LLM Research Papers: The 2025 List (July to December)

LLM Research Papers: The 2025 List (January to June)

A topic-organized collection of 200+ LLM research papers from 2025

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

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

2023, year of open LLMs

Google's year in review: 8 areas with research breakthroughs in 2025

Google 2025 recap: Research breakthroughs of the year

The Exact ML Project I’d Build to Get Hired in 2026

Follow this framework to build a project that will impress hiring managers The post The Exact ML Project I’d Build to Get Hired in 2026 appeared first on Towards Data Science .

Note on 18th September 2026

Simon Willison reflects on his current disinterest in large language models (LLMs), comparing it to a geneticist dismissing the newly opened Jurassic Park. He emphasizes that this stance feels odd given the excitement surrounding LLMs. The note highlights his personal stance on AI and generative‑AI topics.

What We Learned by Reproducing 2,200 papers from ICML

LLM-Generated or Human-Written? Comparing Review and Non-Review Papers on ArXiv

arXiv:2601.17036v2 Announce Type: replace-cross Abstract: ArXiv recently prohibited the upload of unpublished review papers to its servers in the Computer Science domain, citing a high prevalence of...

Requests for Research 2.0

We’re releasing a new batch of seven unsolved problems which have come up in the course of our research at OpenAI.

A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026

A Round Up And Comparison of 10 Open-Weight LLM Releases in Spring 2026

The Scientific Contribution Graph: Automated Literature-based Technological Roadmapping at Scale

The paper introduces the Scientific Contribution Graph, a large-scale resource that extracts 6 million scientific contributions from 655 k open-access papers across multiple disciplines and links them with 36 million prerequisite edges. It frames automated technological roadmapping as the task of identifying contributions and their prerequisites, and presents a new scientific prerequisite prediction task where models forecast which existing technologies enable future discoveries. The authors report that current models achieve a 0.48 MAP score on temporally-filtered backtesting, indicating rapid progress in this area.

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.