Blog
Optimizing Compound AI Systems
We echo through this blog that the optimization framework for compound AI systems should achieve
AmbigNLG: A Tutorial
AmbigNLG tackles ambiguity in Natural Language Generation (NLG) instructions by identifying unclear specifications and refining
Your Internship in the AI Industry: A Student’s Guide
Many of us have seen the memes of jobs asking for years of experience from
Megagon Labs Summer 2024 Internship Experience
Through this inside peek at our internship program, explore the types of projects we at
MEGAnno in Action: Human-LLM Collaborative Annotation
MEGAnno combines the power of large language models (LLMs) with human expertise to streamline and
NAACL 2024 Highlights & Big Trends Shaping NLP
Drawing from our experience at the NAACL conference, the Megagon Labs team has crafted this
Unlocking the Potential of Transformers for Long-Form Text Matching: A Simple yet Powerful Approach
Long-form text matching is a critical problem to solve in the field of Natural Language
Order Matters: Assessing LLM Sensitivity in Multiple-Choice Tasks
Explore the relationship between option arrangement and performance variations in Large Language Models (LLMs) during
Towards Enterprise Compound AI Systems
Researchers at Megagon Labs have been exploring how we can address the challenges of building
Deep Dive with WiTQA: When Does Retrieval Augmentation Help (or Hurt) Language Models?
The article presents the WiTQA dataset, designed to assess the impact of retrieval on the
Watchog: Leveraging Contrastive Learning for Enhanced Table Understanding and Column Annotation
By enabling robust and accurate column annotation, this innovative framework holds the potential to revolutionize
Team Profile: Jin Wang, Research Lead & Research Scientist
This article offers a glimpse into the dynamic research environment at Megagon Labs, where researchers