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 61
CRoS: Causality Reward on Scrambled CoTs Improves Accuracy and Reasoning Faithfulness
Reinforcement learning with verifiable rewards (RLVR) has become the standard method for training language models to reason.The Knowledge Layer Model (KLM): Evidence-Visible AI Output, Routing Diagnostics, and Negative Results
AI answers require more than apparent correctness: reviewers need to inspect their recorded basis.CausalWAM: Learning the Causes of Actions in World Action Models
World action models (WAMs) learn latent variables from observations and use these to both predict the evolution of the scene and to generate actions.Subquadratic Attention with a Hierarchical Tree-Structured Indexer
The quadratic scaling of attention is a fundamental bottleneck limiting the long-context capabilities of large language models (LLMs).ACCT: Asymmetric Cross-LLM Context Transfer
In real-world deployments, large language model (LLM) systems are increasingly evolving from single-model invocation toward heterogeneous deployments in which different models are dynamically…RoboArchitect: Automating the Design of Robotic Agents with Persistent Memory
Recent work shows that a frozen robot policy performs far better inside an agent harness, where control code decides when to query the policy, consult vision tools, or command the arm directly.Hierarchical World Models with Implicit Dynamics
Planning with world models enables test-time adaptation for embodied agents, offering superior generalization over direct policy learning.Latent Sparse Attention: Towards Subquadratic Ultra-Long Context Attention
Agentic workflows are increasingly shifting towards long-horizon tasks, such as open-ended scientific work, where models benefit from long context windows.From Concepts to Actual Causes: Toward Closing the Concept-Malfunction Gap in Robot Foundation Models
Post-incident analysis of a robot foundation model poses a singular causal question: which internal components caused this failure, and to what degree?A Generalized Sparse Fuzzy Clustering Framework with Automated Cluster Cardinality Estimation Ability
Fuzzy clustering provides a robust framework for handling ambiguous and overlapping data boundaries, yet its traditional formulation generates entirely dense membership assignments that limit noise…Learning to bid and bundle: a posterior-sampling agent for online retail
An online retailer launching a perishable product bids for sponsored-search clicks, discounts a bundle with an always-stocked staple and displays its remaining stock, which raises willingness to pay.Early Stopping in Large Reasoning Models: A Survey and Empirical Audit of Efficiency and Reliability
Large reasoning models can improve accuracy by generating longer reasoning traces, but some of this computation may be unnecessary.PatchScout: Thematic Web Data Collection via Information Foraging
Researchers often need web corpora that are not answers to a single query, but reusable collections of documents spanning many decentralized sources.Reimagining Text-to-SQL: A Survey of Large Language Model Architectures and Strategies
Text-to-SQL systems translate natural language questions into executable SQL queries, democratizing access to relational data.From Fragmentation to Fusion: A Survey and Roadmap for Omnimodal Embeddings
Embedding models underpin virtually every modern AI system, from search engines to recommendation systems.AuroraWorld: Structured 4D World Modeling for Exo-to-Ego Video Generation in Robot Manipulation
Egocentric observations provide a robot-centric view of manipulation processes, capturing contact interactions and object-state changes that are important for visuomotor policy learning but…Neurons Are All You Need
For decades, artificial neural networks have operated under the assumption that durable, learned capability resides exclusively in adaptive synaptic parameters, primarily due to the established…MemU-Bench: Benchmarking GUI Agents on Long-Horizon User Interactions
Existing Graphical User Interface (GUI) benchmarks predominantly rely on precise and stateless user instructions.From Cross-Section to Cross-Omics: Conditional Cell Nucleus Image Editing in Spatial Transcriptomics
Spatial transcriptomics (ST) platforms simultaneously measure gene expression and capture cell nucleus images at single-cell resolution.Spectral and Conformal: Neural Network Methods for Calibrated Trajectory Prediction and Control-Point Intervals
Autonomous systems that navigate their environment need methods to quickly assess the feasibility and safety of desired trajectories.