Paving the way for greener ammonia production
New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that's essential to fertilizer and other products.
More from the blog
A better way to turn 2D designs into 3D models for rapid prototyping
Researchers developed an automated framework that helps AI models generate CAD programs more accurately and efficiently.
A better way to model the behavior of metal alloys
MIT researchers’ approach captures subtle atomic patterns, improving predictions of material properties.
Designing the hf CLI as an agent-optimized way to work with the Hub
Four ways Google Research scientists have been using Empirical Research Assistance
Data Mining & Modeling
Related papers
Jailbreaking in the Haystack
NINJA (short for Needle-in-haystack jailbreak attack), a method that jailbreaks aligned LMs by appending benign, model-generated content to harmful user goals to reveal fundamental vulnerabilities in modern LMs.
Convergent Evolution: How Different Language Models Learn Similar Number Representations
This paper identifies two different routes through which models can acquire geometrically separable features: they can learn them from complementary co-occurrence signals in general language data, including text-number co-occurrence and cross-number interaction, or from multi-token addition problems.
SimulRAG: Simulator-based RAG for Grounding LLMs in Long-form Scientific QA
SimulRAG, a simulator-based RAG framework with a generalized retrieval interface that translates between text and simulator parameters/outputs, is proposed, which improves informativeness and factuality over the strongest adapted RAG baselines, while UE+SBA enhances claim-level efficiency and quality.
Evaluating and Explaining Prompt Sensitivity of LLMs Using Interactions
Interactions are introduced as a fine-grained tool to analyze prompt sensitivity of LLMs and it is discovered that subtle changes to prompts can trigger severe instability in interactions, even when the outputs of the LLM remain the same.