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Computer Science & AI
Much of the new work in computer science and AI appears first as a preprint on arXiv. ReadSearch reads those listings every day, with papers OpenAlex files under the same subjects, and this page shows the newest it has, from machine learning and language to systems, theory and security.
The newest 1,000 papers, from 4 November 2026 to 5 November 2026: 1,000 arXiv preprints.
Newest papers, page 29
When File Ingestion Misleads Language Models: Measuring and Mitigating Divergences in Office Documents
Office documents are now routinely uploaded to large language models (LLMs) for processing.Near-Optimal Complexity of Finding Approximate Local Minima of Nonconvex Finite Sums
We study the component-oracle complexity of finding approximate local minima of nonconvex finite sums under mean-squared averaged smoothness with parameter $L$ and a $ρ$-Lipschitz average Hessian.ReTailor: A Residual Feature Tailoring Framework for Real-Time Cross-Sensor Pansharpening Adaptation
Recent pansharpening models achieve strong fusion performance on trained sensors, yet often generalize poorly to unseen sensors.Towards the Query Complexity of Sampling under Strong Log-Concavity and Log-Sobolev Inequalities
We study the query complexity of sampling from smooth distributions on $\mathbb R^d$ using first-order oracles.Learning When Human Decisions Matter: Executor-Relative Consultation Value for LLM Agents
Large language models increasingly automate complex tasks, but human decision capacity does not scale with their capabilities.A Hybrid Approach for Automated Security Pattern Recovery
Security-by-design emphasises integrating security into software design and development.DualCast: Dual-Image Conditioned Diffusion Transformers for Digital Human E-Commerce Video Generation
Digital human e-commerce video generation requires preserving product appearance, human identity, and overall video style during dynamic demonstrations.TandemBench: Benchmarking Decision Models for Multi-Agent Collaboration
Decision models choose among predefined options in tasks such as routing and action selection.Autonomy and Coordination in Intelligent Manufacturing: A Recursive Autonomous Agent Framework
Intelligent production requires systems to make decisions and organize work according to production goals and operating conditions.SciToT: Multimodal Tip-of-the-Tongue Retrieval for Scientific Papers
Researchers frequently encounter difficulties re-finding scientific papers when they remember aspects of the content but cannot recall reliable identifiers, such as titles or author names.Functional inequalities from the fundamental limits of Bayesian estimation
We develop a Bayesian information-theoretic framework for proving functional inequalities for log-concave measures.Pathwise-Budgeted LLM Routing: Online Allocation with K-Bit Tail-Cost Learning
Firms using large language models under fixed budgets must decide which model to call and whether to retry a failed task.RACE: Calibrated Cumulative Scoring for Rollout-Free Robot Policy Checkpoint Selection
Assessing the deployment performance of learned robot policies during training is challenging, as directly measuring task success requires costly real-world trials for each candidate checkpoint.Makespan Bounds for Synchronous Pebble Motion on Graphs
We study the largest minimum makespan of labeled pebble motion on graphs under a model that permits synchronous pebble movement.Vision Paper: Why Distributed LLM Post-Training and Decentralized Alignment Are Now Essential
This vision paper argues that distributed learning, including federated and decentralized, should become a first-class paradigm in LLM post-training, not merely a privacy add-on.PEARL: Prediction Error-Adaptive Regularized Learning for Selective Forgetting under Partial Preference Drift
User preferences shift as needs, context, and tastes evolve.Dual Flow: Joint Image-Measurement Flow for Inverse Problems
Existing generative model-based approaches to linear inverse problems typically use the acquired noisy measurement to condition or guide sampling in the image domain.Sure Enough to Share? Overconfidence in GenAI Video Discernment is Associated with Sharing Intentions
Generative Artificial Intelligence (GenAI) is blurring the line between synthesized and recorded videos, but less is known about people's awareness of their discernment abilities and the…Time-to-Goal: Learned Temporal Metrics for Long-Horizon Planning with JEPA World Models
Joint-Embedding Predictive Architectures (JEPAs) support planning by comparing predicted latent states with an encoded goal.A low-rank decoder bottleneck bounds reliability in foundation-model perturbation prediction
Foundation-model predictors of perturbation response are evaluated primarily by aggregate accuracy.
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