Testing the Limits of AI Peer Review: When Even Ian Goodfellow Gets Rejected by OpenReviewer

High-quality feedback is essential for researchers aiming to improve their work and navigate the peer review process more effectively. Ideally, such feedback would be available before formal submission—allowing authors to identify the strengths and weaknesses of their research early on. This is precisely the promise of OpenReviewer, an automated

by Rebeka Kiss

Using Gemini for Grammar and Style Correction in Google Docs

Integrating Google’s Gemini assistant into Google Docs offers a lightweight yet effective solution for academic and professional editing tasks. Rather than relying on traditional spelling and grammar checkers, users can now issue custom prompts to Gemini—transforming the assistant into a real-time editorial aid capable of producing high-quality revisions

by 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

Automated LaTeX Generation From an Academic PDF: Practical Workflow Using GPT-4.1

Formatting academic manuscripts in LaTeX can be both laborious and technically demanding—especially when converting raw text into structured, publication-ready documents. This post presents a practical workflow using GPT-4.1 to automate manuscript formatting with remarkable precision. With a single, well-crafted prompt, the model generates clean LaTeX code with proper

by Rebeka Kiss

Zero-Shot Distal Fibula Fracture Detection: Gemini 2.5 Flash Delivers Spot-On Results on German Radiology Reports

Identifying specific clinical findings in unstructured medical texts is a common challenge in healthcare data science. In this post, we benchmark Google’s Gemini 2.5 Flash language model on a zero-shot classification task: detecting the presence or absence of distal fibula fractures in real-world German radiology reports. Without any

by Rebeka Kiss

Prompt-Based Disease Mention Extraction with DeepSeek-V3: A Biomedical NER Case Study on a Structured NCBI Test Set

Prompt-based methods are becoming increasingly relevant in biomedical text mining, offering flexible ways to perform tasks such as named entity recognition without explicit model training. In this case study, we assess the performance of DeepSeek-V3 on a structured disease mention extraction task using a curated subset of the NCBI Disease

by Rebeka Kiss

Unlocking Large Language Models via API: Capabilities, Access, and Practical Considerations

Accessing large language models (LLMs) through APIs opens up research and development opportunities that go well beyond the limits of traditional chat interfaces. For researchers API access enables language models to be built directly into bespoke workflows, analytical tools, or automated processes—supporting tasks such as large-scale text analysis, data

by Rebeka Kiss

Benchmarking GenAI Models for Penguin Species Prediction: Grok 3, DeepSeek-V3, and Qwen2.5-Max Delivered Top Results

How well can today’s leading GenAI models classify real-world biodiversity data—without bespoke code or traditional machine learning pipelines? In this study, we benchmarked a range of large language models on the task of predicting penguin species from tabular ecological measurements, including both numerical and categorical variables. Using a

by Rebeka Kiss