Rebeka Kiss

Transforming Academic References into Structured HTML with Mistral Le Chat

Academic writing increasingly relies on consistent, machine-readable formatting—especially when preparing manuscripts for digital publication, automated parsing, or citation indexing. This post demonstrates how the Mistral Le Chat can accurately convert plain-text bibliographic entries into structured HTML, generating both inline (short-form) citations and full bibliographic records with cross-linked anchors. This

by Rebeka Kiss

AI Writing Tools for Researchers: Getting Started with Grammarly and DeepL

Academic writing demands clarity, precision, and often the ability to work across multiple languages. In recent years, AI-powered writing tools have become indispensable aids for researchers looking to improve their manuscripts. Two popular options are Grammarly and DeepL, each offering distinct strengths. Grammarly is known for refining English writing (catching

by Rebeka Kiss

Assessing the FutureHouse Owl Agent’s Ability to Detect Defined Concepts in Academic Research

Following our previous evaluations of the FutureHouse Platform’s research agents this post turns to Owl, the platform’s tool for precedent and concept detection in academic literature. Owl is intended to help researchers determine whether a given concept has already been defined, thereby streamlining theoretical groundwork and avoiding redundant

by Rebeka Kiss

Comparing the FutureHouse Platform’s Falcon Agent and OpenAI’s o3 for Literature Search on Machine Coding for the Comparative Agendas Project

Having previously explored the FutureHouse Platform’s agents in tasks such as identifying tailor-made laws and generating a literature review on legislative backsliding, we now directly compare its Falcon agent and OpenAI’s o3. Our aim was to assess their performance on a focused literature search task: compiling a ranked

by Rebeka Kiss

Using Falcon for Writing a Literature Review on the FutureHouse Platform: Useful for Broad Topics, Not for Niche Concepts

The FutureHouse Platform, launched in May 2025, is a domain-specific AI environment designed to support various stages of scientific research. It provides researchers with access to four specialised agents — each tailored to a particular task in the knowledge production pipeline: concise information retrieval (Crow), deep literature synthesis (Falcon), precedent detection

by Rebeka Kiss

Human- or AI-Generated Text? What AI Detection Tools Still Can’t Tell Us About the Originality of Written Content

Can we truly distinguish between text produced by artificial intelligence and that written by a human author? As large language models become increasingly sophisticated, the boundary between machine-generated and human-crafted writing is growing ever more elusive. Although a range of detection tools claim to identify AI-generated text with high precision,

by Rebeka Kiss

Can AI Really Accelerate Scientific Discovery? A First Look at the FutureHouse Platform

As scientific research became increasingly data-intensive and fragmented across disciplines, the limitations of traditional research workflows became more apparent. In response to these structural challenges, FutureHouse — a nonprofit backed by Eric Schmidt — launched a platform in May 2025 featuring four specialised AI agents. Designed to support literature analysis, hypothesis development,

by Rebeka Kiss

Solving Health Insurance Demand and Social Loss Models Using Manus AI

Can a large language model accurately solve a university-level microeconomics exercise on health insurance? We tested Manus AI on a multi-part problem involving demand curves, list prices, out-of-pocket prices, and the calculation of social loss under various insurance schemes – including full insurance, coinsurance, and copayment plans. Not only did the

by Rebeka Kiss

How to Create Your Own Custom GPT

In our previous blog post, we examined how useful publicly available Custom GPTs are for academic tasks. While many showed promise, especially for brainstorming or outlining, they often fell short in areas where accuracy, source verification, and methodological transparency are crucial. In short: if your work demands high standards of

by Rebeka Kiss