Author: Vibhanshu Patidar

Vibhanshu Patidar
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Vibhanshu Patidar is a consulting intern at MarktechPost. Currently pursuing B.S. at Indian Institute of Technology (IIT) Kanpur. He is a Robotics and Machine Learning enthusiast with a knack for unraveling the complexities of algorithms that bridge theory and practical applications.

Unveiling Player Insights: A Novel Machine Learning Approach to Understanding Gaming Behavior

In the ever-evolving mobile gaming world, delivering a truly personalized and engaging experience has become an important objective. However, traditional methods of understanding player...

CT-LLM: A 2B Tiny LLM that Illustrates a Pivotal Shift Towards Prioritizing the Chinese Language in Developing LLMs

For too long, the world of natural language processing has been dominated by models that primarily cater to the English language. This inherent bias...

ST-LLM: An Effective Video-LLM Baseline with Spatial-Temporal Sequence Modeling Inside LLM

The world of artificial intelligence has been abuzz with the remarkable achievements of Large Language Models (LLMs) like GPT, PaLM, and LLaMA. These models...

Researchers at the University of Glasgow Propose Shallow Cross-Encoders as an AI-based Solution for Low-Latency Information Retrieval

In our rapidly evolving digital world, the demand for instant gratification has never been higher. Whether we're searching for information, products, or services, we...

To Unveil the AI Black Box: Researchers at Imperial College London Proposes a Machine Learning Framework for Making AI Explain Itself

In our rapidly advancing artificial intelligence (AI) world, we have witnessed remarkable breakthroughs in natural language processing (NLP) capabilities. From virtual assistants that can...

ETH Zurich Researchers Unveil New Insights into AI’s Compositional Learning Through Modular Hypernetworks

From a young age, humans exhibit an incredible ability to recombine their knowledge and skills in novel ways. A child can effortlessly combine running,...

LUMOS: An Open-Source Generalizable Language Agent Training Framework

Imagine having a digital assistant that can not only answer your questions but also navigate the web, solve complex math problems, write code, and...

AgentStudio: An Open Toolkit for Developing General-Purpose Agents Capable of Operating in Digital Worlds

In our rapidly evolving digital landscape, the quest to develop autonomous virtual agents capable of navigating the vast expanse of software tools has captured...

FedFixer: A Machine Learning Algorithm with the Dual Model Structure to Mitigate the Impact of Heterogeneous Noisy Label Samples in Federated Learning

In today's world, where data is distributed across various locations and privacy is paramount, Federated Learning (FL) has emerged as a game-changing solution. It...

Researchers at Microsoft Propose AllHands: A Novel Machine Learning Framework Designed for Large-Scale Feedback Analysis Through a Natural Language Interface

In today's digital age, software developers and product teams are inundated with user feedback from various channels – app reviews, forum posts, social media...

Google DeepMind Researchers Introduce TacticAI: A New Deep Learning System that is Reinventing Football Strategy

Football has always been a game of tactical brilliance and strategic genius. From the dugouts of your local parks to the hallowed turf of...

The RAFT Way: Teaching Language AI to Become Domain Experts

Today's language models are mind-blowingly brilliant...for generalists. Ask them about history, science, or current events; they'll dazzle you with many facts and insights. But...

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