A Technical Roadmap to Context Engineering in LLMs: Mechanisms, Benchmarks, and Open Challenges
Estimated reading time: 4 minutes The paper “A Survey of Context Engineering for Large Language Models” establishes Context Engineering as ...
Tag: LLMs
Falcon LLM Team Releases Falcon-H1 Technical Report: A Hybrid Attention–SSM Model That Rivals 70B LLMs
Introduction The Falcon-H1 series, developed by the Technology Innovation Institute (TII), marks a significant advancement in the evolution of large ...
Too Much Thinking Can Break LLMs: Inverse Scaling in Test-Time Compute
Recent advances in large language models (LLMs) have encouraged the idea that letting models “think longer” during inference usually improves ...
Implementing Self-Refine Technique Using Large Language Models LLMs
This tutorial demonstrates how to implement the Self-Refine technique using Large Language Models (LLMs) with Mirascope, a powerful framework for ...
What is RAG in fintech and how financial services are using it with LLMs to power AI innovation: By John Adam
To operate, organisations in the financial services sector require hundreds of thousands of documents of rich, contextualised data. And to ...
This “smart coach” helps LLMs switch between text and code | MIT News
Large language models (LLMs) excel at using textual reasoning to understand the context of a document and provide a logical ...
Study could lead to LLMs that are better at complex reasoning | MIT News
For all their impressive capabilities, large language models (LLMs) often fall short when given challenging new tasks that require complex ...
University of Michigan Researchers Propose G-ACT: A Scalable Machine Learning Framework to Steer Programming Language Bias in LLMs
LLMs and the Need for Scientific Code Control LLMs have rapidly evolved into complex natural language processors, enabling the development ...
LLMs factor in unrelated information when recommending medical treatments | MIT News
A large language model (LLM) deployed to make treatment recommendations can be tripped up by nonclinical information in patient messages, ...
OThink-R1: A Dual-Mode Reasoning Framework to Cut Redundant Computation in LLMs
The Inefficiency of Static Chain-of-Thought Reasoning in LRMs Recent LRMs achieve top performance by using detailed CoT reasoning to solve ...
