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Artificial Intelligence
The newest papers in Artificial Intelligence that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
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 123
Monetizing Intelligence: Advertising and Subscription Design on LLM Platforms
Large language model (LLM) platforms introducing advertising must decide how much capability ad revenue should fund and what consumers should pay to avoid ads.Beyond Discrete Tokens: Preserving Numerical Continuity in Medical Vision-Language Models
To develop a unified vision-language model for prompt-conditioned quantitative ultrasound measurement that addresses the mismatch between continuous measurement targets and discrete token-based…Where Rounding Happens Matters: Rounding-Location Alignment Stabilizes LLM Reinforcement Learning
Reinforcement learning for large language models often uses separate systems for inference and training.DexPort: A Hand-Held Skill Interface for Dexterous Hand Data Collection
Collecting high-quality demonstrations remains a central bottleneck for learning dexterous manipulation.RobustRLlib: A Unified Library and Benchmark for Robust Reinforcement Learning Algorithms
Robust reinforcement learning (RL) is critical for reliable real-world deployment, where policies may fail under diverse shifts and disruptions.SceneBloom: Agentic Indoor Environment Generation with Realistic and Diverse Layouts for Embodied Learning
Training generalizable embodied agents requires realistic, varied, and simulation-ready indoor environments.Conformance as a Distribution: Delegation Contracts, Error Budgets, and the Allocation of Evaluation Authority in Use-Based AI Regulation
Use-based AI regulation assigns obligations by deployment risk but lacks an evidentiary object to carry them.Optimal Correction Sets for Provable Redress of Contestable Causal Discovery
Constraint-based causal discovery relies on conditional-independence (CI) tests that may conflict in finite samples, leaving no causal graph that satisfies them all.AOS-Bench: Can LLM Agents Manage Dynamic Workloads?
Coding agents are moving from handling one request at a time to serving as persistent assistants to which users hand a stream of work: a build, a data-processing job and a bug fix may all be pending…Propensities Please: Exposing Alignment-Faking LLMs using Synthetic Document Finetuning
Alignment evaluations aim to assess whether large language models would engage in dangerous misaligned behaviour.Whale You Go Green? Immediate and Longitudinal Effects of Embodied Conversational AI Avatars on Sustainable Behavioral Tendencies and Pro-Environmental Attitudes
Embodied conversational AI can be persuasive, but can it motivate people to develop sustainable behavioral tendencies and increase pro-environmental attitudes?Cross-Platform Application Migration to HarmonyOS: An Agentic Pipeline with Artifact-Derived Verification
The migration of applications written for a different platforms like Android or iOS to HarmonyOS NEXT requires a complete rewrite in ArkTS.Isharah-Selfie: Continuous Sign Language Recognition Dataset for One-handed Signing
Current sign language recognition and translation benchmarks are commonly collected in controlled settings using fixed or studio-style cameras, particularly limiting their ability to reflect how…Position, Role or Label? A Controlled Study of Instruction Conflicts in LLM Agents
LLM agents take instructions from the operator, repository configuration, user, tool results and saved memory, which often conflict.Scaling Qualitative Analysis with Large Language Models: Development and Validation of the Smart Coder Framework for Human-LLM Collaborative Coding
Current uses of large language models (LLMs) for qualitative coding often rely on ad hoc prompting with limited guidance for reliability and human oversight.Distilling Expert Judgment at Scale
Frontier AI models are increasingly deployed on topics where the stakes are high and expert judgment is required, including healthcare, defense, finance, governance, and politics.NewsBench: Expert-Grounded Evaluation of Epistemic Quality in AI News Reporting
As frontier AI systems increasingly serve as sources of political and current-events information, evaluating the epistemic quality of their responses is now especially consequential.AdaPRA: Process Reward Agents with Adaptive Rubrics for Data Science
Data science agents can automate end-to-end machine learning workflows, yet they remain far from competitive on human leaderboards.Operationalizing Governed Agentic Workflows in Regulated Finance: A Customer Zero Case Study using Zafin AIOS
Regulated industries such as finance and healthcare face critical governance challenges that hamper the adoption of AI-assisted software development and hinder the transition from experimental…Image Clustering with Vision-Language Model Embeddings
Pretrained vision-language models provide image representations whose suitability for clustering may vary with feature extraction, image domain, and partitioning algorithm.