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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 105
Physical structure as an organizing principle for universal Hamiltonian learning
Density functional theory (DFT) gives the electronic structure of materials, but its cost limits large-supercell calculations and materials screening.From Structural Feedback to Prompt Policies: Learning Faithful Text-to-Image Prompt Editors
Prompt optimization should improve the image a user receives without changing the scene the user requested.Replication or Corroboration? An Axiomatic Framework for Evidential Dependence in Multi-Agent Debate
In multi-agent debates, matching reports can arise for two different reasons: agents may repeat the same evidence (replication), or they may provide separate evidential roots that support the same…Stratum: Repository Memory for Coding Agents Beyond the Context Window
Context windows have grown a thousand-fold, yet coding agents still start every session with no memory of their past work.Don't Pick a Winner: Knowledge Conflicts Need a Prior, Not a Rule
A retrieval-augmented language model answers from two sources, the retrieved context and its own knowledge, and the two disagree whenever the context is incomplete or wrong.Learning Human Sports Motion Feasibility via Quantile Regression on Tracking Data
We study time-to-arrival (TTA) in sports: the shortest plausible time a player needs to reach an arbitrary location on the pitch given their current kinematic state, estimated as the lower envelope…Can AI Guide Testing Without Generating Tests? A Comparative Study of AI-Assisted Unit Testing
Recent advances in generative AI have enabled assistants to generate increasingly sophisticated executable unit tests.Skill Dreaming: Evolving Repository Skills through Pull Request Streams
Large language model (LLM) agents increasingly rely on reusable skills for complex software engineering tasks, making skill libraries essential for repository development and maintenance.Beyond the Estimate: Wiener-Informed Decoding for Easier Training of Pixel-Space Flow Models
Learning velocity fields directly in pixel space is difficult and slow.count-catcher: Lean Theorems from Model Counting Certificates
We present count-catcher, a tool that turns a CPOG certificate of a count by the exact model counter d4 into a Lean theorem that a CNF formula defined in Lean has exactly N models over V variables.Base Models Can Detect Hidden Intentions that Prompted Classifiers Miss
The Persona Selection Model (PSM) posits that post-training selects a persona the model learned during pre-training.Concorde: Geometry-Aware Link Prediction via Decoupled Energy Minimization
Link prediction remains difficult in sparse graphs, where diffusion heuristics lack connectivity and geometric methods suffer spectral instability when coupling learned representations with…Counterfactual Profile Perturbations for Recommendation Explanations: A Reproducibility Study
This reproducibility paper explores the counterfactual explanation technique known as Learning to eXplain Recommendations (LXR).Structure, Not Sequence: Tracking and Validating Folding Mechanisms in ESMFold's Trunk with Sparse Autoencoders
Structure predictors like ESMFold fold proteins using neural network computation and have transformed structural biology.Directional Statistics on Circles and Spheres: A New Angle on Data
Two compass bearings near north can have an ordinary arithmetic mean pointing south: the difficulty is that angles live on a circle, not a straight line.Agent or Human? Detecting Commits by AI Coding Agents in the Absence of Authorship Signatures
AI coding agents such as Claude Code, GitHub Copilot coding agent, and Cursor now commit directly to open-source repositories.MARQ: A Modular, LLM-Agnostic Requirement Quality Assessor Infused with Systems Engineering Knowledge
Requirements engineering (RE) is foundational to systems engineering (SE), as requirement defects can propagate downstream and adversely affect development outcomes.BehaveRec: When Does Long-Term Behavioral History Help Sequential Recommendation? A Study with Session, History, and Community Signals
Sequential recommendation models typically predict a user's next action from recent session interactions, which limits personalization when short-term signals are weak or ambiguous.Freeze, Don't Clone: Fine-Tuning with Expressive Policies Without Retaining Offline Data
Offline-to-online reinforcement learning uses offline pretraining to accelerate subsequent online learning.cuArms: GPU-Accelerated Conflict-Based Planning for Multi-Arm Manipulation
Multi-arm manipulation has the potential to dramatically improve the throughput, efficiency, and dexterity of many manipulation tasks.