Reinforcement Learning

Anthropic AI has launched Claude 3.5 Sonnet, marking the first release in its new Claude 3.5 model family. This latest iteration of Claude brings significant advancements in AI capabilities, setting a new benchmark in the industry...
Large Language Models (LLMs) have gained significant attention in the field of simultaneous speech-to-speech translation (SimulS2ST). This technology has become crucial for low-latency communication in various scenarios, such as international conferences, live broadcasts, and online subtitles....

Recall to Imagine (R2I): A New Machine Learning Approach that Enhances Long-Term Memory by Incorporating State Space Models into Model-based Reinforcement Learning (MBRL)

With the recent advancements in the field of Machine Learning (ML), Reinforcement Learning (RL), which is one of its branches, has become significantly popular....

Researchers at the University of Oxford Introduce Craftax: A Machine Learning Benchmark for Open-Ended Reinforcement Learning

Building and using appropriate benchmarks is a major driver of advancement in RL algorithms. For value-based deep RL algorithms, there's the Arcade Learning Environment;...

Researchers from CMU and Peking Introduces ‘DiffTOP’ that Uses Differentiable Trajectory Optimization to Generate the Policy Actions for Deep Reinforcement Learning and Imitation Learning

According to recent studies, a policy's depiction can significantly affect learning performance. Policy representations such as feed-forward neural networks, energy-based models, and diffusion have...

This AI Paper Introduces StepCoder: A Novel Reinforcement Learning Framework for Code Generation

Large language models (LLMs) are advancing the automation of computer code generation in artificial intelligence. These sophisticated models, trained on extensive datasets of programming...

UC Berkeley Researchers Introduce SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning

In recent years, researchers in the field of robotic reinforcement learning (RL) have achieved significant progress, developing methods capable of handling complex image observations,...

Researchers from Université de Montréal and Princeton Tackle Memory and Credit Assignment in Reinforcement Learning: Transformers Enhance Memory but Face Long-term Credit Assignment Challenges

Reinforcement learning (RL) has witnessed significant strides in integrating Transformer architectures, which are known for their proficiency in handling long-term dependencies in data. This...

Meta AI Researchers Open-Source Pearl: A Production-Ready Reinforcement Learning AI Agent Library

Reinforcement Learning (RL) is a subfield of Machine Learning in which an agent takes suitable actions to maximize its rewards. In reinforcement learning, the...

Researchers at UC Berkeley Introduced RLIF: A Reinforcement Learning Method that Learns from Interventions in a Setting that Closely Resembles Interactive Imitation Learning

Researchers from UC Berkeley introduce an unexplored approach to learning-based control problems, integrating reinforcement learning (RL) with user intervention signals. Utilizing off-policy RL on...

This AI Research from MIT and Meta AI Unveils an Innovative and Affordable Controller for Advanced Real-Time In-Hand Object Reorientation in Robotics

Researchers from MIT and Meta AI have developed an object reorientation controller that can utilize a single depth camera to reorient diverse shapes of...

Revolutionizing Digital Art: Researchers at Seoul National University Introduce a Novel Approach to Collage Creation Using Reinforcement Learning

Artistic collage creation, a field deeply intertwined with human artistry, has sparked interest in artificial intelligence (AI). The challenge arises from the need to...

This AI Paper Introduces Φ-SO: A Physical Symbolic Optimization Framework that Uses Deep Reinforcement Learning to Discover Physical Laws from Data

Artificial Intelligence and Deep learning have brought about some great advancements in the field of technology. They are enabling robots to perform activities that...

Duke University Researchers Propose Policy Stitching: A Novel AI Framework that Facilitates Robot Transfer Learning for Novel Combinations of Robots and Tasks

In robotics, researchers face challenges in using reinforcement learning (RL) to teach robots new skills, as these skills can be sensitive to changes in...

Galileo Introduces Luna: An Evaluation Foundation Model to Catch Language Model Hallucinations with High...

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The Galileo Luna represents a significant advancement in language model evaluation. It is specifically designed to address the prevalent issue of hallucinations in large...

Yandex Introduces YaFSDP: An Open-Source AI Tool that Promises to Revolutionize LLM Training by...

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Developing large language models requires substantial investments in time and GPU resources, translating directly into high costs. The larger the model, the more pronounced...

Gretel AI Releases a New Multilingual Synthetic Financial Dataset on HuggingFace 🤗 for AI...

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Detecting personally identifiable information PII in documents involves navigating various regulations, such as the EU’s General Data Protection Regulation (GDPR) and various U.S. financial...

Snowflake AI Research Team Unveils Arctic: An Open-Source Enterprise-Grade Large Language Model (LLM) with...

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Snowflake AI Research has launched the Arctic, a cutting-edge open-source large language model (LLM) specifically designed for enterprise AI applications, setting a new standard...

Google DeepMind Releases RecurrentGemma: One of the Strongest 2B-Parameter Open Language Models Designed for...

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Language models are the backbone of modern artificial intelligence systems, enabling machines to understand and generate human-like text. These models, which process and predict...

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