marktechpost4d
Thinking LLMs: How Thought Preference Optimization Transforms Language Models to Perform Better Across Logic, Marketing, and Creative Tasks
Large language models (LLMs) have evolved to become powerful tools capable of understanding and responding to user instructions. Based on the transformer architecture, these models predict the next ...
marktechpost3d
Google AI Research Examines Random Circuit Sampling (RCS) for Evaluating Quantum Computer Performance in the Presence of Noise
Quantum computers are a revolutionary technology that harnesses the principles of quantum mechanics to perform calculations that would be infeasible for classical computers. Evaluating the performance ...
marktechpost4d
Embodied Agent Interface: An AI Framework for Benchmarking Large Language Models (LLMs) for Embodied Decision Making
Large Language Models (LLMs) need to be evaluated within the framework of embodied decision-making, i.e., the capacity to carry out activities in either digital or physical environments. Even with all ...
marktechpost4d
Orthrus: A Mamba-based RNA Foundation Model Designed to Push the Boundaries of RNA Property Prediction
Despite the vast accumulation of genomic data, the RNA regulatory code must still be better understood. Genomic foundation models, pre-trained on large datasets, can adapt RNA representations for ...
marktechpost6d
Researchers from Moore Threads AI Introduce TurboRAG: A Novel AI Approach to Boost RAG Inference Speed
High latency in time-to-first-token (TTFT) is a significant challenge for retrieval-augmented generation (RAG) systems. Existing RAG systems, which concatenate and process multiple retrieved document ...
marktechpost3d
AutoDAN-Turbo: A Black-Box Jailbreak Method for LLMs with a Lifelong Agent
Large language models (LLMs) have gained widespread adoption due to their advanced text understanding and generation capabilities. However, ensuring their responsible behavior through safety alignment ...
marktechpost4d
MentalArena: A Self-Play AI Framework Designed to Train Language Models for Diagnosis and Treatment of Mental Health Disorders
In today’s fast-paced and interconnected world, mental health is more important than ever. The constant pressures of work, social media, and global events can take a toll on our emotional and ...
marktechpost4d
Google AI Research Introduces Process Advantage Verifiers: A Novel Machine Learning Approach to Improving LLM Reasoning Capabilities
Large language models (LLMs) have become crucial in natural language processing, particularly for solving complex reasoning tasks. These models are designed to handle mathematical problem-solving, ...
marktechpost4d
A New Study by OpenAI Explores How Users’ Names can Impact ChatGPT’s Responses
Bias in AI-powered systems like chatbots remains a persistent challenge, particularly as these models become more integrated into our daily lives. A pressing issue concerns biases that can manifest ...
marktechpost5d
This AI Paper by MIT Introduces Adaptive Computation for Efficient and Cost-Effective Language Models
Language models (LMs) are widely utilized across domains like mathematics, coding, and reasoning to handle complex tasks. These models rely on deep learning techniques to generate high-quality outputs ...
marktechpost6d
Exposing Vulnerabilities in Automatic LLM Benchmarks: The Need for Stronger Anti-Cheating Mechanisms
Automatic benchmarks like AlpacaEval 2.0, Arena-Hard-Auto, and MTBench have gained popularity for evaluating LLMs due to their affordability and scalability compared to human evaluation. These ...
marktechpost6d
F5-TTS: A Fully Non-Autoregressive Text-to-Speech System based on Flow Matching with Diffusion Transformer (DiT)
The current challenges in text-to-speech (TTS) systems revolve around the inherent limitations of autoregressive models and their complexity in aligning text and speech accurately. Many conventional ...