LLM Research Papers: The 2026 List (January to May)
A January-May 2026 list of notable LLM research papers, covering new models, training methods, agents, reasoning, and efficiency improvements.
paperswithcode
Coding agents for data analysis
Here's the handout I prepared for my NICAR 2026 workshop "Coding agents for data analysis" - a three hour session aimed at data journalists demonstrating ways that tools like Claude …
LLM Research Papers: The 2025 List (July to December)
In June, I shared a bonus article with my curated and bookmarked research paper lists to the paid subscribers who make this Substack possible.
LLM Research Papers: The 2025 List (July to December)
A curated list of LLM research papers from July–December 2025, organized by reasoning models, inference-time scaling, architectures, training efficiency, and...
Reasoning
Reinforcement Learning
How To Build an LLM-Powered App To Chat with PapersWithCode
Keep up with the latest ML research
ArXiv.org Reaches a Milestone and a Reckoning
Runaway success and underfunding have led to growing pains for the preprint server
PyTorch vs TensorFlow in 2023
Should you use PyTorch vs TensorFlow in 2023? This guide walks through the major pros and cons of PyTorch vs TensorFlow, and how you can pick the right framework.
louisfb01/best_AI_papers_2021: A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation…
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code. - louisfb01/best_AI_papers_2021
Four Deep Learning Papers to Read in December 2021
From Sensory Substitution to Decision Transformers, Persistent Evolution Strategies and Sharpness-Aware Minimization
Papers with Code - Paper with Code Newsletter
Papers With Code highlights trending Machine Learning research and the code to implement it.
The Methods Corpus | Papers With Code
2284 methods • 143838 papers with code.
Papers with Code 2020 Review
Papers with Code indexes various machine learning artifacts — papers, code, results — to facilitate discovery and comparison. Using this…
Methodology | Papers With Code
**Representation Learning** is a process in machine learning where algorithms extract meaningful patterns from raw data to create representations that are easier to understand and process. These representations can be designed for interpretability, reveal hidden features, or be…
Computer Vision | Papers With Code
**Image Retrieval** is a fundamental and long-standing computer vision task that involves finding images similar to a provided query from a large database. It's often considered as a form of fine-grained, instance-level classification. Not just integral to image recognition…
Computer Vision | Papers With Code
**Denoising** is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of…
Computer Vision | Papers With Code
**Domain Adaptation** is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized…