision, Stale at Action: Routing New Information to LLM Decisions Already Made
Freshness shapes an LLM decision at the moment it is made; the action it commits to is latent, carried out later, in a changing world.Monitoring latent reasoning in looped language models
Looped language models (LMs) reuse one block of layers several times per token generation, promising more latent computation at no additional storage cost.Mitigating Cross-Modal Hallucinations by Correcting Modality Misrouting in Omnimodal LLMs
Omnimodal large language models (OLLMs) are susceptible to cross-modal hallucinations under audio-visual interference.RadixFlow: Filling Execution Bubbles in Prefix-Cached Hybrid LLM Serving
Prefix reuse improves LLM inference by sharing the KV cache of common prompt prefixes.When Do Learned Blocks Preserve Causal Meaning? Block Identifiability and Constructive Causal Abstractions
Standard identifiability theory assumes one-dimensional latent factors, but learned representations can encode latent information across multidimensional blocks whose internal coordinates are not…Fan Out or Relay? Ownership-Aware Routing for LLM Agents Querying Siloed Tables
Inside organizations, a question's data often sit with several owners, who query their own tables but never hand them over.When and How Order-Flow Interventions Work After Dealers Adapt
Learning dealer agents can settle on persistently wide quotes, raising what customers pay to trade.Claim Framing as a Driver of LLM Sycophancy
Sycophancy in Large Language Models, the tendency to align responses with user preferences over ground truth, has largely been studied using questions without a clear ground truth and with a single…LoOPSD: On-Policy Self-Distillation with Looped Teachers
On-policy self-distillation improves a model using guidance from the model itself, but it still requires a teacher that provides more useful predictions than the student.Lifting Finite-Sample Gaussian Approximation of Wide Neural Networks to Functional Convergence
Randomly initialised neural networks of width $m$ converge to Gaussian processes as $m \to \infty$, with two types of quantitative bounds characterising this convergence.Back to the Future: Reverse-Consequence Modeling for Long-Horizon Particle Dynamics
Accurate prediction of object trajectories is fundamental to mechanical understanding and robotic control.Looped Reasoning Finishes Earlier Than You Think
Looped reasoning with dynamic depth can be viewed as relaxation toward solution attractors in a learned dynamical landscape.Neuro-Symbolic Graph Transformers for Hierarchical Intention Recognition from Multimodal Human Activity Sequences
Proactive human-robot collaboration requires autonomous systems to infer not only immediate actions but also the underlying hierarchical intentions governing human behavior.QORH: Learning Query-Specific Ordered Rule Hypergraphs for Inductive Knowledge Graph Link Prediction
Knowledge graph link prediction involving unseen entities and relations requires learning transferable reasoning patterns from observed graph structure.A Few More Tokens Ahead: Reinforcing Parallelism in Diffusion LLMs
Parallel generation is widely regarded as an inherent advantage of diffusion large language models.How Reliable Are Large Language Models for Soil Organic Carbon Assessment? An Australian Benchmark
Soil organic carbon (SOC) is an indicator of agricultural soil condition and carbon storage, but numerical outputs from large language models (LLMs) require validation before use in monitoring or…Reset Early, Reset Often, Eliminate Models
Connection-tableau provers typically construct closed tableaux by backtracking search.TextualRL: Textual Reinforcement Learning for Context Management
LLM agents can adapt to task feedback by revising the textual context that guides their behavior, without changing their model parameters.