​[[{“value”:” Deep learning models typically represent knowledge statically, making adapting to evolving data needs and concepts challenging. This rigidity necessitates frequent retraining or fine-tuning to incorporate new information, which could be more practical. The research paper “Towards Flexible Perception with Visual Memory” by Geirhos et… Read More »Google DeepMind Researchers Propose a Dynamic Visual Memory for Flexible Image Classification Shreya Maji Artificial Intelligence Category – MarkTechPost

​[[{“value”:” LLMs have revolutionized artificial intelligence, particularly natural language processing and software engineering. Models useful for specific tasks such as generating, understanding, and translating text are being integrated into many applications. Because of their nature, LLMs, like OpenAI’s ChatGPT and GPT-4, have interacted extensively with… Read More »Understanding the 27 Unique Challenges in Large Language Model Development: An Empirical Study of Over 29,000 Developer Forum Posts and 54% Unresolved Issues Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In the field of Natural Language Processing (NLP), Retrieval Augmented Generation, or RAG, has attracted much attention lately. Breaking down documents into chunks, embedding those chunks, storing the embeddings, and then finding the closest match and adding it to the query context when receiving… Read More »The Challenges of Implementing Retrieval Augmented Generation (RAG) in Production Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” A Large Language Model (LLM) is an advanced type of artificial intelligence designed to understand and generate human-like text. It’s trained on vast amounts of data, enabling it to perform various natural language processing tasks, such as answering questions, summarizing content, and engaging in… Read More »FlexEval: An Open-Source AI Tool for Chatbot Performance Evaluation and Dialogue Analysis Mahmoud Ghorbel Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Language model alignment is quite important, particularly in a subset of methods from RLHF that have been applied to strengthen the safety and competence of AI systems. Language models are deployed in many applications today, and their outputs can be harmful or biased. Inherent… Read More »USC Researchers Present Safer-Instruct: A Novel Pipeline for Automatically Constructing Large-Scale Preference Data Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Future reward estimation is crucial in RL as it predicts the cumulative rewards an agent might receive, typically through Q-value or state-value functions. However, these scalar outputs lack detail about when or what specific rewards the agent anticipates. This limitation is significant in applications… Read More »Enhancing Reinforcement Learning Explainability with Temporal Reward Decomposition Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Vision-language models (VLMs) have gained significant attention due to their ability to handle various multimodal tasks. However, the rapid proliferation of benchmarks for evaluating these models has created a complex and fragmented landscape. This situation poses several challenges for researchers. Implementing protocols for numerous… Read More »UniBench: A Python Library to Evaluate Vision-Language Models VLMs Robustness Across Diverse Benchmarks Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have gained prominence in deep learning, demonstrating exceptional capabilities across various domains such as assistance, code generation, healthcare, and theorem proving. The training process for LLMs typically involves two stages: pretraining with massive corpora and an alignment step using Reinforcement… Read More »Meta AI and NYU Researchers Propose E-RLHF to Combat LLM Jailbreaking Mohammad Asjad Artificial Intelligence Category – MarkTechPost