AI & Machine Learning · Computer Science & AI
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 130
QICOM: Open-Source Software for Reproducible Image Quality Evaluation, Blinded Assessment, and Radiomic Comparison
QICOM (Quality Image COMparator) is open-source software for quantitative image comparison, paired radiomics, and blinded assessment.Reward-Weighted Preference Optimization for Selective Combinatorial Optimization Problems
Reinforcement learning has emerged as an effective approach for combinatorial optimization, but most existing methods focus on problems such as the Travelling Salesperson Problem (TSP) in which all…Reducing Multi-Horizon Photovoltaic Forecast Error through Tree-Anchored Expert Combination
A strong direct tree model may remain the best standalone photovoltaic forecaster, yet a weighted combination can reduce its residual errors.Can Entanglement-Induced Feature-Map Designs Improve Projected Quantum Kernels?
Projected quantum kernels (PQKs) have emerged as a notable approach to circumvent the hardness of machine learning tasks arising from the exponential dimensionality of the quantum Hilbert space.Notation3: Graph Terms for RDF
Notation3 Logic was introduced as an extension of RDF allowing the user to express rules on top of triples and to make statements about graphs.Memory-Aware Reward Modeling: Learning Human Preferences for LLM Memory Use
Memory enables language model assistants to maintain continuity across sessions and generate personalized responses, but knowing more about a user does not necessarily produce responses they prefer.PointerBench: A Diagnostic Benchmark for Fine-Grained GUI Grounding
Multimodal Large Language Models have shown promising performance in computer-use tasks, from planning user workflows to grounding natural-language actions to precise UI targets.RIPPLE: Recovery Internalization through Process-Level Policy Learning and Effect-Aware Credit for Long-Horizon Agentic Coding
Long-horizon coding agents can observe a failure and generate a plausible critique yet continue along the same incorrect trajectory.CoWriter: Guiding Methodological and Synergetic Human-LLM Co-Authoring
While LLMs have transformed text generation, standard chat-and-canvas interfaces often reduce human authoring to quite passive supervision, causing review fatigue, over-reliance on AI, and the…Beyond Accuracy: Disentangling Decomposition from Typed-State Quality Assurance in Multi-Agent LLM Pipelines
Multi-agent LLM pipelines are often credited with gains in software engineering tasks, but it is rarely clear whether a gain stems from the typed contract between agents or from the specialized…RecallGS: Geometry-Grounded Recall for Online Semantic Gaussian Splatting
Online semantic 3D Gaussian Splatting (3DGS) enables open-vocabulary scene understanding from streaming observations.The Value of Memory in Language Agents
Memory enables language agents to carry useful distinctions from past experience into future decisions.Superintelligent Software Engineering: Governance That Scales with Capability
Software agents are being trained to exceed human engineers; we argue that capability alone does not produce better software engineering.Subgoal-aware Memory Graph for GUI Agent
GUI agents aim to automate complex user tasks by interacting with mobile interfaces, but ef- fective decision-making in long-horizon set- tings requires reusing prior experience rather than relying…When LLMs Forget What They Believe: Characterizing State Integrity Collapse in Long-Horizon Dialogues
Large language models can repeat an instruction while failing to keep obeying it.SurveyGraph: Generating Academic Surveys via Methods-Entity Knowledge Graphs
Most automated survey generation systems retrieve papers as flat documents, limiting their ability to capture research structure.Hyperreduction accelerates finite element model updating for the discovery of neural materials
Finite element model updating is among the most general approaches to discover constitutive models from structural experiments: since the displacement field is computed rather than measured, it…Bridging the Data Gap: Source-Informed Task-Space Transport for Few-Shot Diffusion
Many deployments require a model to move rapidly from a data-rich source to a related target observed only sparsely.AgenticEvolve: Evolutionary Program Search with Persistent Language Model Agents that Design and Run Experiments
Evolutionary program search with large language models keeps the structure of an evolutionary algorithm and uses the model as its variation operator.ValuSpec: Plug-and-Play Candidate Valuation before Target Verification for Tree-Based Speculative Decoding
Tree-based speculative decoding accelerates large language model inference by verifying multiple candidate branches in parallel.