#natural language processing

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6 papers match

cs.AI2026

AIriskEval-edu Demo: Auditing of Pedagogical Risks in Educational Explanations

Javier Irigoyen, Roberto Daza, Francisco Jurado +5

The paper introduces AIriskEval-edu Demo, a platform that audits the pedagogical quality of K-12 instructional explanations by evaluating five risk dimensions and providing binary…

#pedagogical risk assessment#educational explanations#explainable AI#large language models
cs.AI2026

AutoSynthesis: An agentic system for automated meta-analysis

Moein Taherinezhad, Sebastian Maier, Gerardo Vitagliano +2

AutoSynthesis is a multi‑agent AI system that takes a natural‑language research question and automatically conducts a full quantitative meta‑analysis, from literature search to eff…

#meta-analysis automation#multi-agent systems#evidence synthesis#natural language processing
physics.plasm-ph2026

Assessing the impact of Open Research Information Infrastructures using NLP driven full-text Scientometrics: A case study of the LXCat open-access platform

Kalp Pandya, Khushi Shah, Nirmal Shah +2

The paper introduces an NLP‑driven full‑text scientometric framework to evaluate the impact of open research information infrastructures, demonstrated on the LXCat open‑access plat…

#open research infrastructure#full-text analysis#natural language processing#plasma physics data
cs.AI2026

Theory-Level Autoformalization: From Isolated Statements to Unified Formal Knowledge Bases

Marcus J. Min, Mike He, Zhaoyu Li +5

The paper proposes shifting autoformalization from isolated statements to theory-level, aiming to automatically translate whole bodies of mathematical knowledge—including axioms, d…

#autoformalization#formal knowledge bases#theory formalization#natural language processing
cs.SE2026

Natural-Language to SysMLv2 Translation via Conformance-Driven Iterative Refinement

Chance LaVoie, Eladio Andujar Lugo, Taylan G. Topcu +1

The paper introduces a conformance‑checker‑driven framework that iteratively translates natural‑language descriptions into SysMLv2 models, using a generate‑check‑repair loop to ens…

#natural language processing#model-based systems engineering#sysmlv2#conformance checking
cs.SE2026

Faithful Autoformalization of Natural Language Assertions

Hongyi Liu, Madhusudan Parthasarathy, Adithya Murali

The paper introduces Monty, a framework that uses large language models to automatically translate natural‑language specifications into executable Java assertions, improving precis…

#autoformalization#natural language processing#formal verification#software testing