Abstract Natural language-based data query and analysis are crucial for enterprise operation and management. Currently, querying across a large number of metrics faces two main challenges: low query accuracy and the lack of an interpretable analytical process in query results. This paper constructs a natural language q...
Using stepwise probe as an external reference or Chain-of-Thought (CoT) to evaluate visual-language model (VLM) analysis ability is common, but the faithfulness of PASS/FAIL verdicts in VLM produced by explicit CoT and independent SRFE probe needs further work to figure out. Prior works on CoT faithfulness are mainly a...
Xin-Yi Wei· Applied and Computational En...· 0 citations
The wellbore schematic is one of the most critical diagrams in drilling engineering design. Currently, these schematics are predominantly generated manually, a process that is tedious, inefficient, and lacks standardization, leading to significant inconsistencies among diagrams produced by different engineers. To add...
Chun-Qian Chen, Ming Tang, Shi-Ming He· GOTECH· 0 citations
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Abstract This study, completed during the 2025 GOTECH® hackathon, presents a data-driven framework to identify production-optimization opportunities and to forecast incremental production. The approach was applied to an offshore platform with wells operating under high, low, and very low pressure, where planned and rea...
Francisco Javier Parga Garcia, Julieta Álvarez Martínez, Nazario Ramirez de la Cruz et al.· GOTECH· 0 citations
Under geopolitical tensions and monetary policy shifts, global stock market volatility has intensified. Traditional valuation models and risk forecasting models, relying on historical static parameters and overlooking non-quantitative information such as management tone, suffer from systematic biases. This study uses t...
Yu-Xin Ge· Advances in Economics, Manag...· 0 citations
This literature review puts forward a three-stage model of Large Language Models (LLMs), delineates the research goals of LLM in three stages and predicts future trends. Against the rapid, fragmented advancement of large-language-model technologies, systematic sorting of their evolutionary trajectories helps researcher...
As large language models have been increasingly applied to daily life in information seeking and decision-making, public trust in AI output has greatly improved. This brings about the worry that human critical thinking could become impaired. Using Salvi et al.'s GPT-4 conversational persuasion experiment as a start, th...
Zixuan Guo· Lecture Notes in Education P...· 0 citations
With the continuous improvement of communication network scale and business complexity, the traditional operation and maintenance methods relying on manual experience and rules face certain limitations in multi-source information processing and complex fault analysis. The ability of large language model in natural lang...
Yeermaike Mulati· Applied and Computational En...· 0 citations
This study investigates how Large Language Model (LLM)-based conversational AI and human teacher intervention affect the development of Second Language (L2) Interactional Competence (IC). Employing a two-phase qualitative research design, the study first analyzes interaction texts and reflective journals from five coll...
Ji-Jing Xing· Lecture Notes in Education P...· 0 citations
Self-hosted large language model (LLM) serving is emerging as a distinct category of Internet service, but we still know little about how these deployments appear and change on the public Internet. We present a 365-day longitudinal measurement of exposed Ollama endpoints (port 11434) from February 2025 to February 2026...
Zuyao Xu, Xiang Li, Yuqi Qiu et al.· Proceedings of the 2026 ACM...· 0 citations
Experimental results for the paper "Grounding Large Language Models in a Symbolic Formalization Environment for Natural-Language Planning". The archive contains the results of 5,100 formalization sessions. Qwen 3.5 (122B) and GPT-OSS (120B) each formalized the 2,550 Blocksworld, Logistics and Rovers problems of the ben...
Anonymous RiboMotion authors· Zenodo (CERN European Organi...· 0 citations
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026