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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 166
Answer Delivery Under a Shared Token Budget: An Audited Study of Stopping and Finalization
An inference budget is useful only when the system delivers an answer within it.When Coding Agents Outpace Review: Evaluating PRD-Driven Development in Mature Enterprise Repositories
Coding agents increasingly undertake development tasks in mature enterprise repositories, yet existing benchmarks offer limited insight into whether they fulfill complete Product Requirement…Local data augmentation for imbalanced binary classification
Facing imbalanced binary classification, we aim at maximizing the recall while limiting the proportion of false detections in the minority class.Physiology-Aware Graph Attention for Early Ventricular Reentry Prediction
Sudden cardiac death mostly originates from post-infarct ventricular tachycardia.Fake News, Real Crashes: Information Injection Attacks on LLM Financial Trading Agents
Large language model (LLM) agents now trade real capital using news as evidence, yet they cannot reliably tell fabricated headlines from real news.Rethinking LLM Fine-Tuning via Weight Space Reparameterization: Preserving Safety during Downstream Adaptation
Fine-tuning large language models (LLMs) on downstream tasks often weakens their previously aligned safety behavior, creating an inherent trade-off between task adaptation and safety preservation.Learning What to Remember: Resource-Efficient Self-Improvement for Lifelong Agents
Self-improving agents aim to continuously improve their behavior by learning from experience after deployment.ALIGN: Aligning Condition Estimation and Expression in Advantage-Conditioned Behavior Cloning
Human-collected robot manipulation data often mix successful behavior with retries, pauses, recoveries, and failures.VeriCUA: Learning Proactive Verification for Reliable GUI Agent Rewards
Reinforcement learning for computer-use agents increasingly relies on proactive reward agents that interact with the post-execution GUI environment to verify what recorded screenshots cannot reveal.SPAR: Structural Pruning and Action Recovery for Vision-Language-Action Models
The limited onboard computing resources of robots make the inference demands of vision-language-action (VLA) models costly to accommodate.Mitigating Reward Hacking in Preference Reward Models with Evolving Penalties
Reinforcement learning for language models has moved from preference reward models to verifiable rewards, which sustain much longer optimization.ScopeMem: Latent Memory That Learns Where to Revise Frozen GUI Agents
Latent memory is gaining ground as a lightweight history supplement for GUI agents.Learn the Task, Not the Schedule: Reducing Spurious Cross-Arm Coupling in Bimanual Imitation Learning
A bimanual demonstration specifies both what the robot should do and one particular schedule for when each arm should act.RouterWorld: Scaling Conversational AI with Latency-Aware LLM Routing
Conversational AI systems built on Large Language Models (LLMs) require routing mechanisms that balance answer quality and response latency at scale.Toward Structured Financial Foundation Models
Foundation models promise reusable capabilities and step-change performance gains across tasks.Beyond Behavioral Accuracy: Evaluating Individual-Level Fidelity in LLM Investor Simulation
Large language models (LLMs) are increasingly used as user simulators, but can they faithfully reproduce an individual's behavior and decision logic over time?A Semantic Knowledge Graph Construction Pipeline for Vehicle Intention Prediction in nuScenes
Knowledge graphs (KGs) are increasingly used in autonomous driving (AD) to make traffic scene entities and relations explicit for prediction and reasoning.Breaking Diffusion: Parallel Reasoning with Draft Refinement
Drafting an answer allows a reasoning model to reconsider each decision in the context of the others.Agentic Orchestration of EDC Data Space Retrieval and Natural Language Driven Data Processing
Participating in a data space still requires the Dataspace Protocol (DSP) negotiation flow to be hand-coded against each provider's access policy.Training Natural Schemers: RL Can Amplify Oversight-Conditional Behavior
One of the central concerns for the safety of advanced AI is scheming: when a model strategically complies under oversight but pursues its own goals when unobserved.