Author: Adnan Hassan

Adnan Hassan
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Hello, My name is Adnan Hassan. I am a consulting intern at Marktechpost and soon to be a management trainee at American Express. I am currently pursuing a dual degree at the Indian Institute of Technology, Kharagpur. I am passionate about technology and want to create new products that make a difference.

Tsinghua University Researchers Propose Latent Consistency Models (LCMs): The Next Generation of Generative AI Models after Latent Diffusion Models (LDMs)

Latent Consistency Models (LCMs) efficiently generate high-resolution images by directly predicting augmented probability flow ODE solutions in latent space. This method eliminates the need...

Revolutionizing Document Parsing: Meet DSG – The First End-to-End Trainable System for Hierarchical Structure Extraction

The Document Structure Generator (DSG) is a powerful system for parsing and generating structured documents. DSG surpasses commercial OCR tools' capabilities and sets new...

UT Austin Researchers Introduce LIBERO: A Lifelong Robot Learning Benchmark to Study Knowledge Transfer in Decision-Making and Robotics at Scale

LIBERO, a lifelong learning benchmark in robot manipulation, focuses on knowledge transfer in declarative and procedural domains. It introduces five key research areas in...

Meet BOSS: A Reinforcement Learning (RL) Framework that Trains Agents to Solve New Tasks in New Environments with LLM Guidance

Introducing BOSS (Bootstrapping your own SkillS): a groundbreaking approach that leverages large language models to autonomously build a versatile skill library for tackling intricate...

Can We Generate Hyper-Realistic Human Images? This AI Paper Presents HyperHuman: A Leap Forward in Text-to-Image Models

Quantum computing is often heralded for its potential to revolutionize problem-solving, especially when classical computers face substantial limitations. While much of the discussion has...

Researchers from the National University of Singapore propose Show-1: A Hybrid Artificial Intelligence Model that Marries Pixel-Based and Latent-Based VDMs for Text-to-Video Generation

Researchers from the National University of Singapore introduced Show-1, a hybrid model for text-to-video generation that combines the strengths of pixel-based and latent-based video...

Researchers from NVIDIA Introduce Retro 48B: The Largest LLM Pretrained with Retrieval before Instruction Tuning

Researchers from Nvidia and the University of Illinois at Urbana Champaign introduce Retro 48B, a significantly larger language model than previous retrieval-augmented models like...

Meet Universal Simulator (UniSim): An Interactive Simulator of the Real World Interaction Through Generative Modeling

Generative models have transformed content creation in text, images, and videos. The next frontier is simulating realistic experiences triggered by human and agent actions....

Can Language Models Replace Programmers? Researchers from Princeton and the University of Chicago Introduce SWE-bench: An Evaluation Framework that Tests Machine Learning Models on...

Evaluating the proficiency of language models in addressing real-world software engineering challenges is essential for their progress. Enter SWE-bench, an innovative evaluation framework that...

This AI Research Proposes FireAct: A Novel Artificial Intelligence Approach to Fine-Tuning Language Models with Trajectories from Multiple Tasks and Agent Methods

Fine-tuning language models are often overlooked to create language agents, specifically focusing on enhancing their capabilities in question-answering tasks using the Google search API....

Can Compressing Retrieved Documents Boost Language Model Performance? This AI Paper Introduces RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation

Optimizing their performance while managing computational resources is a crucial challenge in an increasingly powerful language model era. Researchers from The University of Texas...

How Can We Effectively Compress Large Language Models with One-Bit Weights? This Artificial Intelligence Research Proposes PB-LLM: Exploring the Potential of Partially-Binarized LLMs

In Large Language Models (LLMs), Partially-Binarized LLMs (PB-LLM) is a cutting-edge technique for achieving extreme low-bit quantization in LLMs without sacrificing language reasoning capabilities....

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