The NLP Course is becoming the LLM Course

Letting Large Models Debate: The First Multilingual LLM Debate Competition

The State Of LLMs 2025: Progress, Problems, and Predictions

A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.

Learning to reason with LLMs

LLM Research Papers: The 2026 List (January to May)

A curated roundup of notable LLM research papers that came out this year

Do LLMs Understand Limit Order Book Dynamics?

A large language model trained on synthetic limit order book data can generate valid sequences of LOB events with near‑perfect accuracy, yet its internal world model does not capture the true state of the book. This shortfall results in biased estimates and misleading predictability when the model is used to forecast future LOB events. The study introduces new tests for an LLM’s world model, extending previous deterministic analyses to the stochastic dynamics inherent in limit order books.

My Workflow for Understanding LLM Architectures

A learning-oriented workflow for understanding new open-weight model releases