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Posts

Reinforcement learning for NLP

10 minute read

Published: March 16, 2026

In my last post, I talked about applying an originally image-based machine learning method to language, and the challenges that came with it. Today, we’re going to be discussing a similar topic—specifically, Reinforcement Learning (RL) for NLP reasoning. Though not initially used for LLMs, RL has a number of benefits when applied to LLMs. Specifically, RL allows LLMs to learn how to create outputs with specific goals in mind.

Diffusion in language models, and rethinking thought

9 minute read

Published: February 09, 2026

Diffusion in language models, and rethinking thought

Dissociating Language and Thought in LLMs

10 minute read

Published: January 14, 2026

Dissociating Language and Thought in LLMs

This post is an overview of the paper: Dissociating Language and Thought in Large Language Models: A Cognitive Perspective by Mahowald and Ivanova et al. The paper is linked here: https://arxiv.org/abs/2301.06627

Faithful Chain of Thought

6 minute read

Published: December 28, 2025

Faithful Chain-of-Thought Reasoning

This post is an overview of the paper: Faithful Chain-of-Thought Reasoning by Lyu, Havaldar, Stein et al. The paper is linked here: https://arxiv.org/pdf/2310.15164

LINC: Neurosymbolic reasoning approach for LLM

6 minute read

Published: December 20, 2025

LINC: Neurosymbolic Reasoning for LLMs

This post is an overview of the paper: LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers by Olausson et al. The paper is linked here: https://arxiv.org/pdf/2310.15164