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 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
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Newest papers, page 223
LAGO: Language Agents with Reusable Growing Options
Long-horizon tasks expose a weakness of monolithic tool-use loops: one agent must decompose, execute, and verify a task within a single trajectory.Memory-Efficient Subspace Optimization with Residual Correction: From Momentum SGD to Muon
Memory-efficient subspace optimization has emerged as a practical approach to reducing the memory cost of LLM training while preserving optimization performance.DeltaStreamer: Towards Human-Like Agentic Streaming Video Understanding
We propose DeltaStreamer, a novel agentic framework for streaming video understanding inspired by how humans observe, remember, and investigate.Lost in the Fallback: How Reliably Do Typed Decision Models Use Fallback Options?
Typed decision models (TDMs) are increasingly used in applications such as request routing and model selection, making reliable decisions critical to system performance.Euler: Towards Human-Centered Multi-Agent Mathematical Discovery
Mathematical research drives scientific discovery, and recent advances in AI for mathematics have shown that language-model agents can solve challenging problems and develop substantial mathematical…Explorer-Zero: Improving Self-Play for Long-Horizon Tasks with Decomposable Verifiable Rewards
Training LLM agents on long-horizon interactive tasks with reinforcement learning typically relies on human-annotated tasks and reliable verification, both expensive to construct for stateful…Rationale Distribution Distillation via Flow Matching for Distributional Continuous Latent Reasoning
Sampling multiple chain-of-thought rationales from a language model can uncover correct solutions missed by a single attempt.Neural Wasserstein Splines: Representation-Invariant Second-Order Priors for Trajectory Inference
Population dynamics are often observed only as unpaired snapshots, which leave the evolution between measurements underdetermined.Frustratingly Easy Majority Voting Using Length Conditioning
Majority Voting (MV) is a simple and widely used strategy which improves the reasoning accuracy of Large Language Models (LLMs) by allocating additional inference-time computation.DeepPV-MRF: End-to-End Partial-Volume Fraction Estimation from MR Fingerprinting Time Series
Estimating subvoxel tissue fractions from magnetic resonance fingerprinting (MRF) is challenging.Universal Sample-Based Embeddings of Higher-Order Objects
Neural networks operate naturally on finite-dimensional vectors, yet many problems require reasoning about higher-order objects such as distributions, functions, and graphs.How GUI Agents Fail: GraceBench for Execution Stability Diagnosis
As GUI agents are increasingly deployed for mobile task automation, their reliability depends not only on final task outcomes, but also on whether they reach these outcomes through stable…Multimodal Medical Image Parsing with Task-Specific Low-Rank Adapters
Adapting a single vision-language model to medical image parsing requires training choices that reflect the demands of each task.Sparse Transformer: a Controlled Testbed for Mechanistic Interpretability
Mechanistic interpretability aims to decompose neural network computations into human-understandable features, yet progress is limited by the absence of ground-truth units to evaluate against.MUCO: A Mani-Unit-Structured Manipulation Framework for Compositional Long-Horizon Robot Tasks
Learning and executing long-horizon robot manipulation as complete task trajectories raises data-collection costs, lim?its capability reuse, and causes local failures to cascade into later task…Does Machine Translation Retain Media Bias?
Within the most recent two decades, machine translation (MT) has been advanced from a research area to a mature, deployed technology for prose text and most language pairs.Learning Graph Energies for Finite-Time Generation
Energy-based models can represent distributions over discrete structures such as molecular graphs, but an energy that is accurate at equilibrium need not yield accurate samples when the sampler…Quiet Triggers, Loud Footprints: A Tri-Space Measurement Study of Backdoor Stealthiness
Backdoor attacks on deep neural networks are commonly evaluated by attack success rate and benign accuracy, yet their stealthiness remains inconsistently defined and measured.When Protection Overrides Consequences: Understanding Protection Mode in Large Language Model Decision-Making
Frontier language models excel at complex tasks yet may prioritize protection over larger physical consequences in simple, urgent decisions.AtomSearch: Evidence-Grounded Tree Search for Agent Skill Optimization
Agent skills adapt frozen models through editable external instructions.