marktechpost3d
OneGen: An AI Framework that Enables a Single LLM to Handle both Retrieval and Generation Simultaneously
A major challenge in the current deployment of Large Language Models (LLMs) is their inability to efficiently manage tasks that require both generation and retrieval of information. While LLMs excel ...
marktechpost3d
Assessing the Capacity of Large Language Models to Generate Innovative Research Ideas: Insights from a Study with Over 100 NLP Experts
Research idea generation methods have evolved through techniques like iterative novelty boosting, multi-agent collaboration, and multi-module retrieval. These approaches aim to enhance idea quality ...
marktechpost3d
gsplat: An Open-Source Python Library for Gaussian Splatting
Gaussian Splatting is a novel 3D rendering technique representing a scene as a collection of 3D Gaussian functions. These Gaussians are splatted, or projected, onto the image plane, enabling faster ...
marktechpost3d
FutureHouse Researchers Introduce PaperQA2: The First AI Agent that Conducts Entire Scientific Literature Reviews on Its Own
Artificial intelligence (AI) is transforming the way scientific research is conducted, especially through language models that assist researchers with processing and analyzing vast amounts of ...
marktechpost3d
Advancing Social Network Analysis: Integrating Stochastic Blockmodels, Reciprocity, and Bayesian Approaches
The use of relational data in social science has surged over the past two decades, driven by interest in network structures and their behavioral implications. However, the methods for analyzing such ...
marktechpost4d
Microsoft Researchers Propose MedFuzz: A New AI Method for Evaluating the Robustness of Medical Question-Answering LLMs to Adversarial Perturbations
Medical question-answering systems have become a research focus due to their potential to assist clinicians in making accurate diagnoses and treatment decisions. These systems utilize large language ...
marktechpost3d
Top 9 Different Types of Retrieval-Augmented Generation (RAGs)
Retrieval-Augmented Generation (RAG) is a machine learning framework that combines the advantages of both retrieval-based and generation-based models. The RAG framework is highly regarded for its ...
marktechpost6d
Understanding the Hidden Layers in Large Language Models LLMs
Hebrew University Researchers addressed the challenge of understanding how information flows through different layers of decoder-based large language models (LLMs). Specifically, it investigates ...
marktechpost4d
Automating Reinforcement Learning Workflows with Vision-Language Models: Towards Autonomous Mastery of Robotic Tasks
Recent advancements in utilizing large vision language models (VLMs) and language models (LLMs) have significantly impacted reinforcement learning (RL) and robotics. These models have demonstrated ...
marktechpost3d
Graphiti: A Python Library for Building Temporal Knowledge Graphs Using LLMs
The challenge of managing and recalling facts from complex, evolving conversations is a key problem for many AI-driven applications. As information grows and changes over time, maintaining accurate ...
marktechpost4d
LLM-CI: A New Machine Learning Framework to Assess Privacy Norms Encoded in LLMs
Large language models (LLMs) are widely implemented in sociotechnical systems like healthcare and education. However, these models often encode societal norms from the data used during training, ...
marktechpost6d
Optimizing Document Understanding with DocOwl2: A Novel High-Resolution Compression Architecture
Understanding multi-page documents and news videos is a common task in human daily life. To tackle such scenarios, Multimodal Large Language Models (MLLMs) should be equipped with the ability to ...