Research desk
The papers behind how we build
An annotated reading list. Every entry is credited to its original authors, with a note on what it changes once the idea meets a real system.
All entries
2 entries
- 2023NeurIPS 2023PublishedCurated
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Generalises chain-of-thought into a search tree. The model proposes multiple partial solutions, evaluates them against each other, and can back out of a branch that is not working, rather than committing to one linear line of reasoning.
- 2023NeurIPS 2023PublishedCurated
Reflexion: Language Agents with Verbal Reinforcement Learning
Instead of updating weights, the agent writes down what went wrong after a failed attempt and carries that reflection into the next attempt. The reflection is stored in natural language and used as additional context, so no gradient step is required.
Browse by topic
Foundations
The architectures and pre-training results everything else stands on.
3 entries
Retrieval & RAG
Grounding a model in documents you actually own.
5 entries
Reasoning
Getting a model to show its work, and checking the work.
6 entries
Agents & Tool Use
Models that call tools, hold state, and finish multi-step jobs.
8 entries
Adaptation
Changing what a model does without retraining all of it.
4 entries
Alignment
Steering outputs toward what a person would accept.
6 entries
Evaluation
How you know it works before a customer finds out it does not.
11 entries