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Artificial Intelligence
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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 163
EmbodiedWorld-200K: Toward Embodied World Agents via Embodied-Planning Dataset and Interactive World Models
Building embodied agents that can perceive, reason, and act across diverse 3D worlds is a central research direction toward artificial general intelligence.PaceVLA: Adaptive Temporal Action Quantization in Vision-Language-Action Models
Fast and reliable manipulation is crucial for practical robot deployment.ABACUS: Program-Guided Multistep Reasoning over Frozen Judgment Models
Judgment models answer semantic questions by scoring a finite set of candidate outcomes.Behavioral Probes for Information Flow in LLM Swarms
Most existing approaches to LLM swarm optimization are utility-driven, focusing on final task utility while leaving the processing, integration, and reliance of information within individual…Reconstruction and Discrete-Event Simulation Assessment of an Analytical
This article presents an analytical-DES benchmark for intra-aisle robotic picking in automated warehousing.GLOBE: Geometry-Led Online Behavioral Early Exit via Unit-Sphere Trajectories
Chain-of-thought (CoT) reasoning can improve problem solving, but models often keep generating after the correct answer is already reachable; the extra steps raise serving costs and may replace a…Correctness-Dependent Asymmetric Target Distributions for Self-Distillation Policy Optimization
Self-distillation policy optimization provides dense token-level supervision for LLM post-training through feedback-conditioned self-teachers.On the Benefits of Uncertainty Estimation for Species Classification: A Case Study on Optimizing Expert re-Annotation
Automated identification of diatoms from microscopic images is a cornerstone of large-scale freshwater biomonitoring, yet the high diversity of species and strong class imbalance pose significant…GraphEvoResearcher: Graph-Aware Training-Free Self-Reflective Reasoning for Cost-Bounded Multi-Hop Question Answering
Multi-hop question answering (QA) requires models to chain intermediate conclusions while remaining cost-aware.ClueFlow: Learning Long-Horizon Search through Attributed Research-State Transitions
Long-horizon search requires agents to acquire relevant evidence and integrate it into an evolving research state.Auditor-Assisted Summary-Channel Verification for Hosted LLM Identity Substitution
Hosted LLM services increasingly expose model identity as a product claim, but external users and auditors often cannot inspect which model configuration served a request.NIOCIS: Typed-Decision Next-Hop Routing with Node-Conditioned Option Spaces for Tool-Use Agents
Tool-use agents pay per decision: at each hop a language model re-reads the state and thinks for seconds, though its actions are finite and decisions recur.Map-Distribution Mixture-of-Experts for Multi-Agent Pathfinding
Designing capable neural policies for multi-agent pathfinding (MAPF), which map local observations to action distributions, represents an important challenge in multi-agent learning, with practical…Procedural Memory for Language Agents: A Neurosymbolic Perspective on Explicit Goal Structure
Large language models remain unreliable on long-horizon tasks requiring procedural reasoning.TimesJev: Thinking Fast on Time Series with System 1 Sufficiency
Large language models (LLMs) have recently shown strong potential for time series reasoning, while models that reason over time series are usually with long chains of thought.Accelerated Drift of Scientific Prose in the LLM Era: Evidence from an Interrupted Time-Series Analysis
Every scientific text is embedded in the writing norms of its time: it reflects earlier publications while also shaping the texts that follow.Understanding When Reflective Prompt and Skill Optimization Helps on Locally Served Reasoning Models: A Two-Model Study of GEPA and SkillOpt
Reflective text-space optimizers such as GEPA and SkillOpt have reported large gains on frontier and mid-size models.FrameGRPO: Incentivizing Video Reasoning via Multi-Frame Rollouts and Temporal Credit
Reinforcement learning with verifiable rewards, particularly Group Relative Policy Optimization (GRPO), has improved video reasoning in multimodal large language models.Multimodal Decoupling for Diversified Recommendation through Semantic and Structural Shaping
Recommender systems often suffer from over-concentrated results when optimized for accuracy, limiting recommendation diversity.TamedFlow: Trajectory-Aware Distillation for Teacher-Assisted Diffusion Sampling
Diffusion Transformers (DiTs) deliver high-fidelity image and video generation, but inference requires many sequential model evaluations.