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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 224
Neurosymbolic Learning of Interpretable World Models
World models aim to learn compact representations of an environment from observations, enabling agents to predict future states and plan their behaviour.Safe-FCL: Continual Risk Awareness and Fine-Grained Safety Aggregation for Federated Continual Learning of LLMs
Federated fine-tuning enables large language models (LLMs) to learn collaboratively from distributed client data, but malicious client updates can compromise global model safety.Empirical Boundaries of Reservoir Computing for Few-Shot Sequence Pattern Tasks
Efficient sequence modeling remains a fundamental challenge in machine learning.A Strong Harness Narrows the Model Gap: A Comparative Evaluation for Legislative Document-to-XML Conversion
Legal-content reproduction requires matching the source exactly in section hierarchy, verbatim text, citations, and amendment spans; a dropped citation or mislabeled amendment carries into the…What Coding Agents Leave Unsaid: Measuring Task-State Gaps Between Execution and Reports
Human supervisors rely on coding agents' reports to assess progress, verify repairs, and decide when to intervene.Provable Transformer Context Compression for In-Context Reinforcement Learning
Transformers can perform in-context reinforcement learning without parameter updates.On the Convergence of Semi-Gradient TD: A Mean Field Perspective
Semi-gradient temporal-difference learning is a core algorithmic component of reinforcement learning, but bootstrapping with function approximation generally induces a non-conservative vector field…MorphAct: Robot Policies Morphing with the Worlds They Act In
Progress toward general intelligence in the physical world requires scaling robot learning across diverse environments and interactions.Memorizing Who, Knowing How: Benchmarking Personal and Procedural Memory for Persistent Assistants
Memory systems for persistent personal agents must move beyond isolated memories, maintaining both personal memory about whom they serve and procedural memory about how to act.SWE-Nexus: Automated Composition of Software Engineering Tasks from Test Execution
Historical code changes provide convenient task boundaries, but do not identify which production functions selected tests exercise or support composing validated behaviors beyond a single change.CoRedSkill: Stealthy Skill Composition Attacks via AST-Guided Injection
Agents extend their capabilities through reusable skills that package instructions, executable code, and resources.GeoCloak: An Agentic Framework for Semantics-Preserving Geolocation Privacy via Peripheral Clue Manipulation
The rapid advancement of large vision language models (LVLMs) has made geolocation inference from images highly accurate and accessible.Beyond Correctness: Compute-Responsive Data Selection for Reasoning Model Post-Training
Reasoning language models increasingly rely on test-time compute scaling, yet most existing work studies how to allocate inference computation while treating the model itself as fixed.FoveaVLA: Foveation Actions Replace the Wrist Camera in VLAs
We present FoveaVLA, a Vision-Language-Action (VLA) model that replaces the wrist camera with learned foveation actions.Which Knowledge Should LLMs Trust? Uncovering a Generalizable Steering Direction Across Knowledge Conflicts
Large Language Models (LLMs) frequently encounter conflicts between internal parametric knowledge and external contextual knowledge, yet the mechanisms governing this selection remain unclear.Trainable at Depth, Solvable at Small Size: What the Loss Surface of a Polynomial Activation Dictates for Designing, Initializing and Training Networks
What makes a deep network train, and what shape is its loss surface?Rethinking Prediction Horizons: Decoupling Model Queries from State Updates in Few-Step MeanFlow
MeanFlow predicts interval-average velocities, but conventional few-step sampling ties the interval queried from the model to the duration of the state update.Designing Textual Interfaces To Enhance Llm Reasoning On Audio-Visual Question Answering
Automatic prompt optimization (APO) has shown strong effectiveness for text-based LLMs and LLM systems, but its application to audio-visual understanding systems requires suitable textual interfaces…AFCS: Atomic-Fact-Conditioned Synthesis for Factual Knowledge Pretraining
Synthetic data is increasingly used in language-model pretraining.EvalBuilder: Can LLMs Build Efficient Benchmarks?
Large language model (LLM) agents are increasingly used for long-horizon research and engineering, yet evaluating these capabilities remains expensive, time-consuming, and heavily dependent on human…