Google’s Groundbreaking Non-Autoregressive, LM-Fused ASR System for Multilingual Speech Recognition
Speech recognition technology has come a long way, revolutionizing how humans interact with machines and enabling a wide range of
Read More
Author: Rishabh Dwivedi
Google AI Presents Lumiere: A Space-Time Diffusion Model for Video Generation
In recent years, generative models have made significant advancements in tasks such as text-to-image (T2I) generation, producing high-resolution, realistic images
Read More
Google DeepMind Researchers Propose WARM: A Novel Approach to Tackle Reward Hacking in Large Language Models Using Weight-Averaged Reward Models
In recent years, Large Language Models (LLMs) have revolutionized the field of natural language processing by achieving remarkable performance in
Read More
Revolutionizing Uncertainty Quantification in Deep Neural Networks Using Cycle Consistency
Deep neural networks have revolutionized the field of artificial intelligence, enabling breakthroughs in various domains such as computer vision, natural
Read More
Meet einx: A Python Library that Allows Formulating Many Tensor Operations as Concise Expressions Using Einstein Notation
The field of machine learning and artificial intelligence heavily relies on tensor operations for data manipulation and analysis. Tensors, which
Read More
Harnessing the Power of Abstract Syntax Trees (ASTs) to Revolutionize Code-Centric Language Models
The field of language models has witnessed remarkable advancements in recent years, with significant progress made in code generation and
Read More
Group Preference Optimization (GPO): A Revolutionary Approach to Aligning Language Models with User Preferences
Language models have become an indispensable tool in various domains, ranging from creative writing to chatbots and semantic search. These
Read More
Predicting Biological Age and Understanding Epigenetic Mechanisms: A Breakthrough in AI Research
As our understanding of aging continues to evolve, scientists and researchers are constantly seeking new ways to accurately predict biological
Read More
Exploring the Intricacies of Self-Correction in Language Models: Unveiling Logical Errors and Backtracking Efficacy
Language Models (LMs) have become an integral part of many AI applications, enabling tasks such as answering questions, completing tasks,
Read More
Transformers in Reinforcement Learning: Enhancing Memory and Overcoming Credit Assignment Challenges
Reinforcement learning (RL) has made significant advancements in recent years, thanks to the integration of Transformer architectures. Transformers are known
Read More