惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

T
The Blog of Author Tim Ferriss
IT之家
IT之家
Engineering at Meta
Engineering at Meta
WordPress大学
WordPress大学
博客园 - 三生石上(FineUI控件)
博客园 - 聂微东
C
Check Point Blog
T
Tailwind CSS Blog
博客园 - Franky
H
Help Net Security
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
Google DeepMind News
Google DeepMind News
博客园 - 叶小钗
J
Java Code Geeks
腾讯CDC
罗磊的独立博客
爱范儿
爱范儿
阮一峰的网络日志
阮一峰的网络日志
Martin Fowler
Martin Fowler
酷 壳 – CoolShell
酷 壳 – CoolShell
I
InfoQ
B
Blog
V
Visual Studio Blog
F
Fortinet All Blogs

cs.AI updates on arXiv.org

Policy Split: Incentivizing Dual-Mode Exploration in LLM Reinforcement with Dual-Mode Entropy Regularization METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning Do LLMs Know Tool Irrelevance? Demystifying Structural Alignment Bias in Tool Invocations Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning Exploring Knowledge Conflicts for Faithful LLM Reasoning: Benchmark and Method CocoaBench: Evaluating Unified Digital Agents in the Wild MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis Efficient Training for Cross-lingual Speech Language Models Shared Emotion Geometry Across Small Language Models: A Cross-Architecture Study of Representation, Behavior, and Methodological Confounds A Systematic Analysis of the Impact of Persona Steering on LLM Capabilities Uncertainty-Aware Web-Conditioned Scientific Fact-Checking When Valid Signals Fail: Regime Boundaries Between LLM Features and RL Trading Policies When Verification Fails: How Compositionally Infeasible Claims Escape Rejection Mem$^2$Evolve: Towards Self-Evolving Agents via Co-Evolutionary Capability Expansion and Experience Distillation AOP-Smart: A RAG-Enhanced Large Language Model Framework for Adverse Outcome Pathway Analysis Advancing Polish Language Modeling through Tokenizer Optimization in the Bielik v3 7B and 11B Series TInR: Exploring Tool-Internalized Reasoning in Large Language Models Do BERT Embeddings Encode Narrative Dimensions? A Token-Level Probing Analysis of Time, Space, Causality, and Character in Fiction Generating Multiple-Choice Knowledge Questions with Interpretable Difficulty Estimation using Knowledge Graphs and Large Language Models Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models Learning and Enforcing Context-Sensitive Control for LLMs Efficient Process Reward Modeling via Contrastive Mutual Information Computational Lesions in Multilingual Language Models Separate Shared and Language-specific Brain Alignment Bridging Linguistic Gaps: Cross-Lingual Mapping in Pre-Training and Dataset for Enhanced Multilingual LLM Performance Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models LLMs Should Incorporate Explicit Mechanisms for Human Empathy
Integrating Virtual Reality and Large Language Models for...
Jacob Barker, Doga Demirel, Cullen Jackson, Anna Johansson, Robb · 2026-01-20 · via cs.AI updates on arXiv.org

Although effective teamwork and communication are critical to surgical safety, structured training for non-technical skills (NTS) remains limited compared with technical simulation. The ACS/APDS Phase III Team-Based Skills Curriculum calls for scalable tools that both teach and objectively assess these competencies during laparoscopic emergencies. We introduce the Virtual Operating Room Team Experience (VORTeX), a multi-user virtual reality (VR) platform that integrates immersive team simulation with large language model (LLM) analytics to train and evaluate communication, decision-making, teamwork, and leadership. Team dialogue is analyzed using structured prompts derived from the Non-Technical Skills for Surgeons (NOTSS) framework, enabling automated classification of behaviors and generation of directed interaction graphs that quantify communication structure and hierarchy. Two laparoscopic emergency scenarios, pneumothorax and intra-abdominal bleeding, were implemented to elicit realistic stress and collaboration. Twelve surgical professionals completed pilot sessions at the 2024 SAGES conference, rating VORTeX as intuitive, immersive, and valuable for developing teamwork and communication. The LLM consistently produced interpretable communication networks reflecting expected operative hierarchies, with surgeons as central integrators, nurses as initiators, and anesthesiologists as balanced intermediaries. By integrating immersive VR with LLM-driven behavioral analytics, VORTeX provides a scalable, privacy-compliant framework for objective assessment and automated, data-informed debriefing across distributed training environments.