large language models

When a Language Model Is Put Under the Microscope

When a Language Model Is Put Under the Microscope A Case Study of Conversational Continuity, Error Correction, and Human-Directed Evaluation Author: Salahuddin Ahmad LavasaniDocument Type: Case Study and Critical Analysis of Human–AI Interaction Abstract Large language models can produce fluent answers, discuss their o...

Scaling the Expert Eye: Automating Subsurface Model Evaluation and Tuning via Reservoir Engineering Inspired AI Agents

Abstract Predicting the behavior of oil fields is a notoriously complex endeavor, often relying on high-fidelity predictive models (e.g. simulation models) that are sensitive to a myriad of geological and operational parameters. Traditionally, the "gold standard" for refining these models has been the manual interventi...

RAG-Wissensbasis mit MCP-Server für die Recherche in Fachliteratur (Python)

Lokale RAG-Wissensbasis für wissenschaftliche Fachliteratur (PBPK und Pharmakometrie): PDF-Extraktion mit GROBID und optional Google Document AI, sektionsbasiertes Chunking, Embeddings (bge-large) und BM25 in Qdrant für hybride Suche; ein MCP-Server in Python stellt Such- und Annotationswerkzeuge für Sprachmodelle bere...

Deterministic Quantum Mechanics of Transformer In-Context Attention: Wavefunction Dirac-Delta Collapse via Optical-Mechanical Dual-Chassis

Large language models (LLMs) governed by softmax-based self-attention inherently suffer from non-deterministic token drift, attention dispersion, and cumulative hallucination. In this paper, we formalize in-context attention dynamics through a quantum mechanical perspective, modeling the attention distribution as a sta...

RABIT-KV

Target-bit-aware KV-cache quantization and physically packed serving for large language model inference. The frozen K3/V2/G32/R4/META8g64 configuration increases observed paged KV capacity on the evaluated H100 system, with higher latency and lower throughput. Canonical logical quality is model-dependent and is evaluat...

Towards guideline-grounded clinical decision-making: a multi-scale study of retrieval augmented generation based large language model agents

Mapping the Silence: Cross-Lingual Asymmetries in Large Language Model Refusal and Evasion on Sensitive History

As large language models increasingly shape public discourse, this study evaluates how US and China-based models govern access to politically sensitive history in US English and Mandarin Chinese. Across 2,400 interactions covering sixty globally significant events, we examined how prompt configurations modulate LLM res...

A Large Language Model Framework for Risk Cause Interpretation and Mitigation Recommendation in Drilling Operations

Summary When drilling risks such as kick events occur, rapidly identifying the root causes and recommending effective mitigation measures is critical for well control and operational safety. Traditional incident analysis mainly relies on expert experience and rule-based diagnostics, which are time-consuming and often l...

ScenePilot-4K: A Large-Scale First-Person Dataset and Benchmark for Vision-Language Models in Autonomous Driving

DrillBench: A Sequential Decision-Making Benchmark for Drilling Operations with Cross-Stage Agent Feedback

Abstract Drilling operations require engineers to make sequential, safety-critical decisions under partial observability, physical constraints, and noisy sensor data, yet most existing machine learning approaches treat drilling intelligence as isolated prediction tasks and fail to capture the multi-stage reasoning proc...

A Physics-Informed, Retrieval-Augmented Industrial Agent for Early Opportunity Detection and Operational Support in Offshore Gas Networks

Abstract Large offshore gas pipeline networks generate continuous process measurements, alarms, operational records, reporting demands, and external-event indications. The bottleneck is often converting a candidate signal into a useful technical assessment. This paper presents a physics-informed, retrieval-augmented in...

A Conversational User Interface for Autonomous Reservoir Simulation Deck Generation and Execution

Abstract Objectives/Scope This paper presents CLARISSA (Conversational Language Agent for Reservoir Integrated Simulation System Analysis), a conversational agent that autonomously generates, executes, and analyzes reservoir simulation models from natural language input. Engineers describe what they want; CLARISSA deli...