A generative model for inorganic materials design (MatterGen)
Microsoft's MatterGen, in Nature in 2025, is a diffusion model that generates new crystal structures to order, then validated one experimentally.
Landmark Papers
What the papers actually said - linked to the originals.
644 entries, all primary-sourced
Constitutional Classifiers: Defending Against Universal Jailbreaks
Anthropic wraps a model in input and output classifiers trained on synthetic data, cutting jailbreak success below 5 percent.
BBC study: AI assistants distort news content
BBC research found that over half of AI-assistant answers about news had significant issues, including factual errors and altered quotes.
Emergent Misalignment: Narrow Finetuning Can Produce Broadly Misaligned LLMs
Fine-tuning a model on one narrow bad task, writing insecure code, made it broadly malicious across unrelated questions.
Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation
OpenAI found that pressuring a model's chain of thought to look clean teaches it to hide cheating rather than stop it.
Circuit Tracing: Revealing Computational Graphs in Language Models
Anthropic's method paper introducing cross-layer transcoders and attribution graphs to trace a model's computation.
On the Biology of a Large Language Model
Anthropic traced the internal circuits of Claude 3.5 Haiku, showing planning, multi-step reasoning, and unfaithful explanations.
AI as Normal Technology
Narayanan and Kapoor's 2025 essay arguing AI should be treated like past general-purpose technologies, not as looming superintelligence.
The Leaderboard Illusion
A 2025 critique showing private testing and unequal sampling can bias Chatbot Arena rankings.
The Illusion of Thinking
Apple researchers show reasoning models collapse to zero accuracy past a complexity threshold on puzzles.
Reuters Institute Digital News Report 2025 on AI and news
The Reuters Institute's 2025 survey found 7% of people use AI chatbots for news weekly, rising to 15% of under-25s, amid broad public scepticism.
Persona Vectors: Monitoring and Controlling Character Traits in Language Models
Anthropic identifies activation directions for traits like sycophancy or malice, then uses them to monitor and steer model character.
EBU/BBC study: AI assistants misrepresent news 45% of the time
A 22-broadcaster international study found 45% of AI-assistant news answers had a significant issue, consistent across languages and territories.
Natural Language Autoencoders: Turning Claude's Thoughts Into Text
Anthropic method that translates a model's internal activations into readable text, exposing thoughts the model never says out loud.
Teaching Claude Why: Reducing Agentic Misalignment
Anthropic finds that teaching a model the principles behind ethical behavior, not just examples, drove blackmail rates from up to 96 percent to near zero.
Gram: Assessing Sabotage Propensities via Automated Alignment Auditing
Google DeepMind framework that tests Gemini for sabotage across simulated deployments; most failures trace to role-play, not deliberate misalignment.
Realistic Honeypot Evaluations for Scheming Propensity
DeepMind plants scheming traps in its own codebases; Gemini does not scheme unprompted, but explicit agency prompts can elicit sabotage attempts.
Cosmos 3: Omnimodal World Models for Physical AI
NVIDIA's open Cosmos 3 unifies language, image, video, audio, and action in one architecture as a backbone for robots and embodied agents.
Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models
Ultralytics YOLO26 drops NMS and Distribution Focal Loss for NMS-free end-to-end real-time detection across five scales.
The Self-Correction Illusion: LLMs Correct Others but Not Themselves
Relabeling an LLM's own wrong claim as an external source raises its correction rate by 23 to 93 points.