Introduction: The Challenge of Memorization in Language Models Modern language models face increasing scrutiny regarding their memorization behavior. With models such as an 8-billion parameter transformer trained on 15 trillion tokens, researchers question whether these models memorize their training data in a meaningful way. Common techniques, including data extraction and membership inference, fall short as […] The post How Much Do Language Models Really Memorize? Meta’s New Framework Defines Model Capacity at the Bit Level appeared first on MarkTechPost. read more

LLMs primarily enhance accuracy through scaling pre-training data and computing resources. However, the attention has shifted towards alternate scaling due to finite data availability. This includes test-time training and inference compute scaling. Reasoning models enhance performance by emitting thought processes before answers, initially through CoT prompting. Recently, reinforcement learning (RL) post-training has been used. Scientific […] The post ether0: A 24B LLM Trained with Reinforcement Learning RL for Advanced Chemical Reasoning Tasks appeared first on MarkTechPost. read more

Reinforcement Learning’s Role in Fine-Tuning LLMs Reinforcement learning has emerged as a powerful approach to fine-tune large language models (LLMs) for more intelligent behavior. These models are already capable of performing a wide range of tasks, from summarization to code generation. RL helps by adapting their outputs based on structured feedback. As demand grows for […] The post Meta Introduces LlamaRL: A Scalable PyTorch-Based Reinforcement Learning RL Framework for Efficient LLM Training at Scale appeared first on MarkTechPost. read more

As AI-first development redefines how software is built, “vibe coding” has emerged as a paradigm-shifting approach where developers simply say what they want, and an agent builds it. Coined by Andrej Karpathy, the term reflects a shift from code-heavy workflows to natural language-driven software prototyping. Here’s a list of reliable vibe coding tools that support […] The post Top 15 Vibe Coding Tools Transforming AI-Driven Software Development in 2025 appeared first on MarkTechPost. read more

In this tutorial, we’ll learn how to harness the power of Google’s Gemini models alongside the flexibility of Pandas. We will perform both straightforward and sophisticated data analyses on the classic Titanic dataset. By combining the ChatGoogleGenerativeAI client with LangChain’s experimental Pandas DataFrame agent, we’ll set up an interactive “agent” that can interpret natural-language queries. […] The post Build a Gemini-Powered DataFrame Agent for Natural Language Data Analysis with Pandas and LangChain appeared first on MarkTechPost. read more

Early large language models (LLMs) excelled at generating coherent text; however, they struggled with tasks that required precise operations, such as arithmetic calculations or real-time data lookups. The emergence of tool-augmented agents has bridged this gap by endowing LLMs with the ability to invoke external APIs and services, effectively combining the breadth of language understanding […] The post From Text to Action: How Tool-Augmented AI Agents Are Redefining Language Models with Reasoning, Memory, and Autonomy appeared first on MarkTechPost. read more

Bridging Perception and Action in Robotics Multimodal Large Language Models (MLLMs) hold promise for enabling machines, such as robotic arms and legged robots, to perceive their surroundings, interpret scenarios, and take meaningful actions. The integration of such intelligence into physical systems is advancing the field of robotics, pushing it toward autonomous machines that don’t just […] The post VeBrain: A Unified Multimodal AI Framework for Visual Reasoning and Real-World Robotic Control appeared first on MarkTechPost. read more

Despite the substantial progress in text-to-image (T2I) generation brought about by models such as DALL-E 3, Imagen 3, and Stable Diffusion 3, achieving consistent output quality — both in aesthetic and alignment terms — remains a persistent challenge. While large-scale pretraining provides general knowledge, it is insufficient to achieve high aesthetic quality and alignment. Supervised […] The post Yandex Releases Alchemist: A Compact Supervised Fine-Tuning Dataset for Enhancing Text-to-Image T2I Model Quality appeared first on MarkTechPost. read more

Large reasoning models, often powered by large language models, are increasingly used to solve high-level problems in mathematics, scientific analysis, and code generation. The central idea is to simulate two types of cognition: rapid responses for simpler reasoning and deliberate, slower thought for more complex problems. This dual-mode thinking reflects how humans transition from intuitive […] The post ALPHAONE: A Universal Test-Time Framework for Modulating Reasoning in AI Models appeared first on MarkTechPost. read more

In this tutorial, we’ll explore how to create smart, multi-agent workflows using the Mistral Agents API’s Handoffs feature. This lets different agents work together by passing tasks to each other, enabling complex problems to be solved in a modular and efficient way. We’ll build a system where agents collaborate to answer inflation-related questions—performing calculations, fetching […] The post How to Create Smart Multi-Agent Workflows Using the Mistral Agents API’s Handoffs Feature appeared first on MarkTechPost. read more