​[[{“value”:” Retrieval-Augmented Generation (RAG) is a growing area of research focused on improving the capabilities of large language models (LLMs) by incorporating external knowledge sources. This approach involves two primary components: a retrieval module that finds relevant external information and a generation module that uses… Read More »FunnelRAG: A Novel AI Approach to Improving Retrieval Efficiency for Retrieval-Augmented Generation Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Alignment with human preferences has led to significant progress in producing honest, safe, and useful responses from Large Language Models (LLMs). Through this alignment process, the models are better equipped to comprehend and represent what humans think is suitable or important in their interactions.… Read More »Meet SynPO: A Self-Boosting Paradigm that Uses Synthetic Preference Data for Model Alignment Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have gained significant attention in data management, with applications spanning data integration, database tuning, query optimization, and data cleaning. However, analyzing unstructured data, especially complex documents, remains challenging in data processing. Recent declarative frameworks designed for LLM-based unstructured data processing… Read More »UC Berkeley Researchers Propose DocETL: A Declarative System that Optimizes Complex Document Processing Tasks using LLMs Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The rapid progress of text-to-image (T2I) diffusion models has made it possible to generate highly detailed and accurate images from text inputs. However, as the length of the input text increases, current encoding methods, such as CLIP (Contrastive Language-Image Pretraining), encounter various limitations. These… Read More »LongAlign: A Segment-Level Encoding Method to Enhance Long-Text to Image Generation Nazmi Syed Artificial Intelligence Category – MarkTechPost

​[[{“value”:” As large language models (LLMs) become increasingly capable and better day by day, their safety has become a critical topic for research. To create a safe model, model providers usually pre-define a policy or a set of rules. These rules help to ensure the… Read More »Controllable Safety Alignment (CoSA): An AI Framework Designed to Adapt Models to Diverse Safety Requirements without Re-Training Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Accelerating inference in large language models (LLMs) is challenging due to their high computational and memory requirements, leading to significant financial and energy costs. Current solutions, such as sparsity, quantization, or pruning, often require specialized hardware or result in decreased model accuracy, making efficient… Read More »Meta AI Releases LayerSkip: A Novel AI Approach to Accelerate Inference in Large Language Models (LLMs) Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Proteins, vital macromolecules, are characterized by their amino acid sequences, which dictate their three-dimensional structures and functions in living organisms. Effective generative protein modeling requires a multimodal approach to simultaneously understand and generate sequences and structures. Current methods often rely on separate models for… Read More »DPLM-2: A Multimodal Protein Language Model Integrating Sequence and Structural Data Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) can understand and generate human-like text across various applications. However, despite their success, LLMs often need help in mathematical reasoning, especially when solving complex problems requiring logical, step-by-step thinking. This research field is evolving rapidly as AI researchers explore new… Read More »MIND (Math Informed syNthetic Dialogue): How Structured Synthetic Data Improves the Mathematical and Logical Capabilities of AI-Powered Language Models Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have gained significant attention in AI research due to their impressive capabilities. However,  their limitation lies with long-term planning and complex problem-solving. While explicit search methods like Monte Carlo Tree Search (MCTS) have been employed to enhance decision-making in various… Read More »DIFFUSEARCH: Revolutionizing Chess AI with Implicit Search and Discrete Diffusion Modeling Sajjad Ansari Artificial Intelligence Category – MarkTechPost