​[[{“value”:” Large language models (LLMs) have shown their potential in many natural language processing (NLP) tasks, like summarization and question answering using zero-shot and few-shot prompting approaches. However, prompting alone is not enough to make LLMs work as agents who can navigate environments to solve… Read More »This AI Paper Explores the Extent to which LLMs can Self-Improve their Performance as Agents in Long-Horizon Tasks in a Complex Environment Using the WebArena Benchmark Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Current methods for aligning LLMs often match the general public’s preferences, assuming this is ideal. However, this overlooks the diverse and nuanced nature of individual preferences, which are difficult to scale due to the need for extensive data collection and model training for each… Read More »Aligning Large Language Models with Diverse User Preferences Using Multifaceted System Messages: The JANUS Approach Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Here is a list of top 12 Trending LLM Leaderboards: A Guide to Leading AI Models’ Evaluation Open LLM Leaderboard With numerous LLMs and chatbots emerging weekly, it’s challenging to discern genuine advancements from hype. The Open LLM Leaderboard addresses this by using the… Read More »Top 12 Trending LLM Leaderboards: A Guide to Leading AI Models’ Evaluation Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Despite the advancements in LLMs, the current models still need to continually improve to incorporate new knowledge without losing previously acquired information, a problem known as catastrophic forgetting. Current methods, such as retrieval-augmented generation (RAG), have limitations in performing tasks that require integrating new… Read More »Neurobiological Inspiration for AI: The HippoRAG Framework for Long-Term LLM Memory Shreya Maji Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The crucial challenge of enhancing logical reasoning capabilities in Large Language Models (LLMs) is pivotal for achieving human-like reasoning, a fundamental step towards realizing Artificial General Intelligence (AGI). Current LLMs exhibit impressive performance in various natural language tasks but often need more logical reasoning,… Read More »Symbolic Chain-of-Thought ‘SymbCoT’: A Fully LLM-based Framework that Integrates Symbolic Expressions and Logic Rules with CoT Prompting Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Ordered sequences, including text, audio, and code, rely on position information for meaning. Large language models (LLMs), like the Transformer architecture, lack inherent ordering information and treat sequences as sets. Position Encoding (PE) addresses this by assigning an embedding vector to each position, which… Read More »Contextual Position Encoding (CoPE): A New Position Encoding Method that Allows Positions to be Conditioned on Context by Incrementing Position only on Certain Tokens Determined by the Model Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” IBM plays a crucial role in advancing AI by developing cutting-edge technologies and offering comprehensive courses. Through its AI initiatives, IBM empowers learners to harness the potential of AI in various fields. Its courses provide practical skills and knowledge, enabling individuals to implement AI… Read More »Top AI Courses Offered by IBM Shobha Kakkar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Handling and retrieving information from various file types can be challenging. People often struggle with extracting content from PDFs and spreadsheets, especially when dealing with large volumes. This process can be time-consuming and inefficient, making it difficult to use the extracted information effectively for… Read More »LlamaParse: An API by LlamaIndex to Efficiently Parse and Represent Files for Efficient Retrieval and Context Augmentation Using LlamaIndex Frameworks Niharika Singh Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In Neural Networks, understanding how to optimize performance with a given computational budget is crucial. More processing power devoted to training neural networks usually results in better performance. However, choosing between expanding the training dataset and raising the model’s parameters is crucial when scaling… Read More »Data Complexity and Scaling Laws in Neural Language Models Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have proven their potential to handle multiple tasks and perform extremely well across various applications. However, it is challenging for LLMs to generate accurate information, especially when the knowledge is less represented in their training data. To overcome this challenge,… Read More »Nearest Neighbor Speculative Decoding (NEST): An Inference-Time Revision Method for Language Models to Enhance Factuality and Attribution Using Nearest-Neighbor Speculative Decoding Sajjad Ansari Artificial Intelligence Category – MarkTechPost