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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 169
Dynamic Dual-Feedback Conformal Inference for Time Series Forecasting
Quantifying uncertainty in time series forecasting is particularly demanding because sequential data exhibit temporal dependence and are prone to distributional changes.3D-MoE: Complementarity-Guided Hardware-Software Co-Design for MoE Decode on 3D-Stacked NMP
Mixture-of-Experts (MoE) have become a mainstream way to scale Large Language Models (LLMs), because each token activates only a small subset of experts, reducing inference cost.CoASFL: Coupled Consistency Optimization for Asynchronous Split Federated Learning
Split Federated Learning (SFL) has emerged as a promising paradigm for training large-scale deep models on resource-constrained edge devices.SPEM: Structure-Aware Procedural Memory for Efficient Skill Use in LLM Agents
LLM-based agents increasingly rely on reusable skills.HierDTA: Hierarchical Structure-Aware Representation Learning for Drug--Target Affinity Prediction
Drug--target affinity (DTA) prediction plays an important role in computer-aided drug discovery, where reliable computational models can help prioritize compound--protein pairs before experimental…Exploration via Activation-Space Steering for Reinforcement Learning with Verifiable Rewards
Reinforcement learning with verifiable rewards (RLVR) trains a language model by sampling responses, scoring them with an automatic verifier, and updating the policy from the resulting rewards.Reliable Estimation of Differential Privacy under Selection Bias
Statistical privacy audits are essential for verifying the theoretical privacy guarantees of differentially private (DP) mechanisms.BR-MoE: Budgeted Semantic Release for Privacy-Preserving Traffic Analytics
Traffic cameras support useful analysis, but their outputs can reveal private information.Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?
Multi-agent LLM systems improve performance on clinical tasks, and that improvement is often read as evidence of a more trustworthy system.Teaching AI Agent to Play Poker Strategically Through Preference Optimization
A poker agent can make a legal move and still make a strategically poor one.M-Plan: Comprehensive Planning For LLM Agents with Memory Arrangement
Large language model (LLM)-based agents have recently demonstrated outstanding performance in single-turn tasks, yet they continue to struggle with long-horizon tasks, particularly in environments…Robustness of Internal Signals for Hallucination Detection in Vision-Language Models
When given an image and a text prompt, vision-language models (VLMs) can produce seemingly sophisticated text responses.Cross-Lingual Reusability of LLM Pipelines: Financial Extraction, Multilingual Reasoning, and Semantic Screening
Financial institutions increasingly deploy large language models (LLMs) in multilingual markets, raising a practical question: can pipelines developed and validated in English be reused across…Physical AI: Concepts, Techniques, and Challenges
In recent years, physical artificial intelligence (physical AI) has experienced rapid development, capturing significant attention in academia and industry.ReuF2F: Benchmarking Coding Agents on Formalized Undergraduate Research Problems
As AI systems begin to resolve open research problems, reliable verification becomes increasingly important.Discrete Neural Interlingua for Ontology-Agnostic EHR Modeling
EHR foundation models promise scalable clinical prediction across health systems, yet their deployment is constrained by a tokenization bottleneck.A general-purpose System One decision model for clinical records
Clinical care, health-system operations and biomedical discovery depend on extracting reliable answers from patient records, yet applying diverse clinical questions across entire populations remains…Omni-Woodpecker: Hallucination Correction via Evidence-Prior Rebalancing for Omni LLMs
Recent Omni LLMs (OLLMs) have demonstrated remarkable capabilities in joint audio-visual reasoning, yet cross-modal hallucinations remain a major challenge.Joint Constraint Aggregation for Qualifier-Sensitive Retrieval-Augmented QA
Retrieval-augmented QA can fail even when the correct answer is in the retrieved evidence.PROVISO: Provenance-Informed Action Selection for Secure LLM Agents
LLM agents act on the external world through tools and third-party skills, so a single executed action can cause irreversible harm.